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.

DeepPCF-MVS	93.56 1	96.55 57	97.84 11	92.68 300	98.71 96	78.11 432	99.70 41	97.71 102	98.18 1	97.36 84	99.76 1	90.37 58	99.94 40	99.27 25	99.54 58	99.99 2

DeepC-MVS_fast	93.52 2	97.16 28	96.84 37	98.13 27	99.61 29	94.45 56	98.85 164	97.64 124	96.51 25	95.88 126	99.39 23	87.35 106	99.99 9	96.61 103	99.69 38	99.96 11
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
PLC	91.07 3	94.23 144	94.01 132	94.87 215	99.17 70	87.49 280	99.25 112	96.55 253	88.43 250	91.26 234	98.21 150	85.92 140	99.86 81	89.77 244	97.57 147	97.24 270
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
DeepC-MVS	91.02 4	94.56 136	93.92 140	96.46 115	97.16 164	90.76 160	98.39 246	97.11 210	93.92 66	88.66 278	98.33 143	78.14 273	99.85 85	95.02 146	98.57 121	98.78 173
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
PCF-MVS	89.78 5	91.26 241	89.63 260	96.16 142	95.44 246	91.58 138	95.29 404	96.10 292	85.07 337	82.75 334	97.45 187	78.28 272	99.78 106	80.60 367	95.65 194	97.12 272
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
IB-MVS	89.43 6	92.12 221	90.83 240	95.98 154	95.40 249	90.78 159	99.81 20	98.06 53	91.23 143	85.63 306	93.66 324	90.63 51	98.78 185	91.22 224	71.85 424	98.36 219
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
HY-MVS	88.56 7	95.29 106	94.23 124	98.48 16	97.72 126	96.41 14	94.03 423	98.74 15	92.42 109	95.65 136	94.76 303	86.52 129	99.49 134	95.29 140	92.97 241	99.53 89

3Dnovator+	87.72 8	93.43 175	91.84 211	98.17 25	95.73 232	95.08 37	98.92 159	97.04 217	91.42 136	81.48 367	97.60 177	74.60 309	99.79 103	90.84 230	98.97 92	99.64 76

TAPA-MVS	87.50 9	90.35 268	89.05 277	94.25 248	98.48 102	85.17 347	98.42 235	96.58 251	82.44 392	87.24 291	98.53 127	82.77 201	98.84 183	59.09 472	97.88 139	98.72 185
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMP	87.39 10	88.71 307	88.24 298	90.12 365	93.91 333	81.06 407	98.50 223	95.67 354	89.43 209	80.37 378	95.55 287	65.67 393	97.83 265	90.55 235	84.51 326	91.47 372
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
3Dnovator	87.35 11	93.17 188	91.77 214	97.37 60	95.41 248	93.07 93	98.82 167	97.85 72	91.53 131	82.56 340	97.58 179	71.97 338	99.82 94	91.01 227	99.23 77	99.22 123

PVSNet	87.13 12	93.69 163	92.83 179	96.28 130	97.99 117	90.22 177	99.38 95	98.93 12	91.42 136	93.66 177	97.68 172	71.29 346	99.64 122	87.94 268	97.20 157	98.98 146

ACMM	86.95 13	88.77 305	88.22 299	90.43 357	93.61 343	81.34 401	98.50 223	95.92 320	87.88 271	83.85 321	95.20 298	67.20 378	97.89 260	86.90 281	84.90 324	92.06 351
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
OpenMVS	85.28 14	90.75 256	88.84 283	96.48 114	93.58 344	93.51 82	98.80 170	97.41 174	82.59 386	78.62 401	97.49 184	68.00 371	99.82 94	84.52 316	98.55 123	96.11 306

ACMH+	83.78 15	84.21 380	82.56 386	89.15 392	93.73 340	79.16 420	96.43 370	94.28 422	81.09 408	74.00 433	94.03 311	54.58 445	97.67 286	76.10 398	78.81 367	90.63 410

PVSNet_0	83.28 16	87.31 330	85.16 346	93.74 272	94.78 294	84.59 356	98.91 160	98.69 20	89.81 191	78.59 406	93.23 334	61.95 416	99.34 156	94.75 154	55.72 479	97.30 267

ACMH	83.09 17	84.60 373	82.61 384	90.57 352	93.18 355	82.94 377	96.27 375	94.92 402	81.01 409	72.61 446	93.61 325	56.54 433	97.79 270	74.31 410	81.07 354	90.99 396
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
COLMAP_ROB	82.69 18	84.54 375	82.82 377	89.70 378	96.72 185	78.85 422	95.89 389	92.83 442	71.55 458	77.54 415	95.89 281	59.40 426	99.14 169	67.26 449	88.26 302	91.11 394
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
LTVRE_ROB	81.71 19	84.59 374	82.72 382	90.18 363	92.89 361	83.18 375	93.15 432	94.74 407	78.99 419	75.14 428	92.69 346	65.64 394	97.63 290	69.46 438	81.82 350	89.74 427
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
OpenMVS_ROB	73.86 20	77.99 427	75.06 432	86.77 419	83.81 460	77.94 433	96.38 372	91.53 462	67.54 472	68.38 459	87.13 442	43.94 470	96.08 372	55.03 479	81.83 349	86.29 461

CMPMVS	58.40 21	80.48 409	80.11 407	81.59 455	85.10 455	59.56 483	94.14 421	95.95 314	68.54 469	60.71 478	93.31 331	55.35 441	97.87 263	83.06 339	84.85 325	87.33 453
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MVE	44.00 22	41.70 461	37.64 466	53.90 479	49.46 502	43.37 499	65.09 493	66.66 501	26.19 497	25.77 498	48.53 495	3.58 504	63.35 498	26.15 494	27.28 494	54.97 493
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
PMVS	41.42 23	45.67 460	42.50 463	55.17 478	34.28 504	32.37 504	66.24 492	78.71 496	30.72 494	22.04 499	59.59 490	4.59 502	77.85 495	27.49 493	58.84 468	55.29 492
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
gbinet_0.2-2-1-0.02		83.16 394	80.42 403	91.39 333	83.70 461	87.60 276	98.62 201	95.77 340	75.83 438	79.33 393	87.92 430	64.07 404	95.34 411	81.87 357	56.67 476	91.25 389

0.3-1-1-0.015		91.27 240	89.64 259	96.15 143	92.69 364	91.62 134	99.74 36	97.35 184	84.68 348	92.71 200	93.18 335	85.31 157	97.75 279	92.11 214	68.98 435	99.09 135

0.4-1-1-0.1		91.07 247	89.43 266	96.01 150	92.48 367	91.23 141	99.69 48	97.34 185	84.50 351	92.49 206	92.98 343	84.53 167	97.72 284	91.87 219	68.97 437	99.08 139

0.4-1-1-0.2		91.19 245	89.53 262	96.20 135	92.78 363	91.76 131	99.76 32	97.34 185	84.77 344	92.54 204	93.05 339	84.51 169	97.74 282	92.01 215	68.98 435	99.09 135

wanda-best-256-512		83.28 390	80.44 401	91.78 324	82.91 465	88.24 250	98.43 232	95.51 364	75.76 439	78.60 403	86.54 448	66.95 381	95.71 396	82.44 348	56.84 472	91.38 378

usedtu_dtu_shiyan2		69.89 446	65.80 451	82.15 451	69.90 492	68.09 475	93.09 433	90.63 468	58.33 481	61.56 477	79.31 479	28.96 487	89.43 474	57.76 475	52.68 485	88.92 440

usedtu_dtu_shiyan1		89.12 292	87.56 308	93.78 269	89.74 411	93.60 76	98.70 185	96.60 245	87.85 272	83.43 324	91.56 369	76.34 292	95.92 382	82.75 341	81.08 352	91.82 355

blended_shiyan8		83.22 392	80.40 404	91.71 327	82.77 471	88.01 261	98.25 262	95.49 369	75.64 442	78.68 399	86.55 446	66.76 385	95.75 392	82.50 347	56.93 471	91.36 382

E5new		92.80 198	92.19 196	94.62 229	94.34 310	87.64 271	98.08 283	95.97 306	89.15 217	92.01 215	97.08 221	76.37 290	98.08 238	93.25 193	93.46 233	98.15 233

FE-blended-shiyan7		83.27 391	80.44 401	91.78 324	82.91 465	88.24 250	98.43 232	95.51 364	75.76 439	78.60 403	86.54 448	66.93 382	95.71 396	82.44 348	56.84 472	91.38 378

