High-res multi-view results

This table lists the benchmark results for the high-res multi-view scenario. The following metrics are evaluated:

Accuracy [%]: The fraction of the reconstruction which is closer to the ground truth than the evaluation threshold distance (*). Larger is better.
Completeness [%]: The fraction of the ground truth which is closer to the reconstruction than the evaluation threshold distance (*). Larger is better.
F₁ score [%]: The harmonic mean of accuracy and completeness, used to rank methods based on both metrics. Larger is better.
Time [s]: The runtime of the method. Smaller is better.

(*) For exact definitions, detailing how potentially incomplete ground truth is taken into account, see our paper.

The datasets are grouped into different categories, and result averages are computed for a category and method if results of the method are available for all datasets within the category. Note that the category "all" includes both the high-res multi-view and the low-res many-view scenarios.

Methods with suffix _ROB may participate in the Robust Vision Challenge.

Click a dataset result cell to show a visualization of the reconstruction. For training datasets, ground truth and accuracy / completeness visualizations are also available. The visualizations may not work with mobile browsers.

Method	all	high-res multi-view	indoor	outdoor	botani.	boulde.	bridge	door	exhibi.	lectur.	living.	lounge	observ.	old co.	statue	terrac.

LTVRE_ROB	98.40 1	99.67 3	99.71 2	99.56 26	99.85 16	99.11 64	99.90 1	99.78 36	99.63 28	99.78 39	99.67 30	99.48 10	99.81 224	99.30 62	99.97 21	99.77 53
Andreas Kuhn, Heiko HirschmÃ¼ller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016
3Dnovator	98.27 2	98.81 127	98.73 130	99.05 143	98.76 350	97.81 202	99.25 43	99.30 250	98.57 174	98.55 306	99.33 118	97.95 140	99.90 81	97.16 252	99.67 244	99.44 208

3Dnovator+	97.89 3	98.69 151	98.51 171	99.24 106	98.81 343	98.40 120	99.02 70	99.19 288	98.99 124	98.07 354	99.28 129	97.11 216	99.84 177	96.84 287	99.32 352	99.47 195

DeepC-MVS	97.60 4	98.97 99	98.93 101	99.10 128	99.35 197	97.98 174	98.01 213	99.46 172	97.56 271	99.54 79	99.50 68	98.97 29	99.84 177	98.06 162	99.92 71	99.49 176
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepPCF-MVS	96.93 5	98.32 222	98.01 257	99.23 108	98.39 414	98.97 73	95.03 467	99.18 292	96.88 340	99.33 137	98.78 288	98.16 122	99.28 473	96.74 296	99.62 266	99.44 208

DeepC-MVS_fast	96.85 6	98.30 227	98.15 242	98.75 211	98.61 384	97.23 256	97.76 256	99.09 312	97.31 303	98.75 268	98.66 319	97.56 177	99.64 368	96.10 357	99.55 295	99.39 230
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
OpenMVS	96.65 7	97.09 351	96.68 364	98.32 292	98.32 418	97.16 269	98.86 92	99.37 213	89.48 516	96.29 469	99.15 175	96.56 255	99.90 81	92.90 458	99.20 377	97.89 464

ACMH	96.65 7	99.25 40	99.24 53	99.26 101	99.72 45	98.38 122	99.07 65	99.55 124	98.30 194	99.65 63	99.45 84	99.22 17	99.76 270	98.44 131	99.77 172	99.64 86
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMH+	96.62 9	99.08 79	99.00 94	99.33 89	99.71 49	98.83 86	98.60 121	99.58 101	99.11 100	99.53 83	99.18 163	98.81 39	99.67 343	96.71 301	99.77 172	99.50 168

COLMAP_ROB	96.50 10	98.99 94	98.85 118	99.41 69	99.58 94	99.10 65	98.74 99	99.56 119	99.09 110	99.33 137	99.19 159	98.40 86	99.72 306	95.98 360	99.76 188	99.42 217
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
TAPA-MVS	96.21 11	96.63 375	95.95 398	98.65 230	98.93 314	98.09 155	96.93 356	99.28 262	83.58 534	98.13 348	97.78 422	96.13 279	99.40 453	93.52 441	99.29 360	98.45 429
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMM	96.08 12	98.91 106	98.73 130	99.48 57	99.55 117	99.14 57	98.07 200	99.37 213	97.62 262	99.04 201	98.96 241	98.84 37	99.79 246	97.43 232	99.65 254	99.49 176
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
HY-MVS	95.94 13	95.90 416	95.35 424	97.55 385	97.95 451	94.79 396	98.81 98	96.94 466	92.28 492	95.17 495	98.57 337	89.90 431	99.75 282	91.20 494	97.33 495	98.10 453

OpenMVS_ROB	95.38 14	95.84 419	95.18 435	97.81 349	98.41 413	97.15 270	97.37 319	98.62 392	83.86 533	98.65 283	98.37 364	94.29 355	99.68 338	88.41 513	98.62 439	96.60 505

ACMP	95.32 15	98.41 203	98.09 247	99.36 74	99.51 134	98.79 89	97.68 268	99.38 209	95.76 404	98.81 258	98.82 280	98.36 90	99.82 207	94.75 400	99.77 172	99.48 187
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PLC	94.65 16	96.51 380	95.73 404	98.85 180	98.75 352	97.91 185	96.42 396	99.06 316	90.94 508	95.59 483	97.38 450	94.41 347	99.59 392	90.93 499	98.04 471	99.05 343
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
PVSNet	93.40 17	95.67 423	95.70 405	95.57 481	98.83 337	88.57 514	92.50 524	97.72 433	92.69 487	96.49 466	96.44 475	93.72 371	99.43 449	93.61 436	99.28 361	98.71 405

PCF-MVS	92.86 18	94.36 453	93.00 472	98.42 279	98.70 364	97.56 223	93.16 521	99.11 309	79.59 538	97.55 396	97.43 447	92.19 402	99.73 296	79.85 535	99.45 323	97.97 461
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
IB-MVS	91.63 19	92.24 492	90.90 496	96.27 449	97.22 494	91.24 491	94.36 492	93.33 522	92.37 490	92.24 529	94.58 514	66.20 533	99.89 97	93.16 452	94.63 528	97.66 479
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021
PMVS	91.26 20	97.86 283	97.94 267	97.65 370	99.71 49	97.94 181	98.52 130	98.68 386	98.99 124	97.52 399	99.35 111	97.41 194	98.18 510	91.59 487	99.67 244	96.82 501
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PVSNet_0	89.98 21	91.15 498	90.30 500	93.70 510	97.72 464	84.34 535	90.24 531	97.42 443	90.20 512	93.79 518	93.09 524	90.90 423	98.89 497	86.57 522	72.76 543	97.87 466

MVE	83.40 22	92.50 487	91.92 489	94.25 501	98.83 337	91.64 479	92.71 522	83.52 545	95.92 393	86.46 540	95.46 498	95.20 319	95.40 537	80.51 534	98.64 435	95.73 517
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CMPMVS	75.91 23	96.29 395	95.44 419	98.84 186	96.25 524	98.69 98	97.02 347	99.12 307	88.90 520	97.83 376	98.86 267	89.51 436	98.90 496	91.92 479	99.51 307	98.92 371
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
onestephybrid01		98.40 206	98.39 195	98.42 279	99.05 287	96.23 323	96.73 370	99.41 200	98.18 212	98.65 283	99.02 212	97.02 221	99.69 326	97.73 202	99.70 226	99.33 266

nocashy02		98.57 177	98.66 146	98.31 294	99.20 242	95.89 339	96.92 358	99.57 109	98.71 158	99.02 205	99.04 208	97.48 190	99.71 308	98.28 145	99.70 226	99.35 256

PMatch-SfM		97.89 277	97.64 297	98.66 228	99.26 227	97.44 236	96.08 421	99.51 142	96.72 351	98.47 316	99.13 181	93.62 374	99.70 316	97.14 255	98.80 421	98.83 383

DenseAffine		98.10 254	97.86 276	98.84 186	99.32 204	97.93 182	96.62 380	99.76 39	96.68 355	98.65 283	98.72 300	94.46 345	99.33 464	96.76 293	99.75 192	99.25 295

ArgMatch-SfM		97.96 272	97.72 288	98.66 228	99.02 299	97.33 242	96.49 390	99.52 140	95.46 417	98.71 275	98.29 378	96.14 277	99.69 326	96.30 342	99.56 290	98.97 361

MASt3R-SfM		96.02 407	95.82 401	96.60 437	97.03 502	94.90 391	94.26 495	98.53 401	88.40 525	98.41 323	98.67 315	92.39 397	97.62 520	95.31 387	99.41 335	97.29 492

hybridnocas07		98.32 222	98.37 201	98.17 311	99.14 264	95.51 355	96.67 375	99.56 119	97.85 243	98.75 268	98.95 245	96.65 251	99.63 371	98.00 170	99.78 164	99.37 242

cashybrid2		99.12 69	99.12 71	99.09 132	99.53 127	98.08 159	98.34 163	99.66 70	99.35 64	99.35 130	99.23 150	98.39 88	99.72 306	98.46 129	99.81 140	99.47 195

dtuonlycased		97.70 298	98.19 235	96.24 451	99.75 34	89.51 511	94.69 479	99.64 78	98.23 201	99.46 101	98.57 337	98.25 107	99.85 158	95.65 377	99.44 330	99.36 250

dtuonly		96.49 383	97.28 319	94.10 504	98.80 346	83.27 538	93.66 511	99.48 157	95.10 430	97.87 371	98.30 375	95.61 305	99.68 338	96.98 272	99.75 192	99.33 266

dtuplus		98.32 222	98.39 195	98.10 319	99.15 262	95.29 373	96.68 373	99.51 142	97.32 301	99.18 179	99.15 175	97.61 172	99.62 375	97.19 249	99.74 195	99.38 239

SIFT-UM-Cal		96.49 383	96.62 371	96.12 462	98.13 442	97.89 188	93.35 517	98.44 406	95.48 416	98.63 287	98.34 368	95.45 313	97.45 521	92.22 476	99.50 315	93.02 532

SIFT-NCM-Cal		96.56 378	96.68 364	96.20 455	98.27 425	98.44 118	94.40 490	96.67 473	95.29 424	97.63 388	98.17 389	96.40 263	96.59 533	93.61 436	99.66 252	93.57 525

SIFT-CM-Cal		96.28 396	96.31 389	96.16 459	98.39 414	98.11 151	93.46 516	96.47 479	94.81 440	98.49 313	98.43 357	94.48 344	97.34 524	92.60 470	99.70 226	93.02 532

SIFT-PCN-Cal		96.34 391	96.46 383	96.01 466	98.17 436	96.89 288	93.48 515	97.35 448	94.84 438	99.35 130	98.30 375	94.70 339	97.92 514	92.03 477	99.88 95	93.21 531

SIFT-NN-UMatch		95.38 436	95.26 429	95.75 475	98.25 426	97.78 204	93.24 520	95.66 499	94.01 465	95.10 497	97.47 445	93.12 382	96.78 530	92.42 473	98.04 471	92.69 537

SIFT-NN-NCMNet		95.39 435	95.22 432	95.92 468	98.29 421	98.34 129	93.58 513	94.60 507	94.07 463	94.84 501	97.53 437	94.37 351	96.62 531	91.01 497	98.64 435	92.80 535

SIFT-NN-CMatch		95.63 426	95.48 415	96.08 463	98.24 428	98.00 169	92.71 522	94.29 511	94.20 457	95.85 479	97.26 455	95.72 302	97.01 526	91.99 478	99.02 401	93.23 529

SIFT-NN-PointCN		96.06 404	96.11 395	95.91 469	97.88 455	97.73 210	93.49 514	97.51 442	93.22 475	96.57 456	98.26 380	96.23 274	96.60 532	92.54 471	99.27 362	93.40 527

XFeat-NN		89.63 500	89.13 503	91.14 521	90.93 545	90.02 508	84.90 538	94.05 517	88.10 526	92.89 524	93.33 523	78.74 507	90.89 542	83.46 528	95.72 522	92.52 538

ALIKED-NN		94.29 457	93.41 466	96.94 421	96.18 525	97.66 215	94.90 471	98.68 386	88.85 521	90.43 533	96.81 466	89.82 432	96.59 533	86.67 521	98.33 449	96.58 506

SP-NN		94.67 449	94.44 451	95.36 489	95.12 533	95.23 378	94.27 494	96.10 486	94.46 448	90.91 532	95.76 490	91.47 416	93.87 540	95.23 390	96.62 506	97.00 496

SIFT-NN		92.96 481	92.79 475	93.46 512	96.92 504	96.45 315	91.89 528	94.39 509	92.91 483	92.54 526	95.46 498	88.26 448	90.71 543	85.22 524	97.52 482	93.22 530

hybridcas		99.08 79	99.13 70	98.92 171	99.54 123	97.61 221	98.22 177	99.66 70	99.27 74	99.40 117	99.24 144	98.47 77	99.70 316	98.59 118	99.80 152	99.46 198

GLUNet-SfM		86.26 504	84.68 506	91.01 522	80.58 548	83.56 536	78.04 539	93.59 519	76.70 539	95.29 494	94.72 512	77.51 513	94.26 539	66.39 542	99.33 349	95.20 519

PDCNetPlus		95.22 440	94.73 447	96.70 435	97.85 457	91.14 494	93.94 505	99.97 1	93.06 480	98.95 222	98.89 262	74.32 517	99.14 483	95.63 378	99.93 57	99.82 36

hybrid		98.22 239	98.27 221	98.08 324	99.13 267	95.24 375	96.61 381	99.53 134	97.43 290	98.46 317	98.97 237	96.75 245	99.65 363	97.84 187	99.69 232	99.35 256

RoMa-SfM		98.46 198	98.27 221	99.02 149	99.35 197	98.32 130	97.56 290	99.70 53	95.88 395	99.38 121	98.65 321	96.41 262	99.46 442	97.78 192	99.71 217	99.28 285

DKM		98.18 247	97.95 264	98.85 180	99.35 197	98.31 131	96.68 373	99.69 56	96.90 339	98.61 293	98.77 290	94.41 347	98.93 493	97.32 240	99.84 114	99.32 271

ELoFTR		97.81 292	97.74 284	98.04 330	99.39 183	95.79 346	97.28 331	99.58 101	94.13 459	99.38 121	99.37 104	93.31 377	99.60 387	97.23 246	99.96 28	98.74 403

MatchFormer		97.07 353	96.92 345	97.49 391	98.44 407	95.92 337	96.79 363	99.14 305	93.08 479	99.32 143	99.10 190	93.89 365	99.03 486	92.78 464	99.78 164	97.52 484

LoFTR		97.97 271	97.79 280	98.53 263	98.80 346	97.47 231	97.01 348	99.55 124	95.55 411	99.46 101	99.22 152	94.22 357	99.44 447	96.45 331	99.82 133	98.68 412

ALIKED-LG		97.10 349	96.63 370	98.50 270	97.96 450	98.68 99	97.75 259	99.68 63	95.86 396	98.36 331	98.33 372	91.58 412	99.04 485	90.87 502	99.31 354	97.77 473

SP-DiffGlue		96.87 365	96.76 358	97.21 406	95.17 532	96.88 290	96.12 418	98.93 341	96.51 360	98.37 329	97.55 436	93.65 373	97.83 515	96.11 356	98.45 447	96.92 497

SP-LightGlue		97.22 341	97.01 339	97.88 343	97.33 491	97.19 263	96.38 398	99.08 314	97.28 306	96.53 459	97.50 441	92.36 398	98.70 502	97.84 187	98.76 423	97.74 475

SP-SuperGlue		97.31 331	97.23 324	97.57 384	96.96 503	97.24 255	96.26 409	98.76 376	97.68 257	96.88 441	97.85 417	94.32 353	98.01 512	97.76 198	98.57 442	97.45 487

SIFT-UMatch		96.33 392	96.47 381	95.89 470	98.29 421	97.95 179	93.84 507	97.24 453	95.78 403	98.72 272	98.04 402	93.45 376	96.81 529	93.14 453	99.73 199	92.91 534

SIFT-NCMNet		96.30 394	96.40 385	96.03 465	97.80 462	97.68 214	92.34 526	96.94 466	95.55 411	98.84 251	98.63 327	94.17 358	97.63 519	93.57 440	99.71 217	92.77 536

SIFT-ConvMatch		96.57 377	96.62 371	96.43 442	98.20 432	98.27 134	93.88 506	96.88 469	95.29 424	98.88 242	98.25 381	95.18 321	97.43 522	93.22 451	99.83 126	93.59 524

SIFT-PointCN		96.45 388	96.47 381	96.39 444	98.13 442	97.54 225	93.31 518	97.23 454	94.67 443	98.68 279	98.32 373	94.64 340	97.81 516	93.50 443	99.77 172	93.83 522

XFeat-MNN		93.41 473	92.98 473	94.68 497	92.63 539	92.92 458	89.72 535	95.81 493	92.10 494	97.23 419	96.29 479	84.95 474	97.31 525	89.60 510	98.54 444	93.81 523

ALIKED-MNN		95.97 413	95.30 428	98.00 333	97.66 474	98.12 150	96.98 351	99.41 200	91.11 506	94.04 514	97.30 454	91.56 413	98.61 504	89.99 507	99.63 262	97.28 493

SP-MNN		96.46 387	96.24 394	97.10 412	96.71 511	95.98 334	96.00 424	97.33 449	95.82 400	94.93 500	97.10 463	93.70 372	98.01 512	96.30 342	98.30 453	97.30 491

SIFT-MNN		95.92 415	95.97 397	95.74 477	98.18 434	98.00 169	94.17 497	96.99 461	95.74 405	97.16 420	97.90 413	90.71 424	95.79 535	93.71 434	99.21 375	93.44 526

casdiffseed414692147		99.09 73	99.12 71	99.01 151	99.55 117	97.91 185	98.30 165	99.68 63	99.04 119	99.19 174	99.37 104	98.98 28	99.61 383	98.13 155	99.83 126	99.50 168

gbinet_0.2-2-1-0.02		95.44 433	94.55 448	98.14 315	95.99 529	95.34 371	94.71 475	98.29 415	96.00 389	96.05 476	90.50 538	84.99 473	99.79 246	97.33 238	97.07 500	99.28 285

0.3-1-1-0.015		87.27 503	84.50 507	95.57 481	91.70 541	90.77 500	89.41 536	92.04 529	88.98 519	82.46 543	81.35 541	60.36 544	99.50 427	92.96 455	81.23 539	96.45 507

0.4-1-1-0.1		88.42 501	85.91 504	95.94 467	93.08 538	91.54 480	90.99 530	92.04 529	89.96 515	84.83 541	83.25 540	63.75 540	99.52 420	93.25 449	82.07 537	96.75 502

0.4-1-1-0.2		87.49 502	84.89 505	95.31 490	91.33 544	90.08 507	88.47 537	92.07 528	88.70 522	84.06 542	81.08 542	63.62 541	99.49 431	92.93 457	81.71 538	96.37 508

wanda-best-256-512		95.48 431	94.74 445	97.68 364	96.53 515	94.12 419	94.17 497	98.57 397	95.84 397	96.71 448	91.16 534	86.05 463	99.76 270	97.57 216	96.09 514	99.17 325

usedtu_dtu_shiyan2		98.99 94	98.86 115	99.39 72	99.73 38	98.71 97	99.05 68	99.47 167	99.16 94	99.49 94	99.12 185	96.34 269	99.93 53	98.05 164	99.36 342	99.54 143

usedtu_dtu_shiyan1		97.37 325	97.13 332	98.11 317	99.03 292	95.40 366	94.47 487	98.99 334	96.87 341	97.97 363	97.81 420	92.12 404	99.75 282	97.49 229	99.43 332	99.16 331

blended_shiyan8		95.98 411	95.33 425	97.94 338	97.05 501	94.87 394	95.34 457	98.59 394	96.17 377	97.09 424	92.39 529	87.62 452	99.76 270	97.65 208	96.05 520	99.20 311

E5new		99.05 83	99.11 74	98.85 180	99.60 88	97.30 246	98.42 151	99.63 81	98.73 151	99.26 156	99.39 100	98.71 51	99.70 316	98.43 133	99.84 114	99.54 143

FE-blended-shiyan7		95.48 431	94.74 445	97.68 364	96.53 515	94.12 419	94.17 497	98.57 397	95.84 397	96.71 448	91.16 534	86.05 463	99.76 270	97.57 216	96.09 514	99.17 325

E6new		99.05 83	99.11 74	98.85 180	99.60 88	97.30 246	98.42 151	99.63 81	98.73 151	99.26 156	99.39 100	98.71 51	99.70 316	98.43 133	99.84 114	99.54 143

blended_shiyan6		95.99 410	95.33 425	97.95 337	97.06 499	94.89 392	95.34 457	98.58 395	96.17 377	97.06 426	92.41 528	87.64 451	99.76 270	97.64 209	96.09 514	99.19 317

usedtu_blend_shiyan5		96.20 402	95.62 408	97.94 338	96.53 515	94.93 389	98.83 96	99.59 98	98.89 138	96.71 448	91.16 534	86.05 463	99.73 296	96.70 302	96.09 514	99.17 325

blend_shiyan4		92.09 494	90.16 501	97.88 343	96.78 509	94.93 389	95.24 461	98.58 395	96.22 375	96.07 474	91.42 533	63.46 542	99.73 296	96.70 302	76.98 542	98.98 357

E6		99.05 83	99.11 74	98.85 180	99.60 88	97.30 246	98.42 151	99.63 81	98.73 151	99.26 156	99.39 100	98.71 51	99.70 316	98.43 133	99.84 114	99.54 143

E5		99.05 83	99.11 74	98.85 180	99.60 88	97.30 246	98.42 151	99.63 81	98.73 151	99.26 156	99.39 100	98.71 51	99.70 316	98.43 133	99.84 114	99.54 143

FE-MVSNET3		97.37 325	97.13 332	98.11 317	99.03 292	95.40 366	94.47 487	98.99 334	96.87 341	97.97 363	97.81 420	92.12 404	99.75 282	97.49 229	99.43 332	99.16 331

E4		98.87 112	98.88 108	98.81 192	99.52 131	97.23 256	97.62 279	99.61 90	98.58 172	99.18 179	99.33 118	98.29 99	99.69 326	97.99 173	99.83 126	99.52 160

E3new		98.41 203	98.34 207	98.62 238	99.19 246	96.90 287	97.32 323	99.50 147	97.40 293	98.63 287	98.92 250	97.21 209	99.65 363	97.34 236	99.52 304	99.31 276

FE-MVSNET2		99.15 57	99.22 54	98.94 165	99.70 57	97.49 227	98.62 118	99.67 69	98.85 145	99.34 134	99.54 62	98.47 77	99.81 224	98.93 92	99.91 80	99.51 164

fmvsm_s_conf0.5_n_11		99.21 47	99.34 35	98.80 195	99.48 156	96.56 308	97.97 226	99.69 56	99.63 28	99.84 30	99.54 62	98.21 115	99.94 41	99.76 23	99.95 39	99.88 20

E2		98.70 147	98.68 141	98.73 217	99.40 181	97.10 273	97.48 302	99.57 109	98.09 224	99.00 207	99.20 156	97.90 143	99.67 343	97.73 202	99.77 172	99.43 212

MED-MVS test				99.45 64	99.58 94	98.93 79	98.68 109	99.60 92	96.46 366	99.53 83	98.77 290		99.83 195	96.67 306	99.64 256	99.58 117

MED-MVS		99.01 90	98.84 119	99.52 44	99.58 94	98.93 79	98.68 109	99.60 92	98.85 145	99.53 83	99.16 169	97.87 149	99.83 195	96.67 306	99.64 256	99.81 41

E3		98.69 151	98.68 141	98.73 217	99.40 181	97.10 273	97.48 302	99.57 109	98.09 224	99.00 207	99.20 156	97.90 143	99.67 343	97.73 202	99.77 172	99.43 212

TestfortrainingZip a		99.09 73	98.92 102	99.61 13	99.58 94	99.17 43	98.68 109	99.27 265	98.85 145	99.61 70	99.16 169	97.14 213	99.86 144	98.39 138	99.57 286	99.81 41

TestfortrainingZip				98.97 160	98.30 420	98.43 119	98.68 109	98.26 416	97.76 251	98.86 248	98.16 391	95.15 322	99.47 438		97.55 481	99.02 350

fmvsm_s_conf0.5_n_10		99.15 57	99.27 47	98.78 202	99.47 159	96.56 308	97.75 259	99.71 48	99.60 35	99.74 46	99.44 85	97.96 139	99.95 25	99.86 4	99.94 51	99.82 36

viewdifsd2359ckpt07		98.71 142	98.86 115	98.26 299	99.43 174	95.65 349	97.20 338	99.66 70	99.20 84	99.29 148	99.01 224	98.29 99	99.73 296	97.92 178	99.75 192	99.39 230

viewdifsd2359ckpt09		98.13 253	97.92 270	98.77 207	99.18 254	97.35 240	97.29 327	99.53 134	95.81 401	98.09 352	98.47 353	96.34 269	99.66 356	97.02 265	99.51 307	99.29 282

viewdifsd2359ckpt13		98.39 213	98.29 217	98.70 221	99.26 227	97.19 263	97.51 298	99.48 157	96.94 334	98.58 300	98.82 280	97.47 192	99.55 408	97.21 248	99.33 349	99.34 260

viewcassd2359sk11		98.55 183	98.51 171	98.67 226	99.29 212	96.99 279	97.39 313	99.54 130	97.73 253	98.81 258	99.08 197	97.55 178	99.66 356	97.52 223	99.67 244	99.36 250

viewdifsd2359ckpt11		98.84 119	99.04 87	98.24 303	99.56 111	95.51 355	97.38 315	99.70 53	99.16 94	99.57 72	99.40 97	98.26 105	99.71 308	98.55 125	99.82 133	99.50 168

viewmacassd2359aftdt		98.86 116	98.87 111	98.83 188	99.53 127	97.32 245	97.70 266	99.64 78	98.22 203	99.25 164	99.27 131	98.40 86	99.61 383	97.98 174	99.87 100	99.55 137

viewmsd2359difaftdt		98.84 119	99.04 87	98.24 303	99.56 111	95.51 355	97.38 315	99.70 53	99.16 94	99.57 72	99.40 97	98.26 105	99.71 308	98.55 125	99.82 133	99.50 168

diffmvs_AUTHOR		98.50 194	98.59 161	98.23 306	99.35 197	95.48 360	96.61 381	99.60 92	98.37 185	98.90 235	99.00 228	97.37 197	99.76 270	98.22 149	99.85 109	99.46 198

FE-MVSNET		98.59 174	98.50 174	98.87 177	99.58 94	97.30 246	98.08 196	99.74 44	96.94 334	98.97 216	99.10 190	96.94 227	99.74 289	97.33 238	99.86 107	99.55 137

fmvsm_l_conf0.5_n_9		99.32 32	99.43 24	98.98 158	99.59 92	97.18 266	97.44 310	99.83 26	99.56 39	99.91 12	99.34 115	99.36 13	99.93 53	99.83 10	99.98 12	99.85 30

mamba_0408		98.80 129	98.88 108	98.55 256	99.27 218	96.50 311	98.00 214	99.60 92	98.93 132	99.22 169	98.84 275	98.59 67	99.89 97	97.74 200	99.72 208	99.27 288

icg_test_0407_2		98.20 244	98.38 199	97.65 370	99.03 292	94.03 425	95.78 440	99.45 176	98.16 216	99.06 191	98.71 302	98.27 103	99.68 338	97.50 224	99.45 323	99.22 306

SSM_04072		98.80 129	98.88 108	98.56 254	99.27 218	96.50 311	98.00 214	99.60 92	98.93 132	99.22 169	98.84 275	98.59 67	99.90 81	97.74 200	99.72 208	99.27 288

SSM_0407		98.86 116	98.96 100	98.55 256	99.27 218	96.50 311	98.04 205	99.66 70	99.09 110	99.22 169	99.02 212	98.79 43	99.87 135	97.87 184	99.72 208	99.27 288

viewmambaseed2359dif		98.19 245	98.26 224	97.99 335	99.02 299	95.03 386	96.59 384	99.53 134	96.21 376	99.00 207	98.99 230	97.62 170	99.61 383	97.62 211	99.72 208	99.33 266

IMVS_0407		98.39 213	98.64 150	97.66 368	99.03 292	94.03 425	98.10 193	99.45 176	98.16 216	99.06 191	98.71 302	98.27 103	99.71 308	97.50 224	99.45 323	99.22 306

viewmanbaseed2359cas		98.58 176	98.54 167	98.70 221	99.28 215	97.13 272	97.47 306	99.55 124	97.55 273	98.96 221	98.92 250	97.77 157	99.59 392	97.59 215	99.77 172	99.39 230

IMVS_0404		98.07 259	98.20 231	97.69 363	99.03 292	94.03 425	96.67 375	99.45 176	98.16 216	98.03 359	98.71 302	96.80 238	99.82 207	97.50 224	99.45 323	99.22 306

SSM_0404		98.90 108	99.01 92	98.57 249	99.42 176	96.59 303	98.13 186	99.66 70	99.09 110	99.30 147	99.02 212	98.79 43	99.89 97	97.87 184	99.80 152	99.23 301

IMVS_0403		98.34 217	98.56 164	97.66 368	99.03 292	94.03 425	97.98 222	99.45 176	98.16 216	98.89 238	98.71 302	97.90 143	99.74 289	97.50 224	99.45 323	99.22 306

SD_0403		96.28 396	95.83 400	97.64 373	98.72 356	94.30 412	98.87 89	98.77 374	97.80 247	96.53 459	98.02 404	97.34 199	99.47 438	76.93 538	99.48 319	99.16 331

fmvsm_s_conf0.5_n_9		99.17 52	99.38 28	98.53 263	99.51 134	95.82 344	97.62 279	99.78 36	99.72 14	99.90 14	99.48 75	98.66 59	99.89 97	99.85 6	99.93 57	99.89 16

ME-MVS		98.61 170	98.33 212	99.44 65	99.24 230	98.93 79	97.45 308	99.06 316	98.14 222	99.06 191	98.77 290	96.97 226	99.82 207	96.67 306	99.64 256	99.58 117

NormalMVS		98.26 234	97.97 263	99.15 121	99.64 77	97.83 194	98.28 167	99.43 190	99.24 77	98.80 260	98.85 270	89.76 433	99.94 41	98.04 165	99.67 244	99.68 73

lecture		99.25 40	99.12 71	99.62 9	99.64 77	99.40 11	98.89 88	99.51 142	99.19 89	99.37 125	99.25 142	98.36 90	99.88 115	98.23 148	99.67 244	99.59 109

SymmetryMVS		98.05 261	97.71 290	99.09 132	99.29 212	97.83 194	98.28 167	97.64 440	99.24 77	98.80 260	98.85 270	89.76 433	99.94 41	98.04 165	99.50 315	99.49 176

Elysia		99.15 57	99.14 68	99.18 113	99.63 83	97.92 183	98.50 137	99.43 190	99.67 20	99.70 51	99.13 181	96.66 249	99.98 4	99.54 44	99.96 28	99.64 86

StellarMVS		99.15 57	99.14 68	99.18 113	99.63 83	97.92 183	98.50 137	99.43 190	99.67 20	99.70 51	99.13 181	96.66 249	99.98 4	99.54 44	99.96 28	99.64 86

KinetiMVS		99.03 88	99.02 90	99.03 146	99.70 57	97.48 230	98.43 148	99.29 258	99.70 15	99.60 71	99.07 198	96.13 279	99.94 41	99.42 55	99.87 100	99.68 73

LuminaMVS		98.39 213	98.20 231	98.98 158	99.50 140	97.49 227	97.78 250	97.69 435	98.75 150	99.49 94	99.25 142	92.30 401	99.94 41	99.14 75	99.88 95	99.50 168

VortexMVS		97.98 270	98.31 214	97.02 416	98.88 328	91.45 483	98.03 207	99.47 167	98.65 160	99.55 77	99.47 78	91.49 415	99.81 224	99.32 60	99.91 80	99.80 45

AstraMVS		98.16 252	98.07 252	98.41 281	99.51 134	95.86 341	98.00 214	95.14 502	98.97 127	99.43 108	99.24 144	93.25 378	99.84 177	99.21 70	99.87 100	99.54 143

guyue		98.01 265	97.93 269	98.26 299	99.45 167	95.48 360	98.08 196	96.24 482	98.89 138	99.34 134	99.14 179	91.32 418	99.82 207	99.07 80	99.83 126	99.48 187

sc_t1		99.62 7	99.66 8	99.53 38	99.82 19	99.09 68	99.50 11	99.63 81	99.88 4	99.86 24	99.80 11	99.03 24	99.89 97	99.48 52	99.93 57	99.60 102

tt0320-xc		99.64 5	99.68 5	99.50 54	99.72 45	98.98 71	99.51 10	99.85 19	99.86 6	99.88 21	99.82 5	99.02 26	99.90 81	99.54 44	99.95 39	99.61 100

tt0320		99.61 8	99.65 9	99.48 57	99.71 49	98.94 78	99.54 8	99.83 26	99.87 5	99.89 18	99.82 5	98.75 47	99.90 81	99.54 44	99.95 39	99.59 109

fmvsm_s_conf0.5_n_8		99.13 66	99.26 50	98.74 215	99.51 134	96.44 316	97.65 274	99.65 76	99.66 23	99.78 39	99.48 75	97.92 142	99.93 53	99.72 30	99.95 39	99.87 22

fmvsm_s_conf0.5_n_7		98.83 122	99.04 87	98.20 308	99.30 210	94.83 395	97.23 333	99.36 217	98.64 161	99.84 30	99.43 88	98.10 127	99.91 74	99.56 41	99.96 28	99.87 22

fmvsm_s_conf0.5_n_6		99.08 79	99.21 57	98.69 223	99.36 192	96.51 310	97.62 279	99.68 63	98.43 183	99.85 27	99.10 190	99.12 23	99.88 115	99.77 22	99.92 71	99.67 78

fmvsm_s_conf0.5_n_5		99.07 82	99.10 80	98.99 154	99.47 159	97.22 259	97.40 312	99.83 26	97.61 265	99.85 27	99.30 125	98.80 41	99.95 25	99.71 32	99.90 88	99.78 50

fmvsm_s_conf0.5_n_4		99.01 90	99.22 54	98.38 285	99.31 206	95.48 360	97.56 290	99.73 45	98.87 140	99.75 44	99.27 131	98.80 41	99.86 144	99.80 17	99.90 88	99.81 41