E6new		92.80 198	92.19 196	94.62 229	94.31 318	87.64 271	98.08 283	95.97 306	89.15 217	92.01 215	97.10 216	76.38 288	98.08 238	93.25 193	93.45 235	98.15 233

blended_shiyan6		83.17 393	80.34 405	91.67 328	82.80 470	87.93 263	98.29 258	95.51 364	75.63 443	78.46 407	86.48 451	66.74 386	95.70 398	82.33 350	56.84 472	91.37 381

usedtu_blend_shiyan5		82.04 400	78.78 413	91.80 319	82.91 465	88.24 250	94.33 415	92.37 447	66.55 476	78.60 403	86.54 448	66.93 382	95.77 390	83.97 326	56.84 472	91.38 378

blend_shiyan4		86.02 351	84.08 366	91.83 316	83.24 463	88.24 250	98.42 235	95.51 364	75.55 445	79.43 391	86.84 445	84.51 169	95.77 390	83.97 326	69.26 432	91.48 371

E6		92.80 198	92.19 196	94.62 229	94.31 318	87.64 271	98.08 283	95.97 306	89.15 217	92.01 215	97.10 216	76.38 288	98.08 238	93.25 193	93.45 235	98.15 233

E5		92.80 198	92.19 196	94.62 229	94.34 310	87.64 271	98.08 283	95.97 306	89.15 217	92.01 215	97.08 221	76.37 290	98.08 238	93.25 193	93.46 233	98.15 233

FE-MVSNET3		89.12 292	87.56 308	93.78 269	89.74 411	93.60 76	98.70 185	96.60 245	87.85 272	83.43 324	91.56 369	76.34 292	95.92 382	82.75 341	81.08 352	91.82 355

E4		93.15 191	92.50 188	95.09 205	94.41 307	88.61 242	98.48 227	95.99 303	89.40 211	92.22 212	97.13 213	77.43 279	98.10 234	93.58 182	93.90 224	98.56 200

E3new		94.19 146	93.78 148	95.43 182	95.81 228	89.44 209	98.80 170	96.11 291	90.24 173	93.85 172	97.75 165	80.94 239	98.14 227	95.00 148	95.48 197	98.72 185

FE-MVSNET2		78.42 424	75.71 427	86.55 420	78.55 481	81.99 393	95.40 401	93.86 429	81.11 406	66.27 469	81.89 468	49.29 465	91.80 460	72.03 429	63.02 454	85.86 463

fmvsm_s_conf0.5_n_11		96.80 41	96.97 29	96.28 130	98.09 113	92.26 118	99.87 6	96.49 260	97.55 4	99.75 3	99.32 28	83.20 190	99.91 56	99.57 13	98.88 99	96.67 289

E2		93.62 168	93.07 167	95.26 195	95.00 281	88.99 226	98.63 198	96.09 297	89.84 188	93.02 190	97.36 193	78.88 258	98.11 232	94.23 169	94.60 210	98.67 192

MED-MVS test				97.84 36	99.75 8	93.67 72	99.65 52	98.11 47	92.89 98	98.58 48	99.53 8		100.00 1	99.53 19	99.64 42	99.87 31

MED-MVS		97.89 8	97.91 10	97.84 36	99.75 8	93.67 72	99.65 52	98.11 47	92.38 113	98.58 48	99.53 8	93.98 18	100.00 1	99.53 19	99.64 42	99.87 31

E3		93.62 168	93.07 167	95.26 195	94.98 283	89.00 225	98.63 198	96.09 297	89.83 189	93.01 192	97.35 195	78.90 257	98.11 232	94.23 169	94.60 210	98.67 192

TestfortrainingZip a		97.86 9	97.55 15	98.78 9	99.75 8	96.39 15	99.65 52	98.11 47	92.89 98	98.58 48	99.53 8	93.98 18	100.00 1	95.87 124	99.64 42	99.95 16

TestfortrainingZip				99.33 5	99.87 2	97.98 5	99.65 52	98.06 53	92.29 115	99.91 1	99.64 2	95.49 8	100.00 1		98.29 133	100.00 1

fmvsm_s_conf0.5_n_10		96.95 35	96.82 40	97.33 62	97.76 124	93.00 96	99.87 6	97.95 63	97.32 9	99.71 4	99.20 41	81.48 229	99.90 61	99.32 23	98.78 109	99.09 135

viewdifsd2359ckpt07		92.71 203	92.19 196	94.28 245	94.96 285	86.26 311	98.29 258	95.80 337	88.71 239	90.81 239	97.34 196	76.57 287	98.19 223	93.16 198	94.05 221	98.39 212

viewdifsd2359ckpt09		93.54 171	92.91 176	95.44 181	95.57 238	89.48 207	98.68 189	95.66 356	89.52 205	92.50 205	97.75 165	78.46 270	98.03 251	93.32 190	94.69 209	98.81 168

viewdifsd2359ckpt13		93.45 173	92.86 178	95.21 198	95.45 245	88.91 234	98.59 210	95.92 320	89.39 212	92.67 202	97.33 197	78.02 275	98.03 251	93.27 192	95.12 204	98.69 189

viewcassd2359sk11		93.95 153	93.48 155	95.36 185	95.48 244	89.25 212	98.74 178	96.10 292	90.10 180	93.48 181	97.55 181	80.05 244	98.14 227	94.66 158	95.16 202	98.69 189

viewdifsd2359ckpt11		90.42 266	89.65 257	92.73 298	93.71 342	82.67 384	98.09 280	95.27 384	89.80 192	90.10 258	97.40 190	69.43 358	98.18 225	92.46 209	80.61 357	97.34 264

viewmacassd2359aftdt		93.16 189	92.44 190	95.31 191	94.34 310	89.19 214	98.40 241	95.84 335	89.62 199	92.87 196	97.31 198	76.07 294	98.00 255	92.93 202	94.58 212	98.75 178

viewmsd2359difaftdt		90.43 265	89.65 257	92.74 296	93.72 341	82.67 384	98.09 280	95.27 384	89.80 192	90.12 257	97.40 190	69.43 358	98.20 222	92.45 210	80.62 356	97.34 264

diffmvs_AUTHOR		94.30 142	93.92 140	95.45 179	94.77 295	89.92 191	98.55 218	95.68 352	91.33 138	95.83 131	97.64 175	79.58 248	98.05 248	96.19 111	95.66 193	98.37 216

FE-MVSNET		75.08 438	72.25 442	83.56 445	77.93 483	76.96 441	94.36 414	87.96 483	75.72 441	66.01 471	81.60 470	50.48 460	88.85 477	55.38 478	60.82 462	84.86 474

fmvsm_l_conf0.5_n_9		97.33 22	97.32 25	97.37 60	97.64 130	92.45 114	99.93 1	97.85 72	97.39 6	99.84 2	99.09 69	85.42 152	99.92 49	99.52 22	99.20 82	99.73 58

mamba_0408		90.65 260	89.16 273	95.12 203	95.12 267	89.81 196	83.02 483	95.17 396	85.95 321	89.50 269	96.85 242	75.85 297	97.82 266	87.19 273	93.79 226	97.73 248

icg_test_0407_2		91.56 233	90.90 236	93.54 275	94.61 301	86.22 314	95.72 398	95.72 344	88.78 233	89.76 264	96.93 234	77.24 282	95.65 400	86.73 285	92.59 248	98.74 179

SSM_04072		90.31 270	89.16 273	93.74 272	95.12 267	89.81 196	83.02 483	95.17 396	85.95 321	89.50 269	96.85 242	75.85 297	93.69 437	87.19 273	93.79 226	97.73 248

SSM_0407		92.04 226	91.03 231	95.07 207	95.12 267	89.81 196	97.18 342	95.49 369	86.17 316	89.50 269	97.13 213	75.65 301	97.68 285	89.26 254	93.79 226	97.73 248

viewmambaseed2359dif		93.05 195	92.64 183	94.25 248	94.94 287	86.53 301	98.38 248	95.69 351	87.03 293	93.38 183	97.74 168	78.79 264	98.08 238	93.49 186	94.35 217	98.15 233

IMVS_0407		91.79 229	90.98 232	94.24 250	94.61 301	86.22 314	96.45 369	95.72 344	88.78 233	89.76 264	96.93 234	77.24 282	97.77 272	86.73 285	92.59 248	98.74 179

viewmanbaseed2359cas		93.90 156	93.34 160	95.56 177	95.39 250	89.72 200	98.58 213	96.00 302	90.32 171	93.58 179	97.78 162	78.71 266	98.07 243	94.43 163	95.29 199	98.88 159

IMVS_0404		89.79 283	88.57 292	93.47 277	94.61 301	86.22 314	94.45 412	95.72 344	88.78 233	81.88 359	96.93 234	65.39 399	95.47 406	86.73 285	92.59 248	98.74 179

SSM_0404		92.33 214	91.33 222	95.33 190	95.35 253	90.54 167	97.45 326	95.49 369	86.17 316	90.26 254	97.13 213	75.65 301	97.82 266	89.26 254	95.26 200	97.63 256

IMVS_0403		91.93 227	91.13 227	94.34 242	94.61 301	86.22 314	96.70 362	95.72 344	88.78 233	90.00 261	96.93 234	78.07 274	98.07 243	86.73 285	92.59 248	98.74 179

SD_0403		86.82 337	87.08 318	86.04 426	93.55 345	69.09 472	94.11 422	95.02 398	87.84 274	80.48 376	95.86 282	73.05 327	91.04 464	72.53 426	91.26 286	97.99 243

fmvsm_s_conf0.5_n_9		96.76 45	96.92 31	96.29 129	97.95 118	89.21 213	99.81 20	97.55 144	97.04 14	99.68 5	99.22 37	82.84 199	99.94 40	99.56 15	98.61 117	99.71 60

ME-MVS		97.59 17	97.51 17	97.84 36	99.73 11	93.67 72	99.52 72	98.07 51	92.38 113	98.32 59	99.53 8	90.83 48	99.97 25	99.53 19	99.64 42	99.87 31

NormalMVS		95.87 82	95.83 78	95.99 152	99.27 62	90.37 170	99.14 130	96.39 264	94.92 45	96.30 117	97.98 155	85.33 155	99.23 160	94.35 164	98.82 102	98.37 216

lecture		96.67 47	96.77 43	96.39 121	99.27 62	89.71 201	99.65 52	98.62 22	92.28 116	98.62 44	99.07 70	86.74 119	99.79 103	97.83 77	98.82 102	99.66 71

SymmetryMVS		95.49 99	95.27 99	96.17 139	97.13 166	90.37 170	99.14 130	98.59 23	94.92 45	96.30 117	97.98 155	85.33 155	99.23 160	94.35 164	93.67 231	98.92 156

Elysia		90.62 262	88.95 279	95.64 170	93.08 357	91.94 123	97.65 318	96.39 264	84.72 346	90.59 245	95.95 278	62.22 413	98.23 219	83.69 331	96.23 181	96.74 285

StellarMVS		90.62 262	88.95 279	95.64 170	93.08 357	91.94 123	97.65 318	96.39 264	84.72 346	90.59 245	95.95 278	62.22 413	98.23 219	83.69 331	96.23 181	96.74 285

KinetiMVS		93.07 194	91.98 206	96.34 125	94.84 292	91.78 128	98.73 181	97.18 202	91.25 141	94.01 168	97.09 220	71.02 347	98.86 181	86.77 284	96.89 166	98.37 216

LuminaMVS		93.16 189	92.30 192	95.76 163	92.26 371	92.64 109	97.60 323	96.21 279	90.30 172	93.06 189	95.59 286	76.00 295	97.89 260	94.93 152	94.70 208	96.76 284

VortexMVS		90.18 275	89.28 270	92.89 291	95.58 237	90.94 157	97.82 301	95.94 315	90.90 148	82.11 354	91.48 372	78.75 265	96.08 372	91.99 216	78.97 365	91.65 360

AstraMVS		93.38 179	93.01 172	94.50 234	93.94 330	86.55 300	98.91 160	95.86 333	93.88 70	92.88 195	97.49 184	75.61 304	98.21 221	96.15 114	92.39 254	98.73 184

guyue		94.21 145	93.72 150	95.66 169	95.22 257	90.17 179	98.74 178	96.85 229	93.67 77	93.01 192	96.72 252	78.83 262	98.06 245	96.04 119	94.44 214	98.77 175

sc_t1		78.53 422	74.87 433	89.48 386	87.92 437	77.36 438	94.80 409	90.61 470	57.65 482	76.28 417	89.59 420	38.25 479	96.18 366	74.04 414	64.72 452	94.91 319

tt0320-xc		75.92 434	72.23 443	87.01 415	88.40 430	78.15 430	93.57 429	89.15 479	55.46 483	69.66 454	85.79 455	38.20 480	93.85 435	69.72 437	60.08 465	89.03 437

tt0320		76.58 431	73.16 439	86.86 418	88.03 436	77.60 436	93.55 430	90.63 468	55.37 484	70.93 448	84.98 456	41.57 474	94.01 434	69.02 442	64.32 453	88.97 438

fmvsm_s_conf0.5_n_8		97.06 33	96.94 30	97.44 53	97.78 123	92.77 105	99.83 15	97.83 78	97.58 3	99.25 19	99.20 41	82.71 205	99.92 49	99.64 8	98.61 117	99.64 76

fmvsm_s_conf0.5_n_7		95.87 82	96.25 61	94.72 223	96.19 211	87.74 266	99.66 50	97.94 65	95.78 31	98.44 53	99.23 35	81.26 235	99.90 61	99.17 33	98.57 121	96.52 297

fmvsm_s_conf0.5_n_6		96.78 43	96.64 48	97.20 70	96.03 221	93.20 89	99.82 19	97.68 109	95.20 42	99.61 6	99.11 67	84.52 168	99.90 61	99.04 38	98.77 110	98.50 204

fmvsm_s_conf0.5_n_5		96.46 59	96.23 62	97.15 73	96.42 196	92.80 103	99.83 15	97.39 177	94.50 52	98.71 39	99.13 60	82.52 208	99.90 61	99.24 30	98.38 128	98.74 179

fmvsm_s_conf0.5_n_4		96.17 68	96.49 52	95.21 198	97.06 171	89.26 211	99.76 32	98.07 51	95.99 28	99.35 15	99.22 37	82.19 219	99.89 69	99.06 37	97.68 145	96.49 298

SSC-MVS3.2		85.22 365	83.90 370	89.17 391	91.87 382	79.84 415	97.66 317	96.63 242	86.81 302	81.99 356	91.35 375	55.80 435	96.00 375	76.52 396	76.53 382	91.67 359

testing3-2		95.17 110	94.78 113	96.33 127	97.35 149	92.35 115	99.85 12	98.43 28	90.60 159	92.84 197	97.00 228	90.89 45	98.89 180	95.95 122	90.12 296	97.76 246

myMVS_eth3d28		95.74 93	95.34 96	96.92 86	97.41 144	93.58 78	99.28 108	97.70 103	90.97 147	93.91 170	97.25 203	90.59 52	98.75 190	96.85 97	94.14 219	98.44 207

UWE-MVS-28		90.99 251	91.93 209	88.15 402	95.12 267	77.87 435	97.18 342	97.79 87	88.72 238	88.69 277	96.52 257	86.54 128	90.75 465	84.64 313	92.16 265	95.83 311

fmvsm_l_conf0.5_n_3		97.12 29	96.89 34	97.79 44	97.39 146	93.84 70	99.87 6	97.70 103	97.34 8	99.39 13	99.20 41	82.86 197	99.94 40	99.21 31	99.07 85	99.58 86

fmvsm_s_conf0.5_n_3		96.58 54	96.55 50	96.66 104	97.23 156	92.59 111	99.81 20	97.82 79	97.35 7	99.42 10	99.16 51	80.27 242	99.93 46	99.26 26	98.60 119	97.45 261

fmvsm_s_conf0.5_n_2		95.85 84	95.83 78	95.91 157	97.19 160	91.79 127	99.78 28	97.65 122	97.23 10	99.22 22	99.06 73	75.93 296	99.90 61	99.30 24	97.09 162	96.02 308

fmvsm_s_conf0.1_n_2		95.24 109	95.04 109	95.83 160	95.60 236	91.71 133	99.65 52	96.18 285	96.99 15	98.79 37	98.91 96	73.91 319	99.87 75	99.00 40	96.30 178	95.91 310

GDP-MVS		96.05 72	95.63 92	97.31 63	95.37 252	94.65 52	99.36 99	96.42 262	92.14 121	97.07 92	98.53 127	93.33 22	98.50 202	91.76 221	96.66 171	98.78 173

BP-MVS1		96.59 52	96.36 58	97.29 64	95.05 278	94.72 49	99.44 85	97.45 166	92.71 102	96.41 115	98.50 131	94.11 17	98.50 202	95.61 132	97.97 137	98.66 197

reproduce_monomvs		92.11 223	91.82 212	92.98 287	98.25 105	90.55 166	98.38 248	97.93 66	94.81 47	80.46 377	92.37 350	96.46 3	97.17 311	94.06 171	73.61 406	91.23 390

mmtdpeth		83.69 386	82.59 385	86.99 416	92.82 362	76.98 440	96.16 383	91.63 459	82.89 384	92.41 209	82.90 462	54.95 443	98.19 223	96.27 109	53.27 482	85.81 464

reproduce_model		96.57 55	96.75 44	96.02 148	98.93 87	88.46 248	98.56 215	97.34 185	93.18 89	96.96 95	99.35 26	88.69 80	99.80 99	98.53 54	99.21 81	99.79 43

reproduce-ours		96.66 48	96.80 41	96.22 132	98.95 84	89.03 222	98.62 201	97.38 178	93.42 83	96.80 105	99.36 24	88.92 75	99.80 99	98.51 55	99.26 75	99.82 37

our_new_method		96.66 48	96.80 41	96.22 132	98.95 84	89.03 222	98.62 201	97.38 178	93.42 83	96.80 105	99.36 24	88.92 75	99.80 99	98.51 55	99.26 75	99.82 37

mmdepth		0.00 470	0.00 473	0.00 485	0.00 508	0.00 510	0.00 496	0.00 509	0.00 503	0.00 504	0.00 503	0.00 507	0.00 504	0.00 502	0.00 502	0.00 500

monomultidepth		0.00 470	0.00 473	0.00 485	0.00 508	0.00 510	0.00 496	0.00 509	0.00 503	0.00 504	0.00 503	0.00 507	0.00 504	0.00 502	0.00 502	0.00 500

mvs5depth		78.17 425	75.56 428	85.97 427	80.43 477	76.44 443	85.46 472	89.24 478	76.39 434	78.17 412	88.26 428	51.73 454	95.73 394	69.31 440	61.09 461	85.73 465