SSC-MVS3.2		98.53 188	98.79 124	97.74 358	99.46 162	93.62 448	96.45 392	99.34 229	99.33 66	98.93 231	98.70 309	97.90 143	99.90 81	99.12 76	99.92 71	99.69 72

testing3-2		93.78 466	93.91 457	93.39 515	98.82 340	81.72 544	97.76 256	95.28 500	98.60 168	96.54 458	96.66 469	65.85 535	99.62 375	96.65 310	98.99 406	98.82 385

myMVS_eth3d28		92.92 483	92.31 479	94.77 495	97.84 458	87.59 521	96.19 412	96.11 485	97.08 326	94.27 508	93.49 521	66.07 534	98.78 499	91.78 482	97.93 475	97.92 463

UWE-MVS-28		90.22 499	89.28 502	93.02 519	94.50 536	82.87 540	96.52 388	87.51 540	95.21 428	92.36 528	96.04 481	71.57 521	98.25 509	72.04 540	97.77 477	97.94 462

fmvsm_l_conf0.5_n_3		99.45 18	99.48 18	99.34 83	99.59 92	98.21 143	97.82 244	99.84 23	99.41 57	99.92 8	99.41 94	99.51 8	99.95 25	99.84 9	99.97 21	99.87 22

fmvsm_s_conf0.5_n_3		99.22 46	99.37 31	98.78 202	99.46 162	96.58 306	97.65 274	99.72 46	99.47 47	99.86 24	99.50 68	98.94 31	99.89 97	99.75 26	99.97 21	99.86 28

fmvsm_s_conf0.5_n_2		99.14 62	99.31 41	98.63 236	99.49 148	96.08 331	97.38 315	99.81 32	99.48 44	99.84 30	99.57 49	98.46 82	99.89 97	99.82 12	99.97 21	99.91 13

fmvsm_s_conf0.1_n_2		99.20 50	99.38 28	98.65 230	99.69 61	96.08 331	97.49 301	99.90 12	99.53 41	99.88 21	99.64 37	98.51 76	99.90 81	99.83 10	99.98 12	99.97 4

GDP-MVS		97.50 311	97.11 334	98.67 226	99.02 299	96.85 291	98.16 183	99.71 48	98.32 192	98.52 311	98.54 340	83.39 488	99.95 25	98.79 101	99.56 290	99.19 317

BP-MVS1		97.40 323	96.97 341	98.71 220	99.07 279	96.81 293	98.34 163	97.18 455	98.58 172	98.17 341	98.61 332	84.01 484	99.94 41	98.97 89	99.78 164	99.37 242

reproduce_monomvs		95.00 446	95.25 430	94.22 502	97.51 485	83.34 537	97.86 240	98.44 406	98.51 179	99.29 148	99.30 125	67.68 528	99.56 404	98.89 96	99.81 140	99.77 53

mmtdpeth		99.30 33	99.42 25	98.92 171	99.58 94	96.89 288	99.48 13	99.92 8	99.92 2	98.26 338	99.80 11	98.33 96	99.91 74	99.56 41	99.95 39	99.97 4

reproduce_model		99.15 57	98.97 98	99.67 4	99.33 203	99.44 9	98.15 184	99.47 167	99.12 99	99.52 87	99.32 123	98.31 97	99.90 81	97.78 192	99.73 199	99.66 80

reproduce-ours		99.09 73	98.90 105	99.67 4	99.27 218	99.49 5	98.00 214	99.42 196	99.05 117	99.48 96	99.27 131	98.29 99	99.89 97	97.61 212	99.71 217	99.62 92

our_new_method		99.09 73	98.90 105	99.67 4	99.27 218	99.49 5	98.00 214	99.42 196	99.05 117	99.48 96	99.27 131	98.29 99	99.89 97	97.61 212	99.71 217	99.62 92

mmdepth		0.00 515	0.00 518	0.00 530	0.00 553	0.00 555	0.00 541	0.00 554	0.00 548	0.00 549	0.00 548	0.00 552	0.00 549	0.00 547	0.00 547	0.00 545

monomultidepth		0.00 515	0.00 518	0.00 530	0.00 553	0.00 555	0.00 541	0.00 554	0.00 548	0.00 549	0.00 548	0.00 552	0.00 549	0.00 547	0.00 547	0.00 545

mvs5depth		99.30 33	99.59 12	98.44 277	99.65 71	95.35 369	99.82 3	99.94 3	99.83 7	99.42 112	99.94 2	98.13 125	99.96 13	99.63 36	99.96 28	100.00 1

MVStest1		95.86 417	95.60 410	96.63 436	95.87 530	91.70 478	97.93 228	98.94 338	98.03 227	99.56 74	99.66 32	71.83 520	98.26 508	99.35 58	99.24 368	99.91 13

ttmdpeth		97.91 274	98.02 256	97.58 379	98.69 369	94.10 421	98.13 186	98.90 348	97.95 233	97.32 415	99.58 47	95.95 294	98.75 500	96.41 334	99.22 372	99.87 22

WBMVS		95.18 441	94.78 443	96.37 445	97.68 472	89.74 510	95.80 439	98.73 383	97.54 275	98.30 332	98.44 356	70.06 522	99.82 207	96.62 312	99.87 100	99.54 143

dongtai		76.24 508	75.95 511	77.12 526	92.39 540	67.91 550	90.16 532	59.44 551	82.04 536	89.42 536	94.67 513	49.68 548	81.74 544	48.06 543	77.66 541	81.72 540

kuosan		69.30 509	68.95 512	70.34 527	87.68 547	65.00 551	91.11 529	59.90 550	69.02 540	74.46 545	88.89 539	48.58 549	68.03 546	28.61 544	72.33 544	77.99 541

MVSMamba_PlusPlus		98.83 122	98.98 97	98.36 289	99.32 204	96.58 306	98.90 84	99.41 200	99.75 10	98.72 272	99.50 68	96.17 276	99.94 41	99.27 64	99.78 164	98.57 422

MGCFI-Net		98.34 217	98.28 218	98.51 266	98.47 402	97.59 222	98.96 78	99.48 157	99.18 92	97.40 410	95.50 495	98.66 59	99.50 427	98.18 152	98.71 428	98.44 432

testing91		93.32 474	92.27 480	96.47 441	97.54 478	91.25 490	96.17 416	96.76 472	97.18 320	93.65 520	93.50 520	65.11 537	99.63 371	93.04 454	97.45 486	98.53 423

testing11		93.08 479	92.02 485	96.26 450	97.56 476	90.83 499	96.32 403	95.70 495	96.47 365	92.66 525	93.73 517	64.36 538	99.59 392	93.77 433	97.57 480	98.37 441

testing99		93.04 480	91.98 488	96.23 453	97.53 480	90.70 502	96.35 401	95.94 490	96.87 341	93.41 521	93.43 522	63.84 539	99.59 392	93.24 450	97.19 496	98.40 437

UBG		93.25 476	92.32 478	96.04 464	97.72 464	90.16 505	95.92 433	95.91 491	96.03 387	93.95 517	93.04 525	69.60 524	99.52 420	90.72 504	97.98 473	98.45 429

UWE-MVS		92.38 489	91.76 492	94.21 503	97.16 495	84.65 531	95.42 454	88.45 539	95.96 391	96.17 470	95.84 489	66.36 531	99.71 308	91.87 481	98.64 435	98.28 444

ETVMVS		92.60 486	91.08 495	97.18 407	97.70 469	93.65 447	96.54 385	95.70 495	96.51 360	94.68 504	92.39 529	61.80 543	99.50 427	86.97 518	97.41 489	98.40 437

sasdasda		98.34 217	98.26 224	98.58 246	98.46 404	97.82 199	98.96 78	99.46 172	99.19 89	97.46 404	95.46 498	98.59 67	99.46 442	98.08 160	98.71 428	98.46 426

testing222		91.96 495	90.37 498	96.72 434	97.47 487	92.59 464	96.11 419	94.76 504	96.83 345	92.90 523	92.87 526	57.92 545	99.55 408	86.93 519	97.52 482	98.00 460

WB-MVSnew		95.73 422	95.57 413	96.23 453	96.70 512	90.70 502	96.07 422	93.86 518	95.60 409	97.04 428	95.45 502	96.00 286	99.55 408	91.04 496	98.31 452	98.43 434

fmvsm_l_conf0.5_n_a		99.19 51	99.27 47	98.94 165	99.65 71	97.05 275	97.80 248	99.76 39	98.70 159	99.78 39	99.11 187	98.79 43	99.95 25	99.85 6	99.96 28	99.83 33

fmvsm_l_conf0.5_n		99.21 47	99.28 46	99.02 149	99.64 77	97.28 252	97.82 244	99.76 39	98.73 151	99.82 34	99.09 196	98.81 39	99.95 25	99.86 4	99.96 28	99.83 33

fmvsm_s_conf0.1_n_a		99.17 52	99.30 44	98.80 195	99.75 34	96.59 303	97.97 226	99.86 17	98.22 203	99.88 21	99.71 22	98.59 67	99.84 177	99.73 28	99.98 12	99.98 3

fmvsm_s_conf0.1_n		99.16 56	99.33 37	98.64 232	99.71 49	96.10 326	97.87 239	99.85 19	98.56 177	99.90 14	99.68 25	98.69 57	99.85 158	99.72 30	99.98 12	99.97 4

fmvsm_s_conf0.5_n_a		99.10 72	99.20 58	98.78 202	99.55 117	96.59 303	97.79 249	99.82 31	98.21 205	99.81 36	99.53 64	98.46 82	99.84 177	99.70 33	99.97 21	99.90 15

fmvsm_s_conf0.5_n		99.09 73	99.26 50	98.61 242	99.55 117	96.09 329	97.74 261	99.81 32	98.55 178	99.85 27	99.55 56	98.60 66	99.84 177	99.69 35	99.98 12	99.89 16

MM		98.22 239	97.99 259	98.91 173	98.66 379	96.97 280	97.89 235	94.44 508	99.54 40	98.95 222	99.14 179	93.50 375	99.92 65	99.80 17	99.96 28	99.85 30

WAC-MVS						90.90 497								91.37 491

Syy-MVS		96.04 406	95.56 414	97.49 391	97.10 497	94.48 407	96.18 414	96.58 476	95.65 407	94.77 502	92.29 531	91.27 419	99.36 458	98.17 154	98.05 469	98.63 416

test_fmvsmconf0.1_n		99.49 15	99.54 14	99.34 83	99.78 24	98.11 151	97.77 253	99.90 12	99.33 66	99.97 3	99.66 32	99.71 3	99.96 13	99.79 19	99.99 5	99.96 8

test_fmvsmconf0.01_n		99.57 10	99.63 10	99.36 74	99.87 12	98.13 149	98.08 196	99.95 2	99.45 50	99.98 2	99.75 16	99.80 1	99.97 6	99.82 12	99.99 5	99.99 2

myMVS_eth3d		91.92 496	90.45 497	96.30 447	97.10 497	90.90 497	96.18 414	96.58 476	95.65 407	94.77 502	92.29 531	53.88 546	99.36 458	89.59 511	98.05 469	98.63 416

testing3		93.51 470	92.09 483	97.75 356	98.60 386	94.40 409	97.32 323	95.26 501	97.56 271	96.79 446	95.50 495	53.57 547	99.77 264	95.26 389	98.97 410	99.08 339

SSC-MVS		98.71 142	98.74 128	98.62 238	99.72 45	96.08 331	98.74 99	98.64 391	99.74 12	99.67 59	99.24 144	94.57 342	99.95 25	99.11 77	99.24 368	99.82 36

test_fmvsmconf_n		99.44 19	99.48 18	99.31 94	99.64 77	98.10 154	97.68 268	99.84 23	99.29 72	99.92 8	99.57 49	99.60 5	99.96 13	99.74 27	99.98 12	99.89 16

WB-MVS		98.52 192	98.55 165	98.43 278	99.65 71	95.59 350	98.52 130	98.77 374	99.65 25	99.52 87	99.00 228	94.34 352	99.93 53	98.65 114	98.83 418	99.76 58

test_fmvsmvis_n_1920		99.26 39	99.49 16	98.54 261	99.66 70	96.97 280	98.00 214	99.85 19	99.24 77	99.92 8	99.50 68	99.39 12	99.95 25	99.89 3	99.98 12	98.71 405

dmvs_re		95.98 411	95.39 422	97.74 358	98.86 331	97.45 234	98.37 159	95.69 497	97.95 233	96.56 457	95.95 484	90.70 425	97.68 518	88.32 514	96.13 513	98.11 452

SDMVSNet		99.23 45	99.32 39	98.96 162	99.68 64	97.35 240	98.84 95	99.48 157	99.69 17	99.63 66	99.68 25	99.03 24	99.96 13	97.97 175	99.92 71	99.57 124

dmvs_testset		92.94 482	92.21 482	95.13 492	98.59 389	90.99 496	97.65 274	92.09 527	96.95 333	94.00 515	93.55 519	92.34 400	96.97 528	72.20 539	92.52 533	97.43 488

sd_testset		99.28 36	99.31 41	99.19 112	99.68 64	98.06 165	99.41 17	99.30 250	99.69 17	99.63 66	99.68 25	99.25 16	99.96 13	97.25 245	99.92 71	99.57 124

test_fmvsm_n_1920		99.33 30	99.45 23	98.99 154	99.57 103	97.73 210	97.93 228	99.83 26	99.22 80	99.93 6	99.30 125	99.42 11	99.96 13	99.85 6	99.99 5	99.29 282

test_cas_vis1_n_1920		98.33 221	98.68 141	97.27 403	99.69 61	92.29 472	98.03 207	99.85 19	97.62 262	99.96 4	99.62 40	93.98 364	99.74 289	99.52 49	99.86 107	99.79 47

test_vis1_n_1920		98.40 206	98.92 102	96.81 430	99.74 37	90.76 501	98.15 184	99.91 10	98.33 190	99.89 18	99.55 56	95.07 325	99.88 115	99.76 23	99.93 57	99.79 47

test_vis1_n		98.31 226	98.50 174	97.73 361	99.76 30	94.17 417	98.68 109	99.91 10	96.31 372	99.79 38	99.57 49	92.85 391	99.42 451	99.79 19	99.84 114	99.60 102

test_fmvs1_n		98.09 257	98.28 218	97.52 388	99.68 64	93.47 450	98.63 116	99.93 6	95.41 422	99.68 57	99.64 37	91.88 409	99.48 435	99.82 12	99.87 100	99.62 92

mvsany_test1		97.60 305	97.54 303	97.77 352	97.72 464	95.35 369	95.36 456	97.13 458	94.13 459	99.71 49	99.33 118	97.93 141	99.30 469	97.60 214	98.94 413	98.67 414

APD_test1		98.83 122	98.66 146	99.34 83	99.78 24	99.47 8	98.42 151	99.45 176	98.28 199	98.98 212	99.19 159	97.76 158	99.58 399	96.57 317	99.55 295	98.97 361

test_vis1_rt		97.75 294	97.72 288	97.83 347	98.81 343	96.35 319	97.30 326	99.69 56	94.61 444	97.87 371	98.05 401	96.26 273	98.32 507	98.74 107	98.18 458	98.82 385

test_vis3_rt		99.14 62	99.17 60	99.07 136	99.78 24	98.38 122	98.92 83	99.94 3	97.80 247	99.91 12	99.67 30	97.15 212	98.91 495	99.76 23	99.56 290	99.92 12

test_fmvs2		98.70 147	98.97 98	97.89 342	99.54 123	94.05 422	98.55 126	99.92 8	96.78 348	99.72 47	99.78 13	96.60 254	99.67 343	99.91 2	99.90 88	99.94 10

test_fmvs1		97.72 296	97.94 267	97.07 415	98.66 379	92.39 469	97.68 268	99.81 32	95.20 429	99.54 79	99.44 85	91.56 413	99.41 452	99.78 21	99.77 172	99.40 229

test_fmvs3		99.12 69	99.41 26	98.25 301	99.76 30	95.07 385	99.05 68	99.94 3	97.78 250	99.82 34	99.84 3	98.56 73	99.71 308	99.96 1	99.96 28	99.97 4

mvsany_test3		98.87 112	98.92 102	98.74 215	99.38 185	96.94 284	98.58 123	99.10 310	96.49 363	99.96 4	99.81 8	98.18 118	99.45 445	98.97 89	99.79 159	99.83 33

testf1		99.25 40	99.16 62	99.51 49	99.89 6	99.63 3	98.71 106	99.69 56	98.90 136	99.43 108	99.35 111	98.86 35	99.67 343	97.81 189	99.81 140	99.24 299