MVStest1		76.56 432	73.43 437	85.96 428	86.30 452	80.88 410	94.26 418	91.74 457	61.98 480	58.53 480	89.96 414	69.30 360	91.47 463	59.26 471	49.56 489	85.52 467

ttmdpeth		79.80 414	77.91 416	85.47 432	83.34 462	75.75 445	95.32 403	91.45 463	76.84 432	74.81 429	91.71 365	53.98 448	94.13 433	72.42 427	61.29 460	86.51 459

WBMVS		91.35 239	90.49 246	93.94 263	96.97 175	93.40 85	99.27 110	96.71 237	87.40 288	83.10 332	91.76 364	92.38 32	96.23 364	88.95 259	77.89 371	92.17 346

dongtai		81.36 405	80.61 397	83.62 444	94.25 321	73.32 457	95.15 406	96.81 231	73.56 454	69.79 452	92.81 345	81.00 237	86.80 483	52.08 483	70.06 431	90.75 405

kuosan		84.40 379	83.34 373	87.60 408	95.87 225	79.21 419	92.39 442	96.87 228	76.12 437	73.79 434	93.98 314	81.51 227	90.63 466	64.13 458	75.42 386	92.95 327

MVSMamba_PlusPlus		95.73 94	95.15 103	97.44 53	97.28 155	94.35 61	98.26 260	96.75 236	83.09 375	97.84 75	95.97 277	89.59 68	98.48 207	97.86 74	99.73 31	99.49 96

MGCFI-Net		94.89 118	93.84 145	98.06 31	97.49 142	95.55 23	98.64 196	96.10 292	91.60 130	95.75 133	98.46 140	79.31 255	98.98 177	95.95 122	91.24 287	99.65 75

testing91		94.88 120	94.44 119	96.21 134	97.19 160	91.90 126	99.23 113	97.66 115	89.91 186	93.66 177	97.05 226	90.21 61	98.50 202	93.52 183	91.53 279	98.25 224

testing11		95.33 105	94.98 111	96.37 123	97.20 158	92.31 116	99.29 105	97.68 109	90.59 160	94.43 156	97.20 207	90.79 50	98.60 199	95.25 141	92.38 255	98.18 231

testing99		94.88 120	94.45 118	96.17 139	97.20 158	91.91 125	99.20 115	97.66 115	89.95 185	93.68 176	97.06 224	90.28 60	98.50 202	93.52 183	91.54 276	98.12 238

UBG		95.73 94	95.41 94	96.69 101	96.97 175	93.23 87	99.13 135	97.79 87	91.28 140	94.38 160	96.78 248	92.37 33	98.56 201	96.17 113	93.84 225	98.26 223

UWE-MVS		93.18 186	93.40 158	92.50 303	96.56 188	83.55 370	98.09 280	97.84 74	89.50 206	91.72 222	96.23 268	91.08 40	96.70 331	86.28 292	93.33 237	97.26 269

ETVMVS		94.50 137	93.90 143	96.31 128	97.48 143	92.98 97	99.07 141	97.86 71	88.09 263	94.40 158	96.90 238	88.35 84	97.28 309	90.72 234	92.25 261	98.66 197

sasdasda		95.02 115	93.96 137	98.20 23	97.53 139	95.92 19	98.71 182	96.19 283	91.78 125	95.86 128	98.49 134	79.53 251	99.03 173	96.12 115	91.42 282	99.66 71

testing222		94.48 138	94.00 133	95.95 155	97.30 152	92.27 117	98.82 167	97.92 67	89.20 214	94.82 149	97.26 201	87.13 109	97.32 308	91.95 217	91.56 274	98.25 224

WB-MVSnew		88.69 308	88.34 296	89.77 376	94.30 320	85.99 329	98.14 271	97.31 189	87.15 292	87.85 284	96.07 274	69.91 351	95.52 404	72.83 424	91.47 280	87.80 449

fmvsm_l_conf0.5_n_a		97.70 15	97.80 12	97.42 56	97.59 135	92.91 101	99.86 9	98.04 57	96.70 19	99.58 8	99.26 30	90.90 44	99.94 40	99.57 13	98.66 115	99.40 104

fmvsm_l_conf0.5_n		97.65 16	97.72 13	97.41 57	97.51 141	92.78 104	99.85 12	98.05 55	96.78 17	99.60 7	99.23 35	90.42 56	99.92 49	99.55 16	98.50 124	99.55 87

fmvsm_s_conf0.1_n_a		95.16 111	95.15 103	95.18 201	92.06 376	88.94 230	99.29 105	97.53 149	94.46 54	98.98 29	98.99 81	79.99 245	99.85 85	98.24 68	96.86 167	96.73 287

fmvsm_s_conf0.1_n		95.56 98	95.68 87	95.20 200	94.35 309	89.10 218	99.50 74	97.67 114	94.76 49	98.68 42	99.03 77	81.13 236	99.86 81	98.63 49	97.36 155	96.63 290

fmvsm_s_conf0.5_n_a		95.97 76	96.19 63	95.31 191	96.51 192	89.01 224	99.81 20	98.39 29	95.46 39	99.19 24	99.16 51	81.44 232	99.91 56	98.83 44	96.97 163	97.01 279

fmvsm_s_conf0.5_n		96.19 67	96.49 52	95.30 193	97.37 148	89.16 216	99.86 9	98.47 26	95.68 34	98.87 33	99.15 55	82.44 215	99.92 49	99.14 34	97.43 153	96.83 283

MM		97.76 13	97.39 23	98.86 6	98.30 104	96.83 8	99.81 20	99.13 9	97.66 2	98.29 60	98.96 88	85.84 143	99.90 61	99.72 3	98.80 105	99.85 35

WAC-MVS						79.74 416								67.75 447

Syy-MVS		84.10 384	84.53 360	82.83 448	95.14 265	65.71 477	97.68 314	96.66 240	86.52 310	82.63 337	96.84 245	68.15 368	89.89 470	45.62 486	91.54 276	92.87 328

test_fmvsmconf0.1_n		95.94 79	95.79 84	96.40 120	92.42 369	89.92 191	99.79 27	96.85 229	96.53 24	97.22 87	98.67 119	82.71 205	99.84 87	98.92 43	98.98 91	99.43 103

test_fmvsmconf0.01_n		94.14 147	93.51 154	96.04 146	86.79 448	89.19 214	99.28 108	95.94 315	95.70 32	95.50 138	98.49 134	73.27 325	99.79 103	98.28 66	98.32 132	99.15 127

myMVS_eth3d		88.68 310	89.07 276	87.50 410	95.14 265	79.74 416	97.68 314	96.66 240	86.52 310	82.63 337	96.84 245	85.22 159	89.89 470	69.43 439	91.54 276	92.87 328

testing3		87.75 322	88.22 299	86.36 422	94.66 299	77.41 437	99.52 72	97.95 63	86.05 319	81.12 369	96.69 254	86.18 137	89.31 475	61.65 466	90.12 296	92.35 339

SSC-MVS		65.42 449	65.20 452	66.06 471	73.96 486	43.83 498	92.08 444	83.54 492	69.77 465	54.73 483	80.92 474	63.30 409	79.92 493	20.48 496	48.02 490	74.44 484

test_fmvsmconf_n		96.78 43	96.84 37	96.61 106	95.99 222	90.25 174	99.90 4	98.13 45	96.68 20	98.42 54	98.92 95	85.34 154	99.88 71	99.12 35	99.08 83	99.70 62

WB-MVS		66.44 448	66.29 450	66.89 470	74.84 485	44.93 497	93.00 434	84.09 491	71.15 459	55.82 482	81.63 469	63.79 407	80.31 492	21.85 495	50.47 488	75.43 483

test_fmvsmvis_n_1920		95.47 100	95.40 95	95.70 166	94.33 313	90.22 177	99.70 41	96.98 224	96.80 16	92.75 198	98.89 100	82.46 214	99.92 49	98.36 61	98.33 130	96.97 280

dmvs_re		88.69 308	88.06 302	90.59 351	93.83 337	78.68 425	95.75 397	96.18 285	87.99 267	84.48 316	96.32 266	67.52 375	96.94 322	84.98 308	85.49 321	96.14 305

SDMVSNet		91.09 246	89.91 253	94.65 225	96.80 181	90.54 167	97.78 304	97.81 83	88.34 254	85.73 303	95.26 296	66.44 390	98.26 216	94.25 168	86.75 309	95.14 314

dmvs_testset		77.17 430	78.99 412	71.71 465	87.25 444	38.55 502	91.44 452	81.76 493	85.77 325	69.49 455	95.94 280	69.71 355	84.37 485	52.71 482	76.82 381	92.21 344

sd_testset		89.23 290	88.05 303	92.74 296	96.80 181	85.33 343	95.85 394	97.03 219	88.34 254	85.73 303	95.26 296	61.12 420	97.76 278	85.61 301	86.75 309	95.14 314

test_fmvsm_n_1920		97.08 32	97.55 15	95.67 168	97.94 119	89.61 205	99.93 1	98.48 25	97.08 12	99.08 25	99.13 60	88.17 87	99.93 46	99.11 36	99.06 86	97.47 260

test_cas_vis1_n_1920		93.86 159	93.74 149	94.22 251	95.39 250	86.08 324	99.73 37	96.07 299	96.38 26	97.19 90	97.78 162	65.46 398	99.86 81	96.71 98	98.92 96	96.73 287

test_vis1_n_1920		93.08 193	93.42 157	92.04 313	96.31 203	79.36 418	99.83 15	96.06 300	96.72 18	98.53 51	98.10 153	58.57 427	99.91 56	97.86 74	98.79 108	96.85 282

test_vis1_n		90.40 267	90.27 249	90.79 347	91.55 388	76.48 442	99.12 137	94.44 415	94.31 57	97.34 85	96.95 231	43.60 472	99.42 145	97.57 80	97.60 146	96.47 299

test_fmvs1_n		91.07 247	91.41 221	90.06 366	94.10 322	74.31 452	99.18 118	94.84 403	94.81 47	96.37 116	97.46 186	50.86 459	99.82 94	97.14 88	97.90 138	96.04 307

mvsany_test1		94.57 135	95.09 107	92.98 287	95.84 227	82.07 392	98.76 177	95.24 389	92.87 101	96.45 113	98.71 116	84.81 164	99.15 165	97.68 78	95.49 196	97.73 248

APD_test1		68.93 447	66.98 449	74.77 463	80.62 476	53.15 490	87.97 466	85.01 488	53.76 486	59.26 479	87.52 435	25.19 488	89.95 469	56.20 476	67.33 444	81.19 481

test_vis1_rt		81.31 406	80.05 408	85.11 433	91.29 393	70.66 467	98.98 154	77.39 497	85.76 326	68.80 457	82.40 465	36.56 482	99.44 141	92.67 207	86.55 311	85.24 471

test_vis3_rt		61.29 451	58.75 454	68.92 469	67.41 493	52.84 491	91.18 457	59.23 504	66.96 473	41.96 492	58.44 492	11.37 499	94.72 426	74.25 411	57.97 469	59.20 491

test_fmvs2		85.10 367	85.45 343	84.02 441	89.85 409	65.63 478	98.49 225	92.59 444	90.45 166	85.43 309	93.32 330	43.94 470	96.59 335	90.81 231	84.19 330	89.85 426

test_fmvs1		92.35 213	92.94 175	90.57 352	97.19 160	75.43 448	99.55 66	94.97 399	95.20 42	96.82 103	97.57 180	59.59 425	99.84 87	97.30 85	98.29 133	96.46 300

test_fmvs3		75.09 437	75.19 430	74.81 462	77.45 484	54.08 488	95.93 387	90.64 467	82.51 390	73.29 438	81.19 472	22.29 490	86.29 484	85.50 302	67.89 441	84.06 475

mvsany_test3		75.85 436	74.52 435	79.83 457	73.53 488	60.64 482	91.73 448	87.87 484	83.91 361	70.55 450	82.52 464	31.12 484	93.66 438	86.66 289	62.83 455	85.19 472

testf1		56.38 455	53.73 458	64.31 474	64.84 494	45.11 495	80.50 487	75.94 499	38.87 489	42.74 489	75.07 482	11.26 500	81.19 488	41.11 488	53.27 482	66.63 488

APD_test2		56.38 455	53.73 458	64.31 474	64.84 494	45.11 495	80.50 487	75.94 499	38.87 489	42.74 489	75.07 482	11.26 500	81.19 488	41.11 488	53.27 482	66.63 488

test_f		71.94 443	70.82 444	75.30 461	72.77 489	53.28 489	91.62 449	89.66 476	75.44 446	64.47 473	78.31 481	20.48 491	89.56 473	78.63 381	66.02 448	83.05 480

FE-MVS		91.38 238	90.16 251	95.05 210	96.46 194	87.53 279	89.69 464	97.84 74	82.97 378	92.18 213	92.00 358	84.07 176	98.93 179	80.71 365	95.52 195	98.68 191

FA-MVS(test-final)		92.22 220	91.08 229	95.64 170	96.05 220	88.98 227	91.60 450	97.25 191	86.99 294	91.84 219	92.12 352	83.03 194	99.00 175	86.91 280	93.91 223	98.93 154

balanced_conf03		96.83 39	96.51 51	97.81 41	97.60 134	95.15 36	98.40 241	96.77 235	93.00 93	98.69 41	96.19 269	89.75 66	98.76 189	98.45 59	99.72 32	99.51 93

MonoMVSNet		90.69 258	89.78 255	93.45 278	91.78 384	84.97 352	96.51 367	94.44 415	90.56 162	85.96 302	90.97 383	78.61 269	96.27 363	95.35 137	83.79 336	99.11 133

patch_mono-2		97.10 31	97.97 8	94.49 235	99.21 68	83.73 368	99.62 60	98.25 34	95.28 41	99.38 14	98.91 96	92.28 34	99.94 40	99.61 11	99.22 78	99.78 46

EGC-MVSNET		60.70 452	55.37 456	76.72 459	86.35 451	71.08 464	89.96 463	84.44 490	0.38 502	1.50 503	84.09 460	37.30 481	88.10 480	40.85 490	73.44 411	70.97 487

test2506		94.80 124	94.21 125	96.58 109	96.41 198	92.18 120	98.01 291	98.96 11	90.82 152	93.46 182	97.28 199	85.92 140	98.45 208	89.82 242	97.19 158	99.12 131

test1111		92.12 221	91.19 226	94.94 213	96.15 213	87.36 285	98.12 274	94.84 403	90.85 151	90.97 237	97.26 201	65.60 396	98.37 210	89.74 245	97.14 161	99.07 142

ECVR-MVS		92.29 216	91.33 222	95.15 202	96.41 198	87.84 264	98.10 277	94.84 403	90.82 152	91.42 232	97.28 199	65.61 395	98.49 206	90.33 236	97.19 158	99.12 131

test_blank		0.00 470	0.00 473	0.00 485	0.00 508	0.00 510	0.00 496	0.00 509	0.00 503	0.00 504	0.00 503	0.00 507	0.00 504	0.00 502	0.00 502	0.00 500

tt0805		86.50 345	84.79 354	91.63 329	91.97 377	81.49 397	96.49 368	97.38 178	82.24 394	82.44 342	95.82 283	51.22 456	98.25 217	84.55 315	80.96 355	95.13 316

DVP-MVS++		98.18 2	98.09 5	98.44 18	99.61 29	95.38 26	99.55 66	97.68 109	93.01 91	99.23 20	99.45 19	95.12 9	99.98 13	99.25 28	99.92 3	99.97 8

FOURS1					99.50 47	88.94 230	99.55 66	97.47 163	91.32 139	98.12 65

MSC_two_6792asdad				99.51 2	99.61 29	98.60 2		97.69 107					99.98 13	99.55 16	99.83 15	99.96 11

PC_three_1452									94.60 51	99.41 11	99.12 63	95.50 7	99.96 33	99.84 2	99.92 3	99.97 8

No_MVS				99.51 2	99.61 29	98.60 2		97.69 107					99.98 13	99.55 16	99.83 15	99.96 11

test_one_0601					99.59 33	94.89 39		97.64 124	93.14 90	98.93 32	99.45 19	93.45 21

eth-test2					0.00 508

eth-test					0.00 508

GeoE		90.60 264	89.56 261	93.72 274	95.10 275	85.43 340	99.41 92	94.94 401	83.96 360	87.21 292	96.83 247	74.37 313	97.05 318	80.50 369	93.73 230	98.67 192

test_method		70.10 445	68.66 448	74.41 464	86.30 452	55.84 486	94.47 411	89.82 474	35.18 493	66.15 470	84.75 459	30.54 485	77.96 494	70.40 436	60.33 464	89.44 432