APD_test2		99.25 40	99.16 62	99.51 49	99.89 6	99.63 3	98.71 106	99.69 56	98.90 136	99.43 108	99.35 111	98.86 35	99.67 343	97.81 189	99.81 140	99.24 299

test_f		98.67 160	98.87 111	98.05 329	99.72 45	95.59 350	98.51 135	99.81 32	96.30 374	99.78 39	99.82 5	96.14 277	98.63 503	99.82 12	99.93 57	99.95 9

FE-MVS		95.66 424	94.95 440	97.77 352	98.53 398	95.28 374	99.40 19	96.09 487	93.11 478	97.96 365	99.26 137	79.10 506	99.77 264	92.40 474	98.71 428	98.27 445

FA-MVS(test-final)		96.99 361	96.82 354	97.50 390	98.70 364	94.78 397	99.34 23	96.99 461	95.07 431	98.48 315	99.33 118	88.41 447	99.65 363	96.13 355	98.92 415	98.07 455

BridgeMVS		98.63 166	98.72 132	98.38 285	98.66 379	96.68 302	98.90 84	99.42 196	98.99 124	98.97 216	99.19 159	95.81 299	99.85 158	98.77 105	99.77 172	98.60 418

MonoMVSNet		96.25 399	96.53 379	95.39 487	96.57 514	91.01 495	98.82 97	97.68 437	98.57 174	98.03 359	99.37 104	90.92 422	97.78 517	94.99 394	93.88 531	97.38 489

patch_mono-2		98.51 193	98.63 152	98.17 311	99.38 185	94.78 397	97.36 320	99.69 56	98.16 216	98.49 313	99.29 128	97.06 217	99.97 6	98.29 144	99.91 80	99.76 58

EGC-MVSNET		85.24 505	80.54 508	99.34 83	99.77 27	99.20 38	99.08 62	99.29 258	12.08 545	20.84 546	99.42 89	97.55 178	99.85 158	97.08 261	99.72 208	98.96 364

test2506		92.39 488	91.89 490	93.89 508	99.38 185	82.28 542	99.32 26	66.03 549	99.08 114	98.77 265	99.57 49	66.26 532	99.84 177	98.71 110	99.95 39	99.54 143

test1111		96.49 383	96.82 354	95.52 483	99.42 176	87.08 523	99.22 46	87.14 541	99.11 100	99.46 101	99.58 47	88.69 441	99.86 144	98.80 100	99.95 39	99.62 92

ECVR-MVS		96.42 389	96.61 373	95.85 472	99.38 185	88.18 518	99.22 46	86.00 543	99.08 114	99.36 128	99.57 49	88.47 446	99.82 207	98.52 127	99.95 39	99.54 143

test_blank		0.00 515	0.00 518	0.00 530	0.00 553	0.00 555	0.00 541	0.00 554	0.00 548	0.00 549	0.00 548	0.00 552	0.00 549	0.00 547	0.00 547	0.00 545

tt0805		98.69 151	98.62 154	98.90 176	99.75 34	99.30 21	99.15 57	96.97 463	98.86 142	98.87 247	97.62 433	98.63 63	98.96 491	99.41 56	98.29 454	98.45 429

DVP-MVS++		98.90 108	98.70 138	99.51 49	98.43 409	99.15 52	99.43 15	99.32 237	98.17 213	99.26 156	99.02 212	98.18 118	99.88 115	97.07 262	99.45 323	99.49 176

FOURS1					99.73 38	99.67 2	99.43 15	99.54 130	99.43 54	99.26 156

MSC_two_6792asdad				99.32 91	98.43 409	98.37 124		98.86 359					99.89 97	97.14 255	99.60 273	99.71 65

PC_three_1452									93.27 474	99.40 117	98.54 340	98.22 113	97.00 527	95.17 391	99.45 323	99.49 176

No_MVS				99.32 91	98.43 409	98.37 124		98.86 359					99.89 97	97.14 255	99.60 273	99.71 65

test_one_0601					99.39 183	99.20 38		99.31 242	98.49 180	98.66 282	99.02 212	97.64 168

eth-test2					0.00 553

eth-test					0.00 553

GeoE		99.05 83	98.99 96	99.25 104	99.44 169	98.35 128	98.73 103	99.56 119	98.42 184	98.91 234	98.81 283	98.94 31	99.91 74	98.35 140	99.73 199	99.49 176

test_method		79.78 506	79.50 509	80.62 524	80.21 549	45.76 552	70.82 540	98.41 411	31.08 544	80.89 544	97.71 426	84.85 475	97.37 523	91.51 489	80.03 540	98.75 401

Anonymous20240521		98.69 151	98.87 111	98.16 314	99.77 27	95.11 384	99.08 62	99.44 184	99.34 65	99.33 137	99.55 56	94.10 363	99.94 41	99.25 67	99.96 28	99.42 217

h-mvs33		97.77 293	97.33 318	99.10 128	99.21 238	97.84 193	98.35 161	98.57 397	99.11 100	98.58 300	99.02 212	88.65 444	99.96 13	98.11 157	96.34 509	99.49 176

hse-mvs2		97.46 316	97.07 335	98.64 232	98.73 354	97.33 242	97.45 308	97.64 440	99.11 100	98.58 300	97.98 407	88.65 444	99.79 246	98.11 157	97.39 490	98.81 390

CL-MVSNet_self_test		97.44 319	97.22 325	98.08 324	98.57 393	95.78 347	94.30 493	98.79 371	96.58 359	98.60 296	98.19 388	94.74 338	99.64 368	96.41 334	98.84 417	98.82 385

KD-MVS_2432*1600		92.87 484	91.99 486	95.51 484	91.37 542	89.27 512	94.07 500	98.14 423	95.42 419	97.25 417	96.44 475	67.86 526	99.24 475	91.28 492	96.08 518	98.02 457

KD-MVS_self_test		99.25 40	99.18 59	99.44 65	99.63 83	99.06 70	98.69 108	99.54 130	99.31 69	99.62 69	99.53 64	97.36 198	99.86 144	99.24 69	99.71 217	99.39 230

AUN-MVS		96.24 401	95.45 418	98.60 244	98.70 364	97.22 259	97.38 315	97.65 438	95.95 392	95.53 490	97.96 411	82.11 496	99.79 246	96.31 340	97.44 487	98.80 395

ZD-MVS					99.01 302	98.84 85		99.07 315	94.10 461	98.05 357	98.12 394	96.36 268	99.86 144	92.70 467	99.19 380

SR-MVS-dyc-post		98.81 127	98.55 165	99.57 21	99.20 242	99.38 12	98.48 143	99.30 250	98.64 161	98.95 222	98.96 241	97.49 189	99.86 144	96.56 321	99.39 338	99.45 204

RE-MVS-def			98.58 162		99.20 242	99.38 12	98.48 143	99.30 250	98.64 161	98.95 222	98.96 241	97.75 159		96.56 321	99.39 338	99.45 204

SED-MVS		98.91 106	98.72 132	99.49 55	99.49 148	99.17 43	98.10 193	99.31 242	98.03 227	99.66 60	99.02 212	98.36 90	99.88 115	96.91 276	99.62 266	99.41 220

IU-MVS					99.49 148	99.15 52		98.87 354	92.97 481	99.41 114				96.76 293	99.62 266	99.66 80

OPU-MVS				98.82 190	98.59 389	98.30 132	98.10 193				98.52 344	98.18 118	98.75 500	94.62 404	99.48 319	99.41 220

test_241102_TWO								99.30 250	98.03 227	99.26 156	99.02 212	97.51 185	99.88 115	96.91 276	99.60 273	99.66 80

test_241102_ONE					99.49 148	99.17 43		99.31 242	97.98 230	99.66 60	98.90 256	98.36 90	99.48 435

SF-MVS		98.53 188	98.27 221	99.32 91	99.31 206	98.75 90	98.19 178	99.41 200	96.77 349	98.83 253	98.90 256	97.80 155	99.82 207	95.68 376	99.52 304	99.38 239

cl22		95.79 420	95.39 422	96.98 419	96.77 510	92.79 461	94.40 490	98.53 401	94.59 445	97.89 369	98.17 389	82.82 493	99.24 475	96.37 336	99.03 398	98.92 371

miper_ehance_all_eth		97.06 354	97.03 337	97.16 411	97.83 459	93.06 454	94.66 480	99.09 312	95.99 390	98.69 276	98.45 355	92.73 394	99.61 383	96.79 289	99.03 398	98.82 385

miper_enhance_ethall		96.01 408	95.74 403	96.81 430	96.41 522	92.27 473	93.69 510	98.89 351	91.14 505	98.30 332	97.35 453	90.58 426	99.58 399	96.31 340	99.03 398	98.60 418

ZNCC-MVS		98.68 157	98.40 192	99.54 31	99.57 103	99.21 32	98.46 145	99.29 258	97.28 306	98.11 350	98.39 361	98.00 134	99.87 135	96.86 286	99.64 256	99.55 137

dcpmvs_2		98.78 133	99.11 74	97.78 351	99.56 111	93.67 445	99.06 66	99.86 17	99.50 43	99.66 60	99.26 137	97.21 209	99.99 2	98.00 170	99.91 80	99.68 73

cl____		97.02 357	96.83 353	97.58 379	97.82 460	94.04 424	94.66 480	99.16 299	97.04 328	98.63 287	98.71 302	88.68 443	99.69 326	97.00 267	99.81 140	99.00 355

DIV-MVS_self_test		97.02 357	96.84 352	97.58 379	97.82 460	94.03 425	94.66 480	99.16 299	97.04 328	98.63 287	98.71 302	88.69 441	99.69 326	97.00 267	99.81 140	99.01 352

eth_miper_zixun_eth		97.23 340	97.25 322	97.17 409	98.00 449	92.77 462	94.71 475	99.18 292	97.27 308	98.56 304	98.74 297	91.89 408	99.69 326	97.06 264	99.81 140	99.05 343

9.14			97.78 281		99.07 279		97.53 295	99.32 237	95.53 414	98.54 308	98.70 309	97.58 175	99.76 270	94.32 417	99.46 321

uanet_test		0.00 515	0.00 518	0.00 530	0.00 553	0.00 555	0.00 541	0.00 554	0.00 548	0.00 549	0.00 548	0.00 552	0.00 549	0.00 547	0.00 547	0.00 545

DCPMVS		0.00 515	0.00 518	0.00 530	0.00 553	0.00 555	0.00 541	0.00 554	0.00 548	0.00 549	0.00 548	0.00 552	0.00 549	0.00 547	0.00 547	0.00 545

save fliter					99.11 270	97.97 175	96.53 387	99.02 328	98.24 200

ET-MVSNet_ETH3D		94.30 456	93.21 468	97.58 379	98.14 439	94.47 408	94.78 474	93.24 523	94.72 441	89.56 535	95.87 487	78.57 510	99.81 224	96.91 276	97.11 499	98.46 426

UniMVSNet_ETH3D		99.69 2	99.69 4	99.69 3	99.84 17	99.34 19	99.69 5	99.58 101	99.90 3	99.86 24	99.78 13	99.58 6	99.95 25	99.00 87	99.95 39	99.78 50

EIA-MVS		98.00 266	97.74 284	98.80 195	98.72 356	98.09 155	98.05 203	99.60 92	97.39 294	96.63 453	95.55 493	97.68 162	99.80 233	96.73 298	99.27 362	98.52 424

miper_refine_blended		92.87 484	91.99 486	95.51 484	91.37 542	89.27 512	94.07 500	98.14 423	95.42 419	97.25 417	96.44 475	67.86 526	99.24 475	91.28 492	96.08 518	98.02 457

miper_lstm_enhance		97.18 345	97.16 328	97.25 405	98.16 437	92.85 460	95.15 465	99.31 242	97.25 310	98.74 271	98.78 288	90.07 429	99.78 258	97.19 249	99.80 152	99.11 338

ETV-MVS		98.03 262	97.86 276	98.56 254	98.69 369	98.07 162	97.51 298	99.50 147	98.10 223	97.50 401	95.51 494	98.41 85	99.88 115	96.27 345	99.24 368	97.71 478

CS-MVS		99.13 66	99.10 80	99.24 106	99.06 284	99.15 52	99.36 22	99.88 15	99.36 63	98.21 340	98.46 354	98.68 58	99.93 53	99.03 85	99.85 109	98.64 415

D2MVS		97.84 289	97.84 278	97.83 347	99.14 264	94.74 399	96.94 354	98.88 352	95.84 397	98.89 238	98.96 241	94.40 349	99.69 326	97.55 218	99.95 39	99.05 343

DVP-MVS		98.77 136	98.52 170	99.52 44	99.50 140	99.21 32	98.02 210	98.84 363	97.97 231	99.08 189	99.02 212	97.61 172	99.88 115	96.99 269	99.63 262	99.48 187
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
test_0728_THIRD									98.17 213	99.08 189	99.02 212	97.89 147	99.88 115	97.07 262	99.71 217	99.70 70

test_0728_SECOND				99.60 16	99.50 140	99.23 30	98.02 210	99.32 237					99.88 115	96.99 269	99.63 262	99.68 73

test0726					99.50 140	99.21 32	98.17 182	99.35 223	97.97 231	99.26 156	99.06 199	97.61 172

SR-MVS		98.71 142	98.43 188	99.57 21	99.18 254	99.35 16	98.36 160	99.29 258	98.29 197	98.88 242	98.85 270	97.53 182	99.87 135	96.14 353	99.31 354	99.48 187

DPM-MVS		96.32 393	95.59 412	98.51 266	98.76 350	97.21 261	94.54 486	98.26 416	91.94 495	96.37 467	97.25 456	93.06 386	99.43 449	91.42 490	98.74 424	98.89 376

GST-MVS		98.61 170	98.30 215	99.52 44	99.51 134	99.20 38	98.26 171	99.25 273	97.44 289	98.67 280	98.39 361	97.68 162	99.85 158	96.00 358	99.51 307	99.52 160

test_yl		96.69 371	96.29 390	97.90 340	98.28 423	95.24 375	97.29 327	97.36 445	98.21 205	98.17 341	97.86 415	86.27 458	99.55 408	94.87 398	98.32 450	98.89 376

thisisatest0530		95.27 438	94.45 450	97.74 358	99.19 246	94.37 410	97.86 240	90.20 536	97.17 321	98.22 339	97.65 430	73.53 519	99.90 81	96.90 281	99.35 345	98.95 365

Anonymous20240529		98.93 104	98.87 111	99.12 124	99.19 246	98.22 142	99.01 71	98.99 334	99.25 76	99.54 79	99.37 104	97.04 218	99.80 233	97.89 179	99.52 304	99.35 256

Anonymous202405211		97.90 275	97.50 306	99.08 134	98.90 322	98.25 136	98.53 129	96.16 483	98.87 140	99.11 184	98.86 267	90.40 428	99.78 258	97.36 235	99.31 354	99.19 317

DCV-MVSNet		96.69 371	96.29 390	97.90 340	98.28 423	95.24 375	97.29 327	97.36 445	98.21 205	98.17 341	97.86 415	86.27 458	99.55 408	94.87 398	98.32 450	98.89 376

tttt0517		95.64 425	94.98 438	97.64 373	99.36 192	93.81 440	98.72 104	90.47 535	98.08 226	98.67 280	98.34 368	73.88 518	99.92 65	97.77 194	99.51 307	99.20 311

our_test_3		97.39 324	97.73 287	96.34 446	98.70 364	89.78 509	94.61 483	98.97 337	96.50 362	99.04 201	98.85 270	95.98 291	99.84 177	97.26 244	99.67 244	99.41 220

thisisatest0515		94.12 461	93.16 469	96.97 420	98.60 386	92.90 459	93.77 509	90.61 534	94.10 461	96.91 435	95.87 487	74.99 516	99.80 233	94.52 407	99.12 391	98.20 447

ppachtmachnet_test		97.50 311	97.74 284	96.78 432	98.70 364	91.23 492	94.55 485	99.05 320	96.36 369	99.21 172	98.79 286	96.39 264	99.78 258	96.74 296	99.82 133	99.34 260

SMA-MVS		98.40 206	98.03 255	99.51 49	99.16 258	99.21 32	98.05 203	99.22 281	94.16 458	98.98 212	99.10 190	97.52 184	99.79 246	96.45 331	99.64 256	99.53 157
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
GSMVS																98.81 390

DPE-MVS		98.59 174	98.26 224	99.57 21	99.27 218	99.15 52	97.01 348	99.39 207	97.67 258	99.44 107	98.99 230	97.53 182	99.89 97	95.40 386	99.68 238	99.66 80
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part2					99.36 192	99.10 65				99.05 199

thres100view900		94.19 458	93.67 462	95.75 475	99.06 284	91.35 486	98.03 207	94.24 514	98.33 190	97.40 410	94.98 507	79.84 500	99.62 375	83.05 529	98.08 466	96.29 509

tfpnnormal		98.90 108	98.90 105	98.91 173	99.67 68	97.82 199	99.00 73	99.44 184	99.45 50	99.51 92	99.24 144	98.20 117	99.86 144	95.92 362	99.69 232	99.04 347

tfpn200view9		94.03 462	93.44 464	95.78 474	98.93 314	91.44 484	97.60 285	94.29 511	97.94 235	97.10 422	94.31 515	79.67 502	99.62 375	83.05 529	98.08 466	96.29 509

c3_l		97.36 327	97.37 314	97.31 400	98.09 444	93.25 452	95.01 468	99.16 299	97.05 327	98.77 265	98.72 300	92.88 389	99.64 368	96.93 275	99.76 188	99.05 343

CHOSEN 280x420		95.51 430	95.47 416	95.65 480	98.25 426	88.27 517	93.25 519	98.88 352	93.53 471	94.65 505	97.15 459	86.17 460	99.93 53	97.41 233	99.93 57	98.73 404

CANet		97.87 282	97.76 282	98.19 310	97.75 463	95.51 355	96.76 367	99.05 320	97.74 252	96.93 432	98.21 386	95.59 307	99.89 97	97.86 186	99.93 57	99.19 317

Fast-Effi-MVS+-dtu		98.27 232	98.09 247	98.81 192	98.43 409	98.11 151	97.61 284	99.50 147	98.64 161	97.39 412	97.52 440	98.12 126	99.95 25	96.90 281	98.71 428	98.38 439

Effi-MVS+-dtu		98.26 234	97.90 273	99.35 80	98.02 448	99.49 5	98.02 210	99.16 299	98.29 197	97.64 387	97.99 406	96.44 261	99.95 25	96.66 309	98.93 414	98.60 418

CANet_DTU		97.26 336	97.06 336	97.84 346	97.57 475	94.65 404	96.19 412	98.79 371	97.23 316	95.14 496	98.24 383	93.22 380	99.84 177	97.34 236	99.84 114	99.04 347

MGCNet		97.44 319	97.01 339	98.72 219	96.42 521	96.74 298	97.20 338	91.97 531	98.46 182	98.30 332	98.79 286	92.74 393	99.91 74	99.30 62	99.94 51	99.52 160

MP-MVS-pluss		98.57 177	98.23 229	99.60 16	99.69 61	99.35 16	97.16 343	99.38 209	94.87 437	98.97 216	98.99 230	98.01 133	99.88 115	97.29 242	99.70 226	99.58 117
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MSP-MVS		98.40 206	98.00 258	99.61 13	99.57 103	99.25 28	98.57 124	99.35 223	97.55 273	99.31 146	97.71 426	94.61 341	99.88 115	96.14 353	99.19 380	99.70 70
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
sam_mvs1												84.74 477				98.81 390

sam_mvs												84.29 483

IterMVS-SCA-FT		97.85 288	98.18 237	96.87 426	99.27 218	91.16 493	95.53 448	99.25 273	99.10 107	99.41 114	99.35 111	93.10 384	99.96 13	98.65 114	99.94 51	99.49 176

TSAR-MVS + MP.		98.63 166	98.49 179	99.06 142	99.64 77	97.90 187	98.51 135	98.94 338	96.96 332	99.24 166	98.89 262	97.83 151	99.81 224	96.88 283	99.49 318	99.48 187
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
xiu_mvs_v1_base_debu		97.86 283	98.17 238	96.92 423	98.98 307	93.91 435	96.45 392	99.17 296	97.85 243	98.41 323	97.14 460	98.47 77	99.92 65	98.02 167	99.05 394	96.92 497

OPM-MVS		98.56 179	98.32 213	99.25 104	99.41 179	98.73 94	97.13 345	99.18 292	97.10 325	98.75 268	98.92 250	98.18 118	99.65 363	96.68 305	99.56 290	99.37 242
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMMP_NAP		98.75 138	98.48 180	99.57 21	99.58 94	99.29 23	97.82 244	99.25 273	96.94 334	98.78 262	99.12 185	98.02 132	99.84 177	97.13 258	99.67 244	99.59 109

ambc				98.24 303	98.82 340	95.97 336	98.62 118	99.00 333		99.27 152	99.21 154	96.99 224	99.50 427	96.55 324	99.50 315	99.26 294

MTGPA								99.20 284

SPE-MVS-test		99.13 66	99.09 82	99.26 101	99.13 267	98.97 73	99.31 30	99.88 15	99.44 52	98.16 344	98.51 345	98.64 61	99.93 53	98.91 93	99.85 109	98.88 379

Effi-MVS+		98.02 263	97.82 279	98.62 238	98.53 398	97.19 263	97.33 322	99.68 63	97.30 304	96.68 451	97.46 446	98.56 73	99.80 233	96.63 311	98.20 457	98.86 381

xiu_mvs_v2_base		97.16 347	97.49 307	96.17 457	98.54 396	92.46 467	95.45 452	98.84 363	97.25 310	97.48 403	96.49 472	98.31 97	99.90 81	96.34 339	98.68 433	96.15 513

xiu_mvs_v1_base		97.86 283	98.17 238	96.92 423	98.98 307	93.91 435	96.45 392	99.17 296	97.85 243	98.41 323	97.14 460	98.47 77	99.92 65	98.02 167	99.05 394	96.92 497

new-patchmatchnet		98.35 216	98.74 128	97.18 407	99.24 230	92.23 474	96.42 396	99.48 157	98.30 194	99.69 55	99.53 64	97.44 193	99.82 207	98.84 99	99.77 172	99.49 176

pmmvs6		99.67 3	99.70 3	99.60 16	99.90 4	99.27 26	99.53 9	99.76 39	99.64 26	99.84 30	99.83 4	99.50 9	99.87 135	99.36 57	99.92 71	99.64 86

pmmvs5		97.64 303	97.49 307	98.08 324	99.14 264	95.12 383	96.70 372	99.05 320	93.77 468	98.62 291	98.83 277	93.23 379	99.75 282	98.33 143	99.76 188	99.36 250

test_post1							97.59 287				20.48 547	83.07 491	99.66 356	94.16 418

test_post											21.25 546	83.86 486	99.70 316

Fast-Effi-MVS+		97.67 301	97.38 313	98.57 249	98.71 360	97.43 237	97.23 333	99.45 176	94.82 439	96.13 471	96.51 471	98.52 75	99.91 74	96.19 349	98.83 418	98.37 441

patchmatchnet-post											98.77 290	84.37 480	99.85 158

Anonymous20231211		99.27 37	99.27 47	99.26 101	99.29 212	98.18 144	99.49 12	99.51 142	99.70 15	99.80 37	99.68 25	96.84 232	99.83 195	99.21 70	99.91 80	99.77 53

pmmvs-eth3d		98.47 197	98.34 207	98.86 179	99.30 210	97.76 206	97.16 343	99.28 262	95.54 413	99.42 112	99.19 159	97.27 204	99.63 371	97.89 179	99.97 21	99.20 311

GG-mvs-BLEND				94.76 496	94.54 535	92.13 475	99.31 30	80.47 547		88.73 538	91.01 537	67.59 529	98.16 511	82.30 533	94.53 529	93.98 521

xiu_mvs_v1_base_debi		97.86 283	98.17 238	96.92 423	98.98 307	93.91 435	96.45 392	99.17 296	97.85 243	98.41 323	97.14 460	98.47 77	99.92 65	98.02 167	99.05 394	96.92 497

Anonymous20231206		98.21 242	98.21 230	98.20 308	99.51 134	95.43 365	98.13 186	99.32 237	96.16 381	98.93 231	98.82 280	96.00 286	99.83 195	97.32 240	99.73 199	99.36 250

MTAPA		98.88 111	98.64 150	99.61 13	99.67 68	99.36 15	98.43 148	99.20 284	98.83 149	98.89 238	98.90 256	96.98 225	99.92 65	97.16 252	99.70 226	99.56 130

MTMP							97.93 228	91.91 532

gm-plane-assit					94.83 534	81.97 543			88.07 527		94.99 506		99.60 387	91.76 483

test9_res														93.28 448	99.15 385	99.38 239

MVP-Stereo		98.08 258	97.92 270	98.57 249	98.96 310	96.79 294	97.90 234	99.18 292	96.41 368	98.46 317	98.95 245	95.93 295	99.60 387	96.51 327	98.98 409	99.31 276
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST9					98.71 360	98.08 159	95.96 428	99.03 325	91.40 501	95.85 479	97.53 437	96.52 257	99.76 270

train_agg		97.10 349	96.45 384	99.07 136	98.71 360	98.08 159	95.96 428	99.03 325	91.64 496	95.85 479	97.53 437	96.47 259	99.76 270	93.67 435	99.16 383	99.36 250

gg-mvs-nofinetune		92.37 490	91.20 494	95.85 472	95.80 531	92.38 470	99.31 30	81.84 546	99.75 10	91.83 530	99.74 18	68.29 525	99.02 488	87.15 517	97.12 498	96.16 512

SCA		96.41 390	96.66 368	95.67 478	98.24 428	88.35 516	95.85 437	96.88 469	96.11 382	97.67 386	98.67 315	93.10 384	99.85 158	94.16 418	99.22 372	98.81 390

Patchmatch-test		96.55 379	96.34 387	97.17 409	98.35 416	93.06 454	98.40 156	97.79 431	97.33 299	98.41 323	98.67 315	83.68 487	99.69 326	95.16 392	99.31 354	98.77 398

test_8					98.67 374	98.01 168	95.91 434	99.02 328	91.64 496	95.79 482	97.50 441	96.47 259	99.76 270

MS-PatchMatch		97.68 300	97.75 283	97.45 395	98.23 431	93.78 441	97.29 327	98.84 363	96.10 383	98.64 286	98.65 321	96.04 283	99.36 458	96.84 287	99.14 386	99.20 311

Patchmatch-RL test		97.26 336	97.02 338	97.99 335	99.52 131	95.53 354	96.13 417	99.71 48	97.47 281	99.27 152	99.16 169	84.30 482	99.62 375	97.89 179	99.77 172	98.81 390

cdsmvs_eth3d_5k		24.66 510	32.88 513	0.00 530	0.00 553	0.00 555	0.00 541	99.10 310	0.00 548	0.00 549	97.58 434	99.21 18	0.00 549	0.00 547	0.00 547	0.00 545

pcd_1.5k_mvsjas		8.17 513	10.90 516	0.00 530	0.00 553	0.00 555	0.00 541	0.00 554	0.00 548	0.00 549	0.00 548	98.07 128	0.00 549	0.00 547	0.00 547	0.00 545

agg_prior2														92.50 472	99.16 383	99.37 242

agg_prior					98.68 373	97.99 171		99.01 331		95.59 483			99.77 264

tmp_tt		78.77 507	78.73 510	78.90 525	58.45 550	74.76 549	94.20 496	78.26 548	39.16 543	86.71 539	92.82 527	80.50 498	75.19 545	86.16 523	92.29 534	86.74 539

canonicalmvs		98.34 217	98.26 224	98.58 246	98.46 404	97.82 199	98.96 78	99.46 172	99.19 89	97.46 404	95.46 498	98.59 67	99.46 442	98.08 160	98.71 428	98.46 426

anonymousdsp		99.51 14	99.47 21	99.62 9	99.88 9	99.08 69	99.34 23	99.69 56	98.93 132	99.65 63	99.72 21	98.93 33	99.95 25	99.11 77	100.00 1	99.82 36

alignmvs		97.35 328	96.88 349	98.78 202	98.54 396	98.09 155	97.71 264	97.69 435	99.20 84	97.59 392	95.90 486	88.12 450	99.55 408	98.18 152	98.96 411	98.70 408

nrg030		99.40 25	99.35 33	99.54 31	99.58 94	99.13 60	98.98 76	99.48 157	99.68 19	99.46 101	99.26 137	98.62 64	99.73 296	99.17 74	99.92 71	99.76 58

v144192		98.54 186	98.57 163	98.45 275	99.21 238	95.98 334	97.63 278	99.36 217	97.15 324	99.32 143	99.18 163	95.84 298	99.84 177	99.50 50	99.91 80	99.54 143

FIs		99.14 62	99.09 82	99.29 95	99.70 57	98.28 133	99.13 59	99.52 140	99.48 44	99.24 166	99.41 94	96.79 239	99.82 207	98.69 112	99.88 95	99.76 58

v1921920		98.54 186	98.60 159	98.38 285	99.20 242	95.76 348	97.56 290	99.36 217	97.23 316	99.38 121	99.17 167	96.02 284	99.84 177	99.57 39	99.90 88	99.54 143

UA-Net		99.47 16	99.40 27	99.70 2	99.49 148	99.29 23	99.80 4	99.72 46	99.82 8	99.04 201	99.81 8	98.05 131	99.96 13	98.85 98	99.99 5	99.86 28

v1192		98.60 172	98.66 146	98.41 281	99.27 218	95.88 340	97.52 296	99.36 217	97.41 291	99.33 137	99.20 156	96.37 267	99.82 207	99.57 39	99.92 71	99.55 137

FC-MVSNet-test		99.27 37	99.25 52	99.34 83	99.77 27	98.37 124	99.30 35	99.57 109	99.61 34	99.40 117	99.50 68	97.12 214	99.85 158	99.02 86	99.94 51	99.80 45

v1144		98.60 172	98.66 146	98.41 281	99.36 192	95.90 338	97.58 288	99.34 229	97.51 277	99.27 152	99.15 175	96.34 269	99.80 233	99.47 53	99.93 57	99.51 164

sosnet-low-res		0.00 515	0.00 518	0.00 530	0.00 553	0.00 555	0.00 541	0.00 554	0.00 548	0.00 549	0.00 548	0.00 552	0.00 549	0.00 547	0.00 547	0.00 545

HFP-MVS		98.71 142	98.44 187	99.51 49	99.49 148	99.16 48	98.52 130	99.31 242	97.47 281	98.58 300	98.50 349	97.97 138	99.85 158	96.57 317	99.59 277	99.53 157

v148		98.45 200	98.60 159	98.00 333	99.44 169	94.98 387	97.44 310	99.06 316	98.30 194	99.32 143	98.97 237	96.65 251	99.62 375	98.37 139	99.85 109	99.39 230

sosnet		0.00 515	0.00 518	0.00 530	0.00 553	0.00 555	0.00 541	0.00 554	0.00 548	0.00 549	0.00 548	0.00 552	0.00 549	0.00 547	0.00 547	0.00 545

uncertanet		0.00 515	0.00 518	0.00 530	0.00 553	0.00 555	0.00 541	0.00 554	0.00 548	0.00 549	0.00 548	0.00 552	0.00 549	0.00 547	0.00 547	0.00 545

AllTest		98.44 201	98.20 231	99.16 118	99.50 140	98.55 108	98.25 172	99.58 101	96.80 346	98.88 242	99.06 199	97.65 165	99.57 401	94.45 410	99.61 271	99.37 242

TestCases				99.16 118	99.50 140	98.55 108		99.58 101	96.80 346	98.88 242	99.06 199	97.65 165	99.57 401	94.45 410	99.61 271	99.37 242

v7n		99.53 12	99.57 13	99.41 69	99.88 9	98.54 111	99.45 14	99.61 90	99.66 23	99.68 57	99.66 32	98.44 84	99.95 25	99.73 28	99.96 28	99.75 62

region2R		98.69 151	98.40 192	99.54 31	99.53 127	99.17 43	98.52 130	99.31 242	97.46 286	98.44 320	98.51 345	97.83 151	99.88 115	96.46 330	99.58 282	99.58 117

RRT-MVS		97.88 280	97.98 260	97.61 376	98.15 438	93.77 442	98.97 77	99.64 78	99.16 94	98.69 276	99.42 89	91.60 410	99.89 97	97.63 210	98.52 445	99.16 331

balanced_ft_v1		98.28 231	98.35 206	98.10 319	98.08 445	96.23 323	99.23 45	99.26 271	98.34 188	97.46 404	99.42 89	95.38 316	99.88 115	98.60 117	99.34 347	98.17 449

PS-MVSNAJss		99.46 17	99.49 16	99.35 80	99.90 4	98.15 146	99.20 49	99.65 76	99.48 44	99.92 8	99.71 22	98.07 128	99.96 13	99.53 48	100.00 1	99.93 11

PS-MVSNAJ		97.08 352	97.39 312	96.16 459	98.56 394	92.46 467	95.24 461	98.85 362	97.25 310	97.49 402	95.99 483	98.07 128	99.90 81	96.37 336	98.67 434	96.12 514

jajsoiax		99.58 9	99.61 11	99.48 57	99.87 12	98.61 103	99.28 40	99.66 70	99.09 110	99.89 18	99.68 25	99.53 7	99.97 6	99.50 50	99.99 5	99.87 22

mvs_tets		99.63 6	99.67 6	99.49 55	99.88 9	98.61 103	99.34 23	99.71 48	99.27 74	99.90 14	99.74 18	99.68 4	99.97 6	99.55 43	99.99 5	99.88 20