Anonymous20240521		78.63 421	76.90 422	83.82 442	82.82 468	72.86 459	95.72 398	93.57 435	73.55 455	72.17 447	84.79 458	49.69 463	92.51 452	65.29 456	74.50 395	86.09 462

h-mvs33		92.47 212	91.95 208	94.05 259	97.13 166	85.01 350	98.36 250	98.08 50	93.85 72	96.27 119	96.73 251	83.19 191	99.43 144	95.81 125	68.09 439	97.70 252

hse-mvs2		91.67 232	91.51 219	92.15 310	96.22 207	82.61 388	97.74 310	97.53 149	93.85 72	96.27 119	96.15 270	83.19 191	97.44 302	95.81 125	66.86 446	96.40 302

CL-MVSNet_self_test		79.89 413	78.34 414	84.54 439	81.56 473	75.01 449	96.88 353	95.62 357	81.10 407	75.86 423	85.81 454	68.49 365	90.26 468	63.21 461	56.51 477	88.35 444

KD-MVS_2432*1600		82.98 395	80.52 399	90.38 359	94.32 314	88.98 227	92.87 437	95.87 331	80.46 414	73.79 434	87.49 436	82.76 203	93.29 442	70.56 434	46.53 491	88.87 442

KD-MVS_self_test		77.47 429	75.88 426	82.24 449	81.59 472	68.93 473	92.83 439	94.02 427	77.03 430	73.14 440	83.39 461	55.44 440	90.42 467	67.95 446	57.53 470	87.38 451

AUN-MVS		90.17 276	89.50 263	92.19 308	96.21 208	82.67 384	97.76 309	97.53 149	88.05 264	91.67 223	96.15 270	83.10 193	97.47 299	88.11 266	66.91 445	96.43 301

ZD-MVS					99.67 15	93.28 86		97.61 131	87.78 276	97.41 82	99.16 51	90.15 62	99.56 127	98.35 62	99.70 37

SR-MVS-dyc-post		95.75 91	95.86 77	95.41 184	99.22 66	87.26 291	98.40 241	97.21 197	89.63 197	96.67 110	98.97 83	86.73 121	99.36 152	96.62 101	99.31 71	99.60 82

RE-MVS-def			95.70 86		99.22 66	87.26 291	98.40 241	97.21 197	89.63 197	96.67 110	98.97 83	85.24 158		96.62 101	99.31 71	99.60 82

SED-MVS		98.18 2	98.10 4	98.41 20	99.63 23	95.24 29	99.77 29	97.72 98	94.17 59	99.30 17	99.54 4	93.32 23	99.98 13	99.70 5	99.81 23	99.99 2

IU-MVS					99.63 23	95.38 26		97.73 97	95.54 37	99.54 9				99.69 7	99.81 23	99.99 2

OPU-MVS				99.49 4	99.64 22	98.51 4	99.77 29				99.19 45	95.12 9	99.97 25	99.90 1	99.92 3	99.99 2

test_241102_TWO								97.72 98	94.17 59	99.23 20	99.54 4	93.14 28	99.98 13	99.70 5	99.82 19	99.99 2

test_241102_ONE					99.63 23	95.24 29		97.72 98	94.16 61	99.30 17	99.49 14	93.32 23	99.98 13

SF-MVS		97.22 26	96.92 31	98.12 29	99.11 73	94.88 40	99.44 85	97.45 166	89.60 200	98.70 40	99.42 22	90.42 56	99.72 111	98.47 58	99.65 40	99.77 51

cl22		89.57 287	88.79 285	91.91 314	97.94 119	87.62 275	97.98 293	96.51 255	85.03 338	82.37 346	91.79 361	83.65 179	96.50 341	85.96 296	77.89 371	91.61 366

miper_ehance_all_eth		88.94 297	88.12 301	91.40 331	95.32 254	86.93 295	97.85 300	95.55 361	84.19 355	81.97 357	91.50 371	84.16 174	95.91 385	84.69 311	77.89 371	91.36 382

miper_enhance_ethall		90.33 269	89.70 256	92.22 306	97.12 168	88.93 232	98.35 251	95.96 312	88.60 242	83.14 331	92.33 351	87.38 101	96.18 366	86.49 290	77.89 371	91.55 369

ZNCC-MVS		96.09 70	95.81 82	96.95 85	99.42 52	91.19 144	99.55 66	97.53 149	89.72 194	95.86 128	98.94 94	86.59 125	99.97 25	95.13 143	99.56 56	99.68 67

dcpmvs_2		95.67 96	96.18 65	94.12 255	98.82 92	84.22 361	97.37 331	95.45 374	90.70 154	95.77 132	98.63 123	90.47 54	98.68 196	99.20 32	99.22 78	99.45 100

cl____		87.82 319	86.79 324	90.89 344	94.88 290	85.43 340	97.81 302	95.24 389	82.91 383	80.71 373	91.22 378	81.97 223	95.84 387	81.34 360	75.06 389	91.40 377

DIV-MVS_self_test		87.82 319	86.81 323	90.87 345	94.87 291	85.39 342	97.81 302	95.22 394	82.92 382	80.76 372	91.31 377	81.99 221	95.81 389	81.36 359	75.04 390	91.42 376

eth_miper_zixun_eth		87.76 321	87.00 321	90.06 366	94.67 298	82.65 387	97.02 349	95.37 380	84.19 355	81.86 363	91.58 368	81.47 230	95.90 386	83.24 334	73.61 406	91.61 366

9.14			96.87 35		99.34 55		99.50 74	97.49 160	89.41 210	98.59 46	99.43 21	89.78 65	99.69 113	98.69 46	99.62 50

uanet_test		0.00 470	0.00 473	0.00 485	0.00 508	0.00 510	0.00 496	0.00 509	0.00 503	0.00 504	0.00 503	0.00 507	0.00 504	0.00 502	0.00 502	0.00 500

DCPMVS		0.00 470	0.00 473	0.00 485	0.00 508	0.00 510	0.00 496	0.00 509	0.00 503	0.00 504	0.00 503	0.00 507	0.00 504	0.00 502	0.00 502	0.00 500

save fliter					99.34 55	93.85 69	99.65 52	97.63 128	95.69 33

ET-MVSNet_ETH3D		92.56 210	91.45 220	95.88 158	96.39 200	94.13 65	99.46 82	96.97 225	92.18 119	66.94 466	98.29 146	94.65 15	94.28 431	94.34 166	83.82 335	99.24 120

UniMVSNet_ETH3D		85.65 362	83.79 371	91.21 335	90.41 403	80.75 411	95.36 402	95.78 338	78.76 422	81.83 364	94.33 307	49.86 462	96.66 332	84.30 317	83.52 339	96.22 304

EIA-MVS		95.11 112	95.27 99	94.64 227	96.34 202	86.51 302	99.59 62	96.62 243	92.51 105	94.08 165	98.64 121	86.05 139	98.24 218	95.07 145	98.50 124	99.18 125

miper_refine_blended		82.98 395	80.52 399	90.38 359	94.32 314	88.98 227	92.87 437	95.87 331	80.46 414	73.79 434	87.49 436	82.76 203	93.29 442	70.56 434	46.53 491	88.87 442

miper_lstm_enhance		86.90 334	86.20 331	89.00 395	94.53 305	81.19 404	96.74 360	95.24 389	82.33 393	80.15 381	90.51 403	81.99 221	94.68 427	80.71 365	73.58 408	91.12 393

ETV-MVS		96.00 73	96.00 73	96.00 151	96.56 188	91.05 152	99.63 59	96.61 244	93.26 88	97.39 83	98.30 145	86.62 124	98.13 230	98.07 70	97.57 147	98.82 167

CS-MVS		95.75 91	96.19 63	94.40 239	97.88 121	86.22 314	99.66 50	96.12 290	92.69 103	98.07 67	98.89 100	87.09 110	97.59 293	96.71 98	98.62 116	99.39 106

D2MVS		87.96 318	87.39 312	89.70 378	91.84 383	83.40 372	98.31 255	98.49 24	88.04 265	78.23 411	90.26 406	73.57 320	96.79 329	84.21 319	83.53 338	88.90 441

DVP-MVS		98.07 7	98.00 6	98.29 21	99.66 17	95.20 34	99.72 38	97.47 163	93.95 64	99.07 26	99.46 15	93.18 26	99.97 25	99.64 8	99.82 19	99.69 65
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									93.01 91	99.07 26	99.46 15	94.66 14	99.97 25	99.25 28	99.82 19	99.95 16

test_0728_SECOND				98.77 10	99.66 17	96.37 16	99.72 38	97.68 109					99.98 13	99.64 8	99.82 19	99.96 11

test0726					99.66 17	95.20 34	99.77 29	97.70 103	93.95 64	99.35 15	99.54 4	93.18 26

SR-MVS		96.13 69	96.16 70	96.07 145	99.42 52	89.04 220	98.59 210	97.33 188	90.44 167	96.84 99	99.12 63	86.75 118	99.41 148	97.47 81	99.44 64	99.76 53

DPM-MVS		97.86 9	97.25 26	99.68 1	98.25 105	99.10 1	99.76 32	97.78 90	96.61 21	98.15 62	99.53 8	93.62 20	100.00 1	91.79 220	99.80 26	99.94 20

GST-MVS		95.97 76	95.66 88	96.90 87	99.49 50	91.22 142	99.45 84	97.48 161	89.69 195	95.89 125	98.72 113	86.37 133	99.95 37	94.62 160	99.22 78	99.52 90

test_yl		95.27 107	94.60 116	97.28 66	98.53 100	92.98 97	99.05 145	98.70 18	86.76 304	94.65 154	97.74 168	87.78 94	99.44 141	95.57 133	92.61 246	99.44 101

thisisatest0530		94.00 150	93.52 153	95.43 182	95.76 231	90.02 189	98.99 152	97.60 133	86.58 307	91.74 221	97.36 193	94.78 12	98.34 211	86.37 291	92.48 253	97.94 244

Anonymous20240529		87.66 326	85.58 340	93.92 264	97.59 135	85.01 350	98.13 272	97.13 208	66.69 475	88.47 280	96.01 276	55.09 442	99.51 132	87.00 277	84.12 331	97.23 271

Anonymous202405211		88.84 300	87.03 320	94.27 246	98.14 112	84.18 362	98.44 231	95.58 360	76.79 433	89.34 273	96.88 241	53.42 450	99.54 130	87.53 272	87.12 308	99.09 135

DCV-MVSNet		95.27 107	94.60 116	97.28 66	98.53 100	92.98 97	99.05 145	98.70 18	86.76 304	94.65 154	97.74 168	87.78 94	99.44 141	95.57 133	92.61 246	99.44 101

tttt0517		93.30 182	93.01 172	94.17 253	95.57 238	86.47 304	98.51 222	97.60 133	85.99 320	90.55 247	97.19 209	94.80 11	98.31 212	85.06 306	91.86 267	97.74 247

our_test_3		84.47 377	82.80 378	89.50 383	89.01 422	83.90 366	97.03 347	94.56 413	81.33 404	75.36 427	90.52 402	71.69 342	94.54 429	68.81 443	76.84 380	90.07 420

thisisatest0515		94.75 126	94.19 126	96.43 117	96.13 218	92.64 109	99.47 78	97.60 133	87.55 285	93.17 186	97.59 178	94.71 13	98.42 209	88.28 263	93.20 238	98.24 227

ppachtmachnet_test		83.63 388	81.57 391	89.80 374	89.01 422	85.09 349	97.13 344	94.50 414	78.84 420	76.14 419	91.00 382	69.78 353	94.61 428	63.40 460	74.36 398	89.71 429

SMA-MVS		97.24 24	96.99 28	98.00 33	99.30 59	94.20 63	99.16 122	97.65 122	89.55 204	99.22 22	99.52 13	90.34 59	99.99 9	98.32 64	99.83 15	99.82 37
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																98.84 163

DPE-MVS		98.11 6	98.00 6	98.44 18	99.50 47	95.39 25	99.29 105	97.72 98	94.50 52	98.64 43	99.54 4	93.32 23	99.97 25	99.58 12	99.90 7	99.95 16
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part2					99.54 41	95.42 24				98.13 63

thres100view900		93.34 181	92.15 202	96.90 87	97.62 131	94.84 43	99.06 144	99.36 2	87.96 268	90.47 250	96.78 248	83.29 187	98.75 190	84.11 322	90.69 290	97.12 272

tfpnnormal		83.65 387	81.35 393	90.56 354	91.37 392	88.06 258	97.29 333	97.87 70	78.51 423	76.20 418	90.91 384	64.78 401	96.47 344	61.71 465	73.50 409	87.13 456

tfpn200view9		93.43 175	92.27 194	96.90 87	97.68 128	94.84 43	99.18 118	99.36 2	88.45 247	90.79 240	96.90 238	83.31 185	98.75 190	84.11 322	90.69 290	97.12 272

c3_l		88.19 317	87.23 316	91.06 338	94.97 284	86.17 321	97.72 311	95.38 379	83.43 369	81.68 365	91.37 374	82.81 200	95.72 395	84.04 325	73.70 405	91.29 387

CHOSEN 280x420		96.80 41	96.85 36	96.66 104	97.85 122	94.42 58	94.76 410	98.36 31	92.50 106	95.62 137	97.52 182	97.92 1	97.38 305	98.31 65	98.80 105	98.20 230

CANet		97.00 34	96.49 52	98.55 14	98.86 91	96.10 18	99.83 15	97.52 153	95.90 29	97.21 88	98.90 98	82.66 207	99.93 46	98.71 45	98.80 105	99.63 79

Fast-Effi-MVS+-dtu		88.84 300	88.59 291	89.58 381	93.44 350	78.18 429	98.65 194	94.62 412	88.46 246	84.12 319	95.37 294	68.91 361	96.52 340	82.06 354	91.70 272	94.06 321

Effi-MVS+-dtu		89.97 281	90.68 243	87.81 406	95.15 264	71.98 463	97.87 299	95.40 378	91.92 123	87.57 286	91.44 373	74.27 315	96.84 325	89.45 247	93.10 240	94.60 320

CANet_DTU		94.31 141	93.35 159	97.20 70	97.03 174	94.71 50	98.62 201	95.54 362	95.61 36	97.21 88	98.47 138	71.88 339	99.84 87	88.38 262	97.46 152	97.04 277

MGCNet		97.81 11	97.51 17	98.74 11	98.97 80	96.57 12	99.91 3	98.17 39	97.45 5	98.76 38	98.97 83	86.69 122	99.96 33	99.72 3	98.92 96	99.69 65

MP-MVS-pluss		95.80 87	95.30 97	97.29 64	98.95 84	92.66 106	98.59 210	97.14 206	88.95 227	93.12 187	99.25 32	85.62 144	99.94 40	96.56 105	99.48 60	99.28 117
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MSP-MVS		97.77 12	98.18 2	96.53 113	99.54 41	90.14 180	99.41 92	97.70 103	95.46 39	98.60 45	99.19 45	95.71 5	99.49 134	98.15 69	99.85 13	99.95 16
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												88.39 83				98.84 163

sam_mvs												87.08 111

IterMVS-SCA-FT		85.73 360	84.64 358	89.00 395	93.46 349	82.90 379	96.27 375	94.70 409	85.02 339	78.62 401	90.35 405	66.61 387	93.33 441	79.38 374	77.36 379	90.76 404

TSAR-MVS + MP.		97.44 21	97.46 20	97.39 59	99.12 72	93.49 83	98.52 219	97.50 158	94.46 54	98.99 28	98.64 121	91.58 36	99.08 172	98.49 57	99.83 15	99.60 82
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		94.73 127	93.98 134	96.99 79	95.19 260	95.24 29	98.62 201	96.50 256	92.99 94	97.52 79	98.83 104	72.37 334	99.15 165	97.03 89	96.74 168	96.58 293

OPM-MVS		89.76 284	89.15 275	91.57 330	90.53 401	85.58 338	98.11 276	95.93 319	92.88 100	86.05 300	96.47 261	67.06 380	97.87 263	89.29 253	86.08 317	91.26 388
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMMP_NAP		96.59 52	96.18 65	97.81 41	98.82 92	93.55 80	98.88 163	97.59 137	90.66 155	97.98 72	99.14 58	86.59 125	100.00 1	96.47 107	99.46 61	99.89 27

ambc				79.60 458	72.76 490	56.61 485	76.20 489	92.01 454		68.25 460	80.23 476	23.34 489	94.73 425	73.78 418	60.81 463	87.48 450

MTGPA								97.45 166

SPE-MVS-test		95.98 75	96.34 59	94.90 214	98.06 115	87.66 270	99.69 48	96.10 292	93.66 78	98.35 58	99.05 75	86.28 134	97.66 287	96.96 93	98.90 98	99.37 107