EI-MVSNet-UG-set		98.69 151	98.71 135	98.62 238	99.10 272	96.37 318	97.23 333	98.87 354	99.20 84	99.19 174	98.99 230	97.30 201	99.85 158	98.77 105	99.79 159	99.65 85

EI-MVSNet-Vis-set		98.68 157	98.70 138	98.63 236	99.09 275	96.40 317	97.23 333	98.86 359	99.20 84	99.18 179	98.97 237	97.29 203	99.85 158	98.72 109	99.78 164	99.64 86

HPM-MVS++		98.10 254	97.64 297	99.48 57	99.09 275	99.13 60	97.52 296	98.75 380	97.46 286	96.90 438	97.83 419	96.01 285	99.84 177	95.82 370	99.35 345	99.46 198

test_prior4						97.97 175	95.86 435

XVS		98.72 141	98.45 185	99.53 38	99.46 162	99.21 32	98.65 114	99.34 229	98.62 166	97.54 397	98.63 327	97.50 186	99.83 195	96.79 289	99.53 301	99.56 130

v1240		98.55 183	98.62 154	98.32 292	99.22 236	95.58 352	97.51 298	99.45 176	97.16 322	99.45 106	99.24 144	96.12 281	99.85 158	99.60 37	99.88 95	99.55 137

pm-mvs1		99.44 19	99.48 18	99.33 89	99.80 21	98.63 100	99.29 36	99.63 81	99.30 71	99.65 63	99.60 45	99.16 22	99.82 207	99.07 80	99.83 126	99.56 130

test_prior2							95.74 442		96.48 364	96.11 472	97.63 432	95.92 296		94.16 418	99.20 377

X-MVStestdata		94.32 454	92.59 476	99.53 38	99.46 162	99.21 32	98.65 114	99.34 229	98.62 166	97.54 397	45.85 543	97.50 186	99.83 195	96.79 289	99.53 301	99.56 130

test_prior				98.95 164	98.69 369	97.95 179		99.03 325					99.59 392			99.30 280

旧先验2							95.76 441		88.56 524	97.52 399			99.66 356	94.48 408

新几何2							95.93 431

新几何1				98.91 173	98.94 312	97.76 206		98.76 376	87.58 528	96.75 447	98.10 396	94.80 335	99.78 258	92.73 466	99.00 404	99.20 311

旧先验1					98.82 340	97.45 234		98.76 376			98.34 368	95.50 311			99.01 403	99.23 301

无先验							95.74 442	98.74 382	89.38 517				99.73 296	92.38 475		99.22 306

原ACMM2							95.53 448

原ACMM1				98.35 290	98.90 322	96.25 322		98.83 367	92.48 489	96.07 474	98.10 396	95.39 315	99.71 308	92.61 469	98.99 406	99.08 339

test222					98.92 318	96.93 285	95.54 447	98.78 373	85.72 531	96.86 442	98.11 395	94.43 346			99.10 393	99.23 301

testdata2													99.79 246	92.80 463

segment_acmp												97.02 221

testdata				98.09 321	98.93 314	95.40 366		98.80 370	90.08 513	97.45 407	98.37 364	95.26 318	99.70 316	93.58 439	98.95 412	99.17 325

testdata1							95.44 453		96.32 371

v8		99.01 90	99.16 62	98.57 249	99.47 159	96.31 321	98.90 84	99.47 167	99.03 121	99.52 87	99.57 49	96.93 228	99.81 224	99.60 37	99.98 12	99.60 102

1314		95.74 421	95.60 410	96.17 457	97.53 480	92.75 463	98.07 200	98.31 414	91.22 503	94.25 509	96.68 468	95.53 308	99.03 486	91.64 486	97.18 497	96.74 503

LFMVS		97.20 343	96.72 361	98.64 232	98.72 356	96.95 283	98.93 82	94.14 516	99.74 12	98.78 262	99.01 224	84.45 479	99.73 296	97.44 231	99.27 362	99.25 295

VDD-MVS		98.56 179	98.39 195	99.07 136	99.13 267	98.07 162	98.59 122	97.01 460	99.59 36	99.11 184	99.27 131	94.82 332	99.79 246	98.34 141	99.63 262	99.34 260

VDDNet		98.21 242	97.95 264	99.01 151	99.58 94	97.74 208	99.01 71	97.29 451	99.67 20	98.97 216	99.50 68	90.45 427	99.80 233	97.88 182	99.20 377	99.48 187

v10		98.97 99	99.11 74	98.55 256	99.44 169	96.21 325	98.90 84	99.55 124	98.73 151	99.48 96	99.60 45	96.63 253	99.83 195	99.70 33	99.99 5	99.61 100

VPNet		98.87 112	98.83 120	99.01 151	99.70 57	97.62 220	98.43 148	99.35 223	99.47 47	99.28 150	99.05 206	96.72 246	99.82 207	98.09 159	99.36 342	99.59 109

MVS		93.19 477	92.09 483	96.50 440	96.91 505	94.03 425	98.07 200	98.06 427	68.01 541	94.56 507	96.48 473	95.96 293	99.30 469	83.84 527	96.89 503	96.17 511

v2v482		98.56 179	98.62 154	98.37 288	99.42 176	95.81 345	97.58 288	99.16 299	97.90 239	99.28 150	99.01 224	95.98 291	99.79 246	99.33 59	99.90 88	99.51 164

V42		98.78 133	98.78 126	98.76 209	99.44 169	97.04 276	98.27 170	99.19 288	97.87 241	99.25 164	99.16 169	96.84 232	99.78 258	99.21 70	99.84 114	99.46 198

SD-MVS		98.40 206	98.68 141	97.54 386	98.96 310	97.99 171	97.88 236	99.36 217	98.20 209	99.63 66	99.04 208	98.76 46	95.33 538	96.56 321	99.74 195	99.31 276
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
GA-MVS		95.86 417	95.32 427	97.49 391	98.60 386	94.15 418	93.83 508	97.93 429	95.49 415	96.68 451	97.42 448	83.21 489	99.30 469	96.22 347	98.55 443	99.01 352

MSLP-MVS++		98.02 263	98.14 244	97.64 373	98.58 391	95.19 380	97.48 302	99.23 280	97.47 281	97.90 368	98.62 330	97.04 218	98.81 498	97.55 218	99.41 335	98.94 369

APDe-MVS		98.99 94	98.79 124	99.60 16	99.21 238	99.15 52	98.87 89	99.48 157	97.57 269	99.35 130	99.24 144	97.83 151	99.89 97	97.88 182	99.70 226	99.75 62
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
APD-MVS_3200maxsize		98.84 119	98.61 158	99.53 38	99.19 246	99.27 26	98.49 140	99.33 235	98.64 161	99.03 204	98.98 235	97.89 147	99.85 158	96.54 325	99.42 334	99.46 198

ADS-MVSNet2		95.43 434	94.98 438	96.76 433	98.14 439	91.74 477	97.92 231	97.76 432	90.23 509	96.51 463	98.91 253	85.61 468	99.85 158	92.88 459	96.90 501	98.69 409

EI-MVSNet		98.40 206	98.51 171	98.04 330	99.10 272	94.73 400	97.20 338	98.87 354	98.97 127	99.06 191	99.02 212	96.00 286	99.80 233	98.58 119	99.82 133	99.60 102

Regformer		0.00 515	0.00 518	0.00 530	0.00 553	0.00 555	0.00 541	0.00 554	0.00 548	0.00 549	0.00 548	0.00 552	0.00 549	0.00 547	0.00 547	0.00 545

CVMVSNet		96.25 399	97.21 326	93.38 516	99.10 272	80.56 546	97.20 338	98.19 422	96.94 334	99.00 207	99.02 212	89.50 437	99.80 233	96.36 338	99.59 277	99.78 50

pmmvs4		97.58 308	97.28 319	98.51 266	98.84 335	96.93 285	95.40 455	98.52 403	93.60 470	98.61 293	98.65 321	95.10 324	99.60 387	96.97 273	99.79 159	98.99 356

EU-MVSNet		97.66 302	98.50 174	95.13 492	99.63 83	85.84 526	98.35 161	98.21 419	98.23 201	99.54 79	99.46 80	95.02 326	99.68 338	98.24 146	99.87 100	99.87 22

VNet		98.42 202	98.30 215	98.79 199	98.79 349	97.29 251	98.23 173	98.66 388	99.31 69	98.85 249	98.80 284	94.80 335	99.78 258	98.13 155	99.13 388	99.31 276

test-LLR		93.90 464	93.85 458	94.04 505	96.53 515	84.62 532	94.05 502	92.39 525	96.17 377	94.12 511	95.07 503	82.30 494	99.67 343	95.87 366	98.18 458	97.82 467

TESTMET0.1,1		92.19 493	91.77 491	93.46 512	96.48 520	82.80 541	94.05 502	91.52 533	94.45 451	94.00 515	94.88 509	66.65 530	99.56 404	95.78 371	98.11 464	98.02 457

test-mter		92.33 491	91.76 492	94.04 505	96.53 515	84.62 532	94.05 502	92.39 525	94.00 466	94.12 511	95.07 503	65.63 536	99.67 343	95.87 366	98.18 458	97.82 467

VPA-MVSNet		99.30 33	99.30 44	99.28 96	99.49 148	98.36 127	99.00 73	99.45 176	99.63 28	99.52 87	99.44 85	98.25 107	99.88 115	99.09 79	99.84 114	99.62 92

ACMMPR		98.70 147	98.42 190	99.54 31	99.52 131	99.14 57	98.52 130	99.31 242	97.47 281	98.56 304	98.54 340	97.75 159	99.88 115	96.57 317	99.59 277	99.58 117

testgi		98.32 222	98.39 195	98.13 316	99.57 103	95.54 353	97.78 250	99.49 155	97.37 296	99.19 174	97.65 430	98.96 30	99.49 431	96.50 328	98.99 406	99.34 260

test20.03		98.78 133	98.77 127	98.78 202	99.46 162	97.20 262	97.78 250	99.24 278	99.04 119	99.41 114	98.90 256	97.65 165	99.76 270	97.70 205	99.79 159	99.39 230

thres600view7		94.45 452	93.83 459	96.29 448	99.06 284	91.53 481	97.99 221	94.24 514	98.34 188	97.44 408	95.01 505	79.84 500	99.67 343	84.33 526	98.23 455	97.66 479

ADS-MVSNet		95.24 439	94.93 441	96.18 456	98.14 439	90.10 506	97.92 231	97.32 450	90.23 509	96.51 463	98.91 253	85.61 468	99.74 289	92.88 459	96.90 501	98.69 409

MP-MVS		98.46 198	98.09 247	99.54 31	99.57 103	99.22 31	98.50 137	99.19 288	97.61 265	97.58 393	98.66 319	97.40 195	99.88 115	94.72 403	99.60 273	99.54 143
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		17.12 511	20.53 514	6.87 529	12.05 551	4.20 554	93.62 512	6.73 552	4.62 547	10.41 547	24.33 544	8.28 551	3.56 548	9.69 546	15.07 545	12.86 544

thres400		94.14 460	93.44 464	96.24 451	98.93 314	91.44 484	97.60 285	94.29 511	97.94 235	97.10 422	94.31 515	79.67 502	99.62 375	83.05 529	98.08 466	97.66 479

test123		17.04 512	20.11 515	7.82 528	10.25 552	4.91 553	94.80 473	4.47 553	4.93 546	10.00 548	24.28 545	9.69 550	3.64 547	10.14 545	12.43 546	14.92 543

thres200		93.72 468	93.14 470	95.46 486	98.66 379	91.29 488	96.61 381	94.63 506	97.39 294	96.83 443	93.71 518	79.88 499	99.56 404	82.40 532	98.13 463	95.54 518

test0.0.03 1		94.51 451	93.69 461	96.99 418	96.05 526	93.61 449	94.97 469	93.49 520	96.17 377	97.57 395	94.88 509	82.30 494	99.01 490	93.60 438	94.17 530	98.37 441

pmmvs3		95.03 444	94.40 452	96.93 422	97.70 469	92.53 466	95.08 466	97.71 434	88.57 523	97.71 383	98.08 399	79.39 504	99.82 207	96.19 349	99.11 392	98.43 434

EMVS		93.83 465	94.02 456	93.23 517	96.83 508	84.96 529	89.77 534	96.32 481	97.92 237	97.43 409	96.36 478	86.17 460	98.93 493	87.68 516	97.73 478	95.81 516

E-PMN		94.17 459	94.37 453	93.58 511	96.86 506	85.71 528	90.11 533	97.07 459	98.17 213	97.82 378	97.19 457	84.62 478	98.94 492	89.77 508	97.68 479	96.09 515

PGM-MVS		98.66 161	98.37 201	99.55 28	99.53 127	99.18 42	98.23 173	99.49 155	97.01 331	98.69 276	98.88 264	98.00 134	99.89 97	95.87 366	99.59 277	99.58 117

LCM-MVSNet-Re		98.64 164	98.48 180	99.11 126	98.85 334	98.51 113	98.49 140	99.83 26	98.37 185	99.69 55	99.46 80	98.21 115	99.92 65	94.13 422	99.30 358	98.91 374

LCM-MVSNet		99.93 1	99.92 1	99.94 1	99.99 1	99.97 1	99.90 1	99.89 14	99.98 1	99.99 1	99.96 1	99.77 2	100.00 1	99.81 16	100.00 1	99.85 30

MCST-MVS		98.00 266	97.63 299	99.10 128	99.24 230	98.17 145	96.89 360	98.73 383	95.66 406	97.92 366	97.70 428	97.17 211	99.66 356	96.18 351	99.23 371	99.47 195

mvs_anonymous		97.83 291	98.16 241	96.87 426	98.18 434	91.89 476	97.31 325	98.90 348	97.37 296	98.83 253	99.46 80	96.28 272	99.79 246	98.90 94	98.16 461	98.95 365

MVS_Test		98.18 247	98.36 203	97.67 366	98.48 401	94.73 400	98.18 179	99.02 328	97.69 256	98.04 358	99.11 187	97.22 208	99.56 404	98.57 121	98.90 416	98.71 405

MDA-MVSNet-bldmvs		97.94 273	97.91 272	98.06 327	99.44 169	94.96 388	96.63 379	99.15 304	98.35 187	98.83 253	99.11 187	94.31 354	99.85 158	96.60 314	98.72 426	99.37 242

CDPH-MVS		97.26 336	96.66 368	99.07 136	99.00 303	98.15 146	96.03 423	99.01 331	91.21 504	97.79 379	97.85 417	96.89 230	99.69 326	92.75 465	99.38 341	99.39 230

test12				98.93 168	98.58 391	97.83 194		98.66 388		96.53 459		95.51 310	99.69 326		99.13 388	99.27 288

casdiffmvs		98.95 102	99.00 94	98.81 192	99.38 185	97.33 242	97.82 244	99.57 109	99.17 93	99.35 130	99.17 167	98.35 94	99.69 326	98.46 129	99.73 199	99.41 220
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
diffmvs		98.22 239	98.24 228	98.17 311	99.00 303	95.44 364	96.38 398	99.58 101	97.79 249	98.53 309	98.50 349	96.76 242	99.74 289	97.95 177	99.64 256	99.34 260
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
baseline2		93.73 467	92.83 474	96.42 443	97.70 469	91.28 489	96.84 362	89.77 537	93.96 467	92.44 527	95.93 485	79.14 505	99.77 264	92.94 456	96.76 505	98.21 446

baseline1		95.96 414	95.44 419	97.52 388	98.51 400	93.99 432	98.39 157	96.09 487	98.21 205	98.40 328	97.76 424	86.88 454	99.63 371	95.42 385	89.27 536	98.95 365

YYNet1		97.60 305	97.67 292	97.39 399	99.04 289	93.04 457	95.27 459	98.38 412	97.25 310	98.92 233	98.95 245	95.48 312	99.73 296	96.99 269	98.74 424	99.41 220

PMMVS2		98.07 259	98.08 250	98.04 330	99.41 179	94.59 406	94.59 484	99.40 205	97.50 278	98.82 256	98.83 277	96.83 234	99.84 177	97.50 224	99.81 140	99.71 65

MDA-MVSNet_test_wron		97.60 305	97.66 295	97.41 398	99.04 289	93.09 453	95.27 459	98.42 409	97.26 309	98.88 242	98.95 245	95.43 314	99.73 296	97.02 265	98.72 426	99.41 220

tpmvs		95.02 445	95.25 430	94.33 500	96.39 523	85.87 525	98.08 196	96.83 471	95.46 417	95.51 491	98.69 311	85.91 466	99.53 416	94.16 418	96.23 511	97.58 482

PM-MVS		98.82 125	98.72 132	99.12 124	99.64 77	98.54 111	97.98 222	99.68 63	97.62 262	99.34 134	99.18 163	97.54 180	99.77 264	97.79 191	99.74 195	99.04 347

HQP_MVS		97.99 269	97.67 292	98.93 168	99.19 246	97.65 217	97.77 253	99.27 265	98.20 209	97.79 379	97.98 407	94.90 328	99.70 316	94.42 412	99.51 307	99.45 204

plane_prior7					99.19 246	97.87 190

plane_prior6					98.99 306	97.70 213						94.90 328

plane_prior5								99.27 265					99.70 316	94.42 412	99.51 307	99.45 204

plane_prior4											97.98 407

plane_prior3						97.78 204			97.41 291	97.79 379

plane_prior2							97.77 253		98.20 209

plane_prior1					99.05 287

plane_prior						97.65 217	97.07 346		96.72 351						99.36 342

PS-CasMVS		99.40 25	99.33 37	99.62 9	99.71 49	99.10 65	99.29 36	99.53 134	99.53 41	99.46 101	99.41 94	98.23 110	99.95 25	98.89 96	99.95 39	99.81 41

UniMVSNet_NR-MVSNet		98.86 116	98.68 141	99.40 71	99.17 256	98.74 91	97.68 268	99.40 205	99.14 98	99.06 191	98.59 335	96.71 247	99.93 53	98.57 121	99.77 172	99.53 157

PEN-MVS		99.41 24	99.34 35	99.62 9	99.73 38	99.14 57	99.29 36	99.54 130	99.62 32	99.56 74	99.42 89	98.16 122	99.96 13	98.78 102	99.93 57	99.77 53

TransMVSNet (Re)		99.44 19	99.47 21	99.36 74	99.80 21	98.58 106	99.27 42	99.57 109	99.39 58	99.75 44	99.62 40	99.17 20	99.83 195	99.06 82	99.62 266	99.66 80

DTE-MVSNet		99.43 22	99.35 33	99.66 7	99.71 49	99.30 21	99.31 30	99.51 142	99.64 26	99.56 74	99.46 80	98.23 110	99.97 6	98.78 102	99.93 57	99.72 64

DU-MVS		98.82 125	98.63 152	99.39 72	99.16 258	98.74 91	97.54 294	99.25 273	98.84 148	99.06 191	98.76 295	96.76 242	99.93 53	98.57 121	99.77 172	99.50 168

UniMVSNet (Re)		98.87 112	98.71 135	99.35 80	99.24 230	98.73 94	97.73 263	99.38 209	98.93 132	99.12 183	98.73 298	96.77 240	99.86 144	98.63 116	99.80 152	99.46 198

CP-MVSNet		99.21 47	99.09 82	99.56 26	99.65 71	98.96 77	99.13 59	99.34 229	99.42 55	99.33 137	99.26 137	97.01 223	99.94 41	98.74 107	99.93 57	99.79 47

WR-MVS_H		99.33 30	99.22 54	99.65 8	99.71 49	99.24 29	99.32 26	99.55 124	99.46 49	99.50 93	99.34 115	97.30 201	99.93 53	98.90 94	99.93 57	99.77 53

WR-MVS		98.40 206	98.19 235	99.03 146	99.00 303	97.65 217	96.85 361	98.94 338	98.57 174	98.89 238	98.50 349	95.60 306	99.85 158	97.54 220	99.85 109	99.59 109

NR-MVSNet		98.95 102	98.82 121	99.36 74	99.16 258	98.72 96	99.22 46	99.20 284	99.10 107	99.72 47	98.76 295	96.38 266	99.86 144	98.00 170	99.82 133	99.50 168

Baseline_NR-MVSNet		98.98 98	98.86 115	99.36 74	99.82 19	98.55 108	97.47 306	99.57 109	99.37 60	99.21 172	99.61 43	96.76 242	99.83 195	98.06 162	99.83 126	99.71 65

TranMVSNet+NR-MVSNet		99.17 52	99.07 85	99.46 63	99.37 191	98.87 84	98.39 157	99.42 196	99.42 55	99.36 128	99.06 199	98.38 89	99.95 25	98.34 141	99.90 88	99.57 124

TSAR-MVS + GP.		98.18 247	97.98 260	98.77 207	98.71 360	97.88 189	96.32 403	98.66 388	96.33 370	99.23 168	98.51 345	97.48 190	99.40 453	97.16 252	99.46 321	99.02 350

n2								0.00 554

nn								0.00 554

mPP-MVS		98.64 164	98.34 207	99.54 31	99.54 123	99.17 43	98.63 116	99.24 278	97.47 281	98.09 352	98.68 313	97.62 170	99.89 97	96.22 347	99.62 266	99.57 124

door-mid								99.57 109

XVG-OURS-SEG-HR		98.49 195	98.28 218	99.14 122	99.49 148	98.83 86	96.54 385	99.48 157	97.32 301	99.11 184	98.61 332	99.33 15	99.30 469	96.23 346	98.38 448	99.28 285

mvsmamba		97.57 309	97.26 321	98.51 266	98.69 369	96.73 299	98.74 99	97.25 452	97.03 330	97.88 370	99.23 150	90.95 421	99.87 135	96.61 313	99.00 404	98.91 374

MVSFormer		98.26 234	98.43 188	97.77 352	98.88 328	93.89 438	99.39 20	99.56 119	99.11 100	98.16 344	98.13 392	93.81 368	99.97 6	99.26 65	99.57 286	99.43 212

jason		97.45 318	97.35 316	97.76 355	99.24 230	93.93 434	95.86 435	98.42 409	94.24 455	98.50 312	98.13 392	94.82 332	99.91 74	97.22 247	99.73 199	99.43 212
jason: jason.
lupinMVS		97.06 354	96.86 350	97.65 370	98.88 328	93.89 438	95.48 451	97.97 428	93.53 471	98.16 344	97.58 434	93.81 368	99.91 74	96.77 292	99.57 286	99.17 325

test_djsdf		99.52 13	99.51 15	99.53 38	99.86 14	98.74 91	99.39 20	99.56 119	99.11 100	99.70 51	99.73 20	99.00 27	99.97 6	99.26 65	99.98 12	99.89 16

HPM-MVS_fast		99.01 90	98.82 121	99.57 21	99.71 49	99.35 16	99.00 73	99.50 147	97.33 299	98.94 230	98.86 267	98.75 47	99.82 207	97.53 221	99.71 217	99.56 130

K. test v3		98.00 266	97.66 295	99.03 146	99.79 23	97.56 223	99.19 53	92.47 524	99.62 32	99.52 87	99.66 32	89.61 435	99.96 13	99.25 67	99.81 140	99.56 130

lessismore_v0				98.97 160	99.73 38	97.53 226		86.71 542		99.37 125	99.52 67	89.93 430	99.92 65	98.99 88	99.72 208	99.44 208

SixPastTwentyTwo		98.75 138	98.62 154	99.16 118	99.83 18	97.96 178	99.28 40	98.20 420	99.37 60	99.70 51	99.65 36	92.65 395	99.93 53	99.04 84	99.84 114	99.60 102

OurMVSNet-221017-0		99.37 28	99.31 41	99.53 38	99.91 3	98.98 71	99.63 7	99.58 101	99.44 52	99.78 39	99.76 15	96.39 264	99.92 65	99.44 54	99.92 71	99.68 73

HPM-MVS		98.79 131	98.53 169	99.59 20	99.65 71	99.29 23	99.16 55	99.43 190	96.74 350	98.61 293	98.38 363	98.62 64	99.87 135	96.47 329	99.67 244	99.59 109
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
XVG-OURS		98.53 188	98.34 207	99.11 126	99.50 140	98.82 88	95.97 426	99.50 147	97.30 304	99.05 199	98.98 235	99.35 14	99.32 466	95.72 373	99.68 238	99.18 321

XVG-ACMP-BASELINE		98.56 179	98.34 207	99.22 109	99.54 123	98.59 105	97.71 264	99.46 172	97.25 310	98.98 212	98.99 230	97.54 180	99.84 177	95.88 363	99.74 195	99.23 301

casdiffmvs_mvg		99.12 69	99.16 62	98.99 154	99.43 174	97.73 210	98.00 214	99.62 87	99.22 80	99.55 77	99.22 152	98.93 33	99.75 282	98.66 113	99.81 140	99.50 168
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
LPG-MVS_test		98.71 142	98.46 184	99.47 61	99.57 103	98.97 73	98.23 173	99.48 157	96.60 357	99.10 187	99.06 199	98.71 51	99.83 195	95.58 382	99.78 164	99.62 92

LGP-MVS_train				99.47 61	99.57 103	98.97 73		99.48 157	96.60 357	99.10 187	99.06 199	98.71 51	99.83 195	95.58 382	99.78 164	99.62 92

baseline		98.96 101	99.02 90	98.76 209	99.38 185	97.26 254	98.49 140	99.50 147	98.86 142	99.19 174	99.06 199	98.23 110	99.69 326	98.71 110	99.76 188	99.33 266

test11								98.87 354

door								99.41 200

EPNet_dtu		94.93 447	94.78 443	95.38 488	93.58 537	87.68 520	96.78 365	95.69 497	97.35 298	89.14 537	98.09 398	88.15 449	99.49 431	94.95 397	99.30 358	98.98 357
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x2688		97.49 314	97.14 331	98.54 261	99.68 64	96.09 329	96.50 389	99.62 87	91.58 498	98.84 251	98.97 237	92.36 398	99.88 115	96.76 293	99.95 39	99.67 78

EPNet		96.14 403	95.44 419	98.25 301	90.76 546	95.50 359	97.92 231	94.65 505	98.97 127	92.98 522	98.85 270	89.12 439	99.87 135	95.99 359	99.68 238	99.39 230
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS						96.79 294

HQP-NCC					98.67 374		96.29 405		96.05 384	95.55 486

ACMP_Plane					98.67 374		96.29 405		96.05 384	95.55 486

APD-MVS		98.10 254	97.67 292	99.42 67	99.11 270	98.93 79	97.76 256	99.28 262	94.97 434	98.72 272	98.77 290	97.04 218	99.85 158	93.79 432	99.54 297	99.49 176
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS														92.82 461

HQP4-MVS										95.56 485			99.54 414			99.32 271

HQP3-MVS								99.04 323							99.26 366

HQP2-MVS												93.84 366

CNVR-MVS		98.17 250	97.87 275	99.07 136	98.67 374	98.24 137	97.01 348	98.93 341	97.25 310	97.62 389	98.34 368	97.27 204	99.57 401	96.42 333	99.33 349	99.39 230

NCCC		97.86 283	97.47 310	99.05 143	98.61 384	98.07 162	96.98 351	98.90 348	97.63 261	97.04 428	97.93 412	95.99 290	99.66 356	95.31 387	98.82 420	99.43 212

114514_t		96.50 382	95.77 402	98.69 223	99.48 156	97.43 237	97.84 243	99.55 124	81.42 537	96.51 463	98.58 336	95.53 308	99.67 343	93.41 446	99.58 282	98.98 357

CP-MVS		98.70 147	98.42 190	99.52 44	99.36 192	99.12 62	98.72 104	99.36 217	97.54 275	98.30 332	98.40 360	97.86 150	99.89 97	96.53 326	99.72 208	99.56 130

DSMNet-mixed		97.42 321	97.60 301	96.87 426	99.15 262	91.46 482	98.54 128	99.12 307	92.87 485	97.58 393	99.63 39	96.21 275	99.90 81	95.74 372	99.54 297	99.27 288

tpm2		93.09 478	92.58 477	94.62 498	97.56 476	86.53 524	97.66 272	95.79 494	86.15 530	94.07 513	98.23 385	75.95 514	99.53 416	90.91 500	96.86 504	97.81 469

NP-MVS					98.84 335	97.39 239					96.84 464

EG-PatchMatch MVS		98.99 94	99.01 92	98.94 165	99.50 140	97.47 231	98.04 205	99.59 98	98.15 221	99.40 117	99.36 110	98.58 72	99.76 270	98.78 102	99.68 238	99.59 109

tpm cat1		93.29 475	93.13 471	93.75 509	97.39 489	84.74 530	97.39 313	97.65 438	83.39 535	94.16 510	98.41 359	82.86 492	99.39 455	91.56 488	95.35 525	97.14 495

SteuartSystems-ACMMP		98.79 131	98.54 167	99.54 31	99.73 38	99.16 48	98.23 173	99.31 242	97.92 237	98.90 235	98.90 256	98.00 134	99.88 115	96.15 352	99.72 208	99.58 117
Skip Steuart: Steuart Systems R&D Blog.
CostFormer		93.97 463	93.78 460	94.51 499	97.53 480	85.83 527	97.98 222	95.96 489	89.29 518	94.99 499	98.63 327	78.63 509	99.62 375	94.54 406	96.50 507	98.09 454

CR-MVSNet		96.28 396	95.95 398	97.28 402	97.71 467	94.22 413	98.11 191	98.92 345	92.31 491	96.91 435	99.37 104	85.44 471	99.81 224	97.39 234	97.36 493	97.81 469

JIA-IIPM		95.52 429	95.03 437	97.00 417	96.85 507	94.03 425	96.93 356	95.82 492	99.20 84	94.63 506	99.71 22	83.09 490	99.60 387	94.42 412	94.64 527	97.36 490

Patchmtry		97.35 328	96.97 341	98.50 270	97.31 492	96.47 314	98.18 179	98.92 345	98.95 131	98.78 262	99.37 104	85.44 471	99.85 158	95.96 361	99.83 126	99.17 325

PatchT		96.65 374	96.35 386	97.54 386	97.40 488	95.32 372	97.98 222	96.64 475	99.33 66	96.89 439	99.42 89	84.32 481	99.81 224	97.69 207	97.49 484	97.48 485

tpmrst		95.07 443	95.46 417	93.91 507	97.11 496	84.36 534	97.62 279	96.96 464	94.98 433	96.35 468	98.80 284	85.46 470	99.59 392	95.60 380	96.23 511	97.79 472

BH-w/o		95.13 442	94.89 442	95.86 471	98.20 432	91.31 487	95.65 444	97.37 444	93.64 469	96.52 462	95.70 491	93.04 387	99.02 488	88.10 515	95.82 521	97.24 494

tpm		94.67 449	94.34 454	95.66 479	97.68 472	88.42 515	97.88 236	94.90 503	94.46 448	96.03 478	98.56 339	78.66 508	99.79 246	95.88 363	95.01 526	98.78 397

DELS-MVS		98.27 232	98.20 231	98.48 272	98.86 331	96.70 300	95.60 446	99.20 284	97.73 253	98.45 319	98.71 302	97.50 186	99.82 207	98.21 150	99.59 277	98.93 370
Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023
BH-untuned		96.83 367	96.75 360	97.08 413	98.74 353	93.33 451	96.71 371	98.26 416	96.72 351	98.44 320	97.37 451	95.20 319	99.47 438	91.89 480	97.43 488	98.44 432

RPMNet		97.02 357	96.93 343	97.30 401	97.71 467	94.22 413	98.11 191	99.30 250	99.37 60	96.91 435	99.34 115	86.72 455	99.87 135	97.53 221	97.36 493	97.81 469

MVSTER		96.86 366	96.55 377	97.79 350	97.91 454	94.21 415	97.56 290	98.87 354	97.49 280	99.06 191	99.05 206	80.72 497	99.80 233	98.44 131	99.82 133	99.37 242

CPTT-MVS		97.84 289	97.36 315	99.27 99	99.31 206	98.46 116	98.29 166	99.27 265	94.90 436	97.83 376	98.37 364	94.90 328	99.84 177	93.85 431	99.54 297	99.51 164

GBi-Net		98.65 162	98.47 182	99.17 115	98.90 322	98.24 137	99.20 49	99.44 184	98.59 169	98.95 222	99.55 56	94.14 359	99.86 144	97.77 194	99.69 232	99.41 220

PVSNet_Blended_VisFu		98.17 250	98.15 242	98.22 307	99.73 38	95.15 381	97.36 320	99.68 63	94.45 451	98.99 211	99.27 131	96.87 231	99.94 41	97.13 258	99.91 80	99.57 124

PVSNet_BlendedMVS		97.55 310	97.53 304	97.60 377	98.92 318	93.77 442	96.64 378	99.43 190	94.49 446	97.62 389	99.18 163	96.82 235	99.67 343	94.73 401	99.93 57	99.36 250

UnsupCasMVSNet_eth		97.89 277	97.60 301	98.75 211	99.31 206	97.17 268	97.62 279	99.35 223	98.72 157	98.76 267	98.68 313	92.57 396	99.74 289	97.76 198	95.60 523	99.34 260

UnsupCasMVSNet_bld		97.30 333	96.92 345	98.45 275	99.28 215	96.78 297	96.20 411	99.27 265	95.42 419	98.28 336	98.30 375	93.16 381	99.71 308	94.99 394	97.37 491	98.87 380

PVSNet_Blended		96.88 364	96.68 364	97.47 394	98.92 318	93.77 442	94.71 475	99.43 190	90.98 507	97.62 389	97.36 452	96.82 235	99.67 343	94.73 401	99.56 290	98.98 357

FMVSNet5		96.01 408	95.20 434	98.41 281	97.53 480	96.10 326	98.74 99	99.50 147	97.22 319	98.03 359	99.04 208	69.80 523	99.88 115	97.27 243	99.71 217	99.25 295

test1		98.65 162	98.47 182	99.17 115	98.90 322	98.24 137	99.20 49	99.44 184	98.59 169	98.95 222	99.55 56	94.14 359	99.86 144	97.77 194	99.69 232	99.41 220

new_pmnet		96.99 361	96.76 358	97.67 366	98.72 356	94.89 392	95.95 430	98.20 420	92.62 488	98.55 306	98.54 340	94.88 331	99.52 420	93.96 426	99.44 330	98.59 421

FMVSNet3		97.50 311	97.24 323	98.29 297	98.08 445	95.83 343	97.86 240	98.91 347	97.89 240	98.95 222	98.95 245	87.06 453	99.81 224	97.77 194	99.69 232	99.23 301

dp		93.47 471	93.59 463	93.13 518	96.64 513	81.62 545	97.66 272	96.42 480	92.80 486	96.11 472	98.64 325	78.55 511	99.59 392	93.31 447	92.18 535	98.16 450

FMVSNet2		98.49 195	98.40 192	98.75 211	98.90 322	97.14 271	98.61 120	99.13 306	98.59 169	99.19 174	99.28 129	94.14 359	99.82 207	97.97 175	99.80 152	99.29 282

FMVSNet1		99.17 52	99.17 60	99.17 115	99.55 117	98.24 137	99.20 49	99.44 184	99.21 82	99.43 108	99.55 56	97.82 154	99.86 144	98.42 137	99.89 94	99.41 220

N_pmnet		97.63 304	97.17 327	98.99 154	99.27 218	97.86 191	95.98 425	93.41 521	95.25 426	99.47 100	98.90 256	95.63 304	99.85 158	96.91 276	99.73 199	99.27 288

cascas		94.79 448	94.33 455	96.15 461	96.02 528	92.36 471	92.34 526	99.26 271	85.34 532	95.08 498	94.96 508	92.96 388	98.53 505	94.41 415	98.59 440	97.56 483

BH-RMVSNet		96.83 367	96.58 376	97.58 379	98.47 402	94.05 422	96.67 375	97.36 445	96.70 354	97.87 371	97.98 407	95.14 323	99.44 447	90.47 505	98.58 441	99.25 295

UGNet		98.53 188	98.45 185	98.79 199	97.94 452	96.96 282	99.08 62	98.54 400	99.10 107	96.82 444	99.47 78	96.55 256	99.84 177	98.56 124	99.94 51	99.55 137
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022
WTY-MVS		96.67 373	96.27 392	97.87 345	98.81 343	94.61 405	96.77 366	97.92 430	94.94 435	97.12 421	97.74 425	91.11 420	99.82 207	93.89 428	98.15 462	99.18 321

XXY-MVS		99.14 62	99.15 67	99.10 128	99.76 30	97.74 208	98.85 93	99.62 87	98.48 181	99.37 125	99.49 74	98.75 47	99.86 144	98.20 151	99.80 152	99.71 65

EC-MVSNet		99.09 73	99.05 86	99.20 110	99.28 215	98.93 79	99.24 44	99.84 23	99.08 114	98.12 349	98.37 364	98.72 50	99.90 81	99.05 83	99.77 172	98.77 398

sss		97.21 342	96.93 343	98.06 327	98.83 337	95.22 379	96.75 368	98.48 405	94.49 446	97.27 416	97.90 413	92.77 392	99.80 233	96.57 317	99.32 352	99.16 331

Test_1112_low_res		96.99 361	96.55 377	98.31 294	99.35 197	95.47 363	95.84 438	99.53 134	91.51 500	96.80 445	98.48 352	91.36 417	99.83 195	96.58 315	99.53 301	99.62 92

1112_ss		97.29 335	96.86 350	98.58 246	99.34 202	96.32 320	96.75 368	99.58 101	93.14 477	96.89 439	97.48 443	92.11 406	99.86 144	96.91 276	99.54 297	99.57 124

ab-mvs-re		8.12 514	10.83 517	0.00 530	0.00 553	0.00 555	0.00 541	0.00 554	0.00 548	0.00 549	97.48 443	0.00 552	0.00 549	0.00 547	0.00 547	0.00 545

ab-mvs		98.41 203	98.36 203	98.59 245	99.19 246	97.23 256	99.32 26	98.81 368	97.66 259	98.62 291	99.40 97	96.82 235	99.80 233	95.88 363	99.51 307	98.75 401

TR-MVS		95.55 428	95.12 436	96.86 429	97.54 478	93.94 433	96.49 390	96.53 478	94.36 454	97.03 430	96.61 470	94.26 356	99.16 481	86.91 520	96.31 510	97.47 486

MDTV_nov1_ep13_2view						74.92 548	97.69 267		90.06 514	97.75 382		85.78 467		93.52 441		98.69 409

MDTV_nov1_ep13			95.22 432		97.06 499	83.20 539	97.74 261	96.16 483	94.37 453	96.99 431	98.83 277	83.95 485	99.53 416	93.90 427	97.95 474

MIMVSNet1		99.38 27	99.32 39	99.55 28	99.86 14	99.19 41	99.41 17	99.59 98	99.59 36	99.71 49	99.57 49	97.12 214	99.90 81	99.21 70	99.87 100	99.54 143

MIMVSNet		96.62 376	96.25 393	97.71 362	99.04 289	94.66 403	99.16 55	96.92 468	97.23 316	97.87 371	99.10 190	86.11 462	99.65 363	91.65 485	99.21 375	98.82 385

IterMVS-LS		98.55 183	98.70 138	98.09 321	99.48 156	94.73 400	97.22 337	99.39 207	98.97 127	99.38 121	99.31 124	96.00 286	99.93 53	98.58 119	99.97 21	99.60 102
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet		97.69 299	97.35 316	98.69 223	98.73 354	97.02 278	96.92 358	98.75 380	95.89 394	98.59 298	98.67 315	92.08 407	99.74 289	96.72 299	99.81 140	99.32 271
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref															99.77 172

IterMVS		97.73 295	98.11 246	96.57 438	99.24 230	90.28 504	95.52 450	99.21 282	98.86 142	99.33 137	99.33 118	93.11 383	99.94 41	98.49 128	99.94 51	99.48 187
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon		97.33 330	96.92 345	98.57 249	99.09 275	97.99 171	96.79 363	99.35 223	93.18 476	97.71 383	98.07 400	95.00 327	99.31 467	93.97 425	99.13 388	98.42 436

MVS_111021_LR		98.30 227	98.12 245	98.83 188	99.16 258	98.03 167	96.09 420	99.30 250	97.58 268	98.10 351	98.24 383	98.25 107	99.34 462	96.69 304	99.65 254	99.12 337

DP-MVS		98.93 104	98.81 123	99.28 96	99.21 238	98.45 117	98.46 145	99.33 235	99.63 28	99.48 96	99.15 175	97.23 207	99.75 282	97.17 251	99.66 252	99.63 91

ACMMP++															99.68 238

HQP-MVS		97.00 360	96.49 380	98.55 256	98.67 374	96.79 294	96.29 405	99.04 323	96.05 384	95.55 486	96.84 464	93.84 366	99.54 414	92.82 461	99.26 366	99.32 271

QAPM		97.31 331	96.81 356	98.82 190	98.80 346	97.49 227	99.06 66	99.19 288	90.22 511	97.69 385	99.16 169	96.91 229	99.90 81	90.89 501	99.41 335	99.07 341

Vis-MVSNet		99.34 29	99.36 32	99.27 99	99.73 38	98.26 135	99.17 54	99.78 36	99.11 100	99.27 152	99.48 75	98.82 38	99.95 25	98.94 91	99.93 57	99.59 109
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet		94.32 454	95.62 408	90.42 523	98.46 404	75.36 547	96.29 405	89.13 538	95.25 426	95.38 492	99.75 16	92.88 389	99.19 479	94.07 424	99.39 338	96.72 504

IS-MVSNet		98.19 245	97.90 273	99.08 134	99.57 103	97.97 175	99.31 30	98.32 413	99.01 123	98.98 212	99.03 211	91.59 411	99.79 246	95.49 384	99.80 152	99.48 187

HyFIR lowres test		97.19 344	96.60 375	98.96 162	99.62 87	97.28 252	95.17 463	99.50 147	94.21 456	99.01 206	98.32 373	86.61 456	99.99 2	97.10 260	99.84 114	99.60 102

EPMVS		93.72 468	93.27 467	95.09 494	96.04 527	87.76 519	98.13 186	85.01 544	94.69 442	96.92 433	98.64 325	78.47 512	99.31 467	95.04 393	96.46 508	98.20 447

PAPM_NR		96.82 369	96.32 388	98.30 296	99.07 279	96.69 301	97.48 302	98.76 376	95.81 401	96.61 455	96.47 474	94.12 362	99.17 480	90.82 503	97.78 476	99.06 342

TAMVS		98.24 238	98.05 253	98.80 195	99.07 279	97.18 266	97.88 236	98.81 368	96.66 356	99.17 182	99.21 154	94.81 334	99.77 264	96.96 274	99.88 95	99.44 208

PAPR		95.29 437	94.47 449	97.75 356	97.50 486	95.14 382	94.89 472	98.71 385	91.39 502	95.35 493	95.48 497	94.57 342	99.14 483	84.95 525	97.37 491	98.97 361

RPSCF		98.62 169	98.36 203	99.42 67	99.65 71	99.42 10	98.55 126	99.57 109	97.72 255	98.90 235	99.26 137	96.12 281	99.52 420	95.72 373	99.71 217	99.32 271

Vis-MVSNet (Re-imp)		97.46 316	97.16 328	98.34 291	99.55 117	96.10 326	98.94 81	98.44 406	98.32 192	98.16 344	98.62 330	88.76 440	99.73 296	93.88 429	99.79 159	99.18 321

test_0402		98.76 137	98.71 135	98.93 168	99.56 111	98.14 148	98.45 147	99.34 229	99.28 73	98.95 222	98.91 253	98.34 95	99.79 246	95.63 378	99.91 80	98.86 381

MVS_111021_HR		98.25 237	98.08 250	98.75 211	99.09 275	97.46 233	95.97 426	99.27 265	97.60 267	97.99 362	98.25 381	98.15 124	99.38 457	96.87 284	99.57 286	99.42 217

CSCG		98.68 157	98.50 174	99.20 110	99.45 167	98.63 100	98.56 125	99.57 109	97.87 241	98.85 249	98.04 402	97.66 164	99.84 177	96.72 299	99.81 140	99.13 336

PatchMatch-RL		97.24 339	96.78 357	98.61 242	99.03 292	97.83 194	96.36 400	99.06 316	93.49 473	97.36 414	97.78 422	95.75 300	99.49 431	93.44 445	98.77 422	98.52 424

API-MVS		97.04 356	96.91 348	97.42 397	97.88 455	98.23 141	98.18 179	98.50 404	97.57 269	97.39 412	96.75 467	96.77 240	99.15 482	90.16 506	99.02 401	94.88 520

Test By Simon												96.52 257

TDRefinement		99.42 23	99.38 28	99.55 28	99.76 30	99.33 20	99.68 6	99.71 48	99.38 59	99.53 83	99.61 43	98.64 61	99.80 233	98.24 146	99.84 114	99.52 160

USDC		97.41 322	97.40 311	97.44 396	98.94 312	93.67 445	95.17 463	99.53 134	94.03 464	98.97 216	99.10 190	95.29 317	99.34 462	95.84 369	99.73 199	99.30 280

EPP-MVSNet		98.30 227	98.04 254	99.07 136	99.56 111	97.83 194	99.29 36	98.07 426	99.03 121	98.59 298	99.13 181	92.16 403	99.90 81	96.87 284	99.68 238	99.49 176

PMMVS		96.51 380	95.98 396	98.09 321	97.53 480	95.84 342	94.92 470	98.84 363	91.58 498	96.05 476	95.58 492	95.68 303	99.66 356	95.59 381	98.09 465	98.76 400

PAPM		91.88 497	90.34 499	96.51 439	98.06 447	92.56 465	92.44 525	97.17 456	86.35 529	90.38 534	96.01 482	86.61 456	99.21 478	70.65 541	95.43 524	97.75 474

ACMMP		98.75 138	98.50 174	99.52 44	99.56 111	99.16 48	98.87 89	99.37 213	97.16 322	98.82 256	99.01 224	97.71 161	99.87 135	96.29 344	99.69 232	99.54 143
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence
CNLPA		97.17 346	96.71 362	98.55 256	98.56 394	98.05 166	96.33 402	98.93 341	96.91 338	97.06 426	97.39 449	94.38 350	99.45 445	91.66 484	99.18 382	98.14 451

PatchmatchNet		95.58 427	95.67 407	95.30 491	97.34 490	87.32 522	97.65 274	96.65 474	95.30 423	97.07 425	98.69 311	84.77 476	99.75 282	94.97 396	98.64 435	98.83 383
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS		98.29 230	97.95 264	99.34 83	98.44 407	99.16 48	98.12 190	99.38 209	96.01 388	98.06 355	98.43 357	97.80 155	99.67 343	95.69 375	99.58 282	99.20 311

F-COLMAP		97.30 333	96.68 364	99.14 122	99.19 246	98.39 121	97.27 332	99.30 250	92.93 482	96.62 454	98.00 405	95.73 301	99.68 338	92.62 468	98.46 446	99.35 256

ANet_high		99.57 10	99.67 6	99.28 96	99.89 6	98.09 155	99.14 58	99.93 6	99.82 8	99.93 6	99.81 8	99.17 20	99.94 41	99.31 61	100.00 1	99.82 36

wuyk23d		96.06 404	97.62 300	91.38 520	98.65 383	98.57 107	98.85 93	96.95 465	96.86 344	99.90 14	99.16 169	99.18 19	98.40 506	89.23 512	99.77 172	77.18 542

OMC-MVS		97.88 280	97.49 307	99.04 145	98.89 327	98.63 100	96.94 354	99.25 273	95.02 432	98.53 309	98.51 345	97.27 204	99.47 438	93.50 443	99.51 307	99.01 352

MG-MVS		96.77 370	96.61 373	97.26 404	98.31 419	93.06 454	95.93 431	98.12 425	96.45 367	97.92 366	98.73 298	93.77 370	99.39 455	91.19 495	99.04 397	99.33 266

AdaColmap		97.14 348	96.71 362	98.46 274	98.34 417	97.80 203	96.95 353	98.93 341	95.58 410	96.92 433	97.66 429	95.87 297	99.53 416	90.97 498	99.14 386	98.04 456

uanet		0.00 515	0.00 518	0.00 530	0.00 553	0.00 555	0.00 541	0.00 554	0.00 548	0.00 549	0.00 548	0.00 552	0.00 549	0.00 547	0.00 547	0.00 545

ITE_SJBPF				98.87 177	99.22 236	98.48 115		99.35 223	97.50 278	98.28 336	98.60 334	97.64 168	99.35 461	93.86 430	99.27 362	98.79 396

DeepMVS_CX				93.44 514	98.24 428	94.21 415		94.34 510	64.28 542	91.34 531	94.87 511	89.45 438	92.77 541	77.54 537	93.14 532	93.35 528

TinyColmap		97.89 277	97.98 260	97.60 377	98.86 331	94.35 411	96.21 410	99.44 184	97.45 288	99.06 191	98.88 264	97.99 137	99.28 473	94.38 416	99.58 282	99.18 321

MAR-MVS		96.47 386	95.70 405	98.79 199	97.92 453	99.12 62	98.28 167	98.60 393	92.16 493	95.54 489	96.17 480	94.77 337	99.52 420	89.62 509	98.23 455	97.72 477
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020
LF4IMVS		97.90 275	97.69 291	98.52 265	99.17 256	97.66 215	97.19 342	99.47 167	96.31 372	97.85 375	98.20 387	96.71 247	99.52 420	94.62 404	99.72 208	98.38 439

MSDG		97.71 297	97.52 305	98.28 298	98.91 321	96.82 292	94.42 489	99.37 213	97.65 260	98.37 329	98.29 378	97.40 195	99.33 464	94.09 423	99.22 372	98.68 412

LS3D		98.63 166	98.38 199	99.36 74	97.25 493	99.38 12	99.12 61	99.32 237	99.21 82	98.44 320	98.88 264	97.31 200	99.80 233	96.58 315	99.34 347	98.92 371

CLD-MVS		97.49 314	97.16 328	98.48 272	99.07 279	97.03 277	94.71 475	99.21 282	94.46 448	98.06 355	97.16 458	97.57 176	99.48 435	94.46 409	99.78 164	98.95 365
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS		93.44 472	92.23 481	97.08 413	99.25 229	97.86 191	95.61 445	97.16 457	92.90 484	93.76 519	98.65 321	75.94 515	95.66 536	79.30 536	97.49 484	97.73 476

Gipuma		99.03 88	99.16 62	98.64 232	99.94 2	98.51 113	99.32 26	99.75 43	99.58 38	98.60 296	99.62 40	98.22 113	99.51 426	97.70 205	99.73 199	97.89 464
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015

High-resolution multi-view benchmark