Effi-MVS+		93.87 158	93.15 166	96.02 148	95.79 229	90.76 160	96.70 362	95.78 338	86.98 297	95.71 134	97.17 211	79.58 248	98.01 254	94.57 161	96.09 185	99.31 114

xiu_mvs_v2_base		96.66 48	96.17 68	98.11 30	97.11 169	96.96 7	99.01 150	97.04 217	95.51 38	98.86 34	99.11 67	82.19 219	99.36 152	98.59 52	98.14 135	98.00 241

xiu_mvs_v1_base		94.73 127	93.98 134	96.99 79	95.19 260	95.24 29	98.62 201	96.50 256	92.99 94	97.52 79	98.83 104	72.37 334	99.15 165	97.03 89	96.74 168	96.58 293

new-patchmatchnet		74.80 440	72.40 441	81.99 453	78.36 482	72.20 462	94.44 413	92.36 448	77.06 429	63.47 474	79.98 477	51.04 457	88.85 477	60.53 469	54.35 480	84.92 473

pmmvs6		79.90 412	77.31 419	87.67 407	84.17 458	78.13 431	95.86 393	93.68 433	67.94 471	72.67 445	89.62 419	50.98 458	95.75 392	74.80 408	66.04 447	89.14 436

pmmvs5		85.87 354	84.40 364	90.30 362	88.53 429	84.23 360	98.60 208	93.71 432	81.53 402	80.29 379	92.02 355	64.51 402	95.52 404	82.04 355	78.34 369	91.15 392

test_post1							90.74 461				41.37 500	85.38 153	96.36 350	83.16 336

test_post											46.00 497	87.37 102	97.11 314

Fast-Effi-MVS+		91.72 231	90.79 241	94.49 235	95.89 224	87.40 284	99.54 71	95.70 349	85.01 340	89.28 274	95.68 285	77.75 277	97.57 297	83.22 335	95.06 205	98.51 203

patchmatchnet-post											84.86 457	88.73 79	96.81 327

Anonymous20231211		84.72 371	82.65 383	90.91 342	97.71 127	84.55 357	97.28 334	96.67 239	66.88 474	79.18 396	90.87 386	58.47 428	96.60 334	82.61 345	74.20 401	91.59 368

pmmvs-eth3d		78.71 420	76.16 425	86.38 421	80.25 478	81.19 404	94.17 420	92.13 452	77.97 425	66.90 467	82.31 466	55.76 436	92.56 451	73.63 419	62.31 459	85.38 468

GG-mvs-BLEND				96.98 82	96.53 190	94.81 46	87.20 467	97.74 94		93.91 170	96.40 262	96.56 2	96.94 322	95.08 144	98.95 95	99.20 124

xiu_mvs_v1_base_debi		94.73 127	93.98 134	96.99 79	95.19 260	95.24 29	98.62 201	96.50 256	92.99 94	97.52 79	98.83 104	72.37 334	99.15 165	97.03 89	96.74 168	96.58 293

Anonymous20231206		80.76 408	79.42 411	84.79 437	84.78 456	72.98 458	96.53 365	92.97 440	79.56 417	74.33 430	88.83 425	61.27 419	92.15 456	60.59 468	75.92 384	89.24 435

MTAPA		96.09 70	95.80 83	96.96 84	99.29 60	91.19 144	97.23 338	97.45 166	92.58 104	94.39 159	99.24 34	86.43 132	99.99 9	96.22 110	99.40 68	99.71 60

MTMP							99.21 114	91.09 465

gm-plane-assit					94.69 297	88.14 256			88.22 259		97.20 207		98.29 214	90.79 232

test9_res														98.60 50	99.87 9	99.90 24

MVP-Stereo		86.61 342	85.83 336	88.93 397	88.70 427	83.85 367	96.07 385	94.41 420	82.15 396	75.64 425	91.96 359	67.65 374	96.45 346	77.20 389	98.72 111	86.51 459
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST9					99.57 38	93.17 90	99.38 95	97.66 115	89.57 202	98.39 55	99.18 48	90.88 46	99.66 116

train_agg		97.20 27	97.08 27	97.57 51	99.57 38	93.17 90	99.38 95	97.66 115	90.18 176	98.39 55	99.18 48	90.94 42	99.66 116	98.58 53	99.85 13	99.88 28

gg-mvs-nofinetune		90.00 280	87.71 306	96.89 91	96.15 213	94.69 51	85.15 474	97.74 94	68.32 470	92.97 194	60.16 489	96.10 4	96.84 325	93.89 174	98.87 100	99.14 128

SCA		90.64 261	89.25 271	94.83 218	94.95 286	88.83 235	96.26 377	97.21 197	90.06 184	90.03 259	90.62 396	66.61 387	96.81 327	83.16 336	94.36 216	98.84 163

Patchmatch-test		86.25 349	84.06 367	92.82 292	94.42 306	82.88 381	82.88 485	94.23 423	71.58 457	79.39 392	90.62 396	89.00 74	96.42 347	63.03 462	91.37 284	99.16 126

test_8					99.55 40	93.07 93	99.37 98	97.64 124	90.18 176	98.36 57	99.19 45	90.94 42	99.64 122

MS-PatchMatch		86.75 338	85.92 335	89.22 389	91.97 377	82.47 389	96.91 351	96.14 289	83.74 363	77.73 413	93.53 328	58.19 429	97.37 307	76.75 393	98.35 129	87.84 447

Patchmatch-RL test		81.90 403	80.13 406	87.23 413	80.71 475	70.12 470	84.07 480	88.19 482	83.16 374	70.57 449	82.18 467	87.18 108	92.59 450	82.28 352	62.78 456	98.98 146

cdsmvs_eth3d_5k		22.52 464	30.03 467	0.00 485	0.00 508	0.00 510	0.00 496	97.17 204	0.00 503	0.00 504	98.77 107	74.35 314	0.00 504	0.00 502	0.00 502	0.00 500

pcd_1.5k_mvsjas		6.87 469	9.16 472	0.00 485	0.00 508	0.00 510	0.00 496	0.00 509	0.00 503	0.00 504	0.00 503	82.48 211	0.00 504	0.00 502	0.00 502	0.00 500

agg_prior2														97.84 76	99.87 9	99.91 23

agg_prior					99.54 41	92.66 106		97.64 124		97.98 72			99.61 124

tmp_tt		53.66 458	52.86 460	56.05 477	32.75 505	41.97 501	73.42 491	76.12 498	21.91 498	39.68 494	96.39 264	42.59 473	65.10 497	78.00 384	14.92 498	61.08 490

canonicalmvs		95.02 115	93.96 137	98.20 23	97.53 139	95.92 19	98.71 182	96.19 283	91.78 125	95.86 128	98.49 134	79.53 251	99.03 173	96.12 115	91.42 282	99.66 71

anonymousdsp		86.69 339	85.75 338	89.53 382	86.46 450	82.94 377	96.39 371	95.71 348	83.97 359	79.63 388	90.70 390	68.85 362	95.94 379	86.01 294	84.02 332	89.72 428

alignmvs		95.77 89	95.00 110	98.06 31	97.35 149	95.68 22	99.71 40	97.50 158	91.50 132	96.16 121	98.61 125	86.28 134	99.00 175	96.19 111	91.74 270	99.51 93

nrg030		90.23 272	88.87 282	94.32 244	91.53 389	93.54 81	98.79 175	95.89 329	88.12 262	84.55 314	94.61 305	78.80 263	96.88 324	92.35 212	75.21 388	92.53 334

v144192		86.40 346	84.89 351	90.91 342	89.48 418	85.59 337	98.21 266	95.43 377	82.45 391	82.62 339	90.58 399	72.79 332	96.36 350	78.45 382	74.04 404	90.79 402

FIs		90.70 257	89.87 254	93.18 283	92.29 370	91.12 147	98.17 270	98.25 34	89.11 222	83.44 323	94.82 302	82.26 217	96.17 368	87.76 269	82.76 344	92.25 340

v1921920		86.02 351	84.44 362	90.77 348	89.32 420	85.20 345	98.10 277	95.35 382	82.19 395	82.25 348	90.71 389	70.73 348	96.30 361	76.85 392	74.49 396	90.80 401

UA-Net		93.30 182	92.62 185	95.34 188	96.27 205	88.53 247	95.88 391	96.97 225	90.90 148	95.37 141	97.07 223	82.38 216	99.10 171	83.91 328	94.86 207	98.38 213

v1192		86.32 348	84.71 356	91.17 336	89.53 417	86.40 306	98.13 272	95.44 376	82.52 389	82.42 344	90.62 396	71.58 344	96.33 357	77.23 387	74.88 391	90.79 402

FC-MVSNet-test		90.22 273	89.40 267	92.67 301	91.78 384	89.86 194	97.89 296	98.22 37	88.81 232	82.96 333	94.66 304	81.90 224	95.96 378	85.89 299	82.52 347	92.20 345

v1144		86.83 336	85.31 345	91.40 331	89.75 410	87.21 293	98.31 255	95.45 374	83.22 372	82.70 336	90.78 387	73.36 321	96.36 350	79.49 372	74.69 394	90.63 410

sosnet-low-res		0.00 470	0.00 473	0.00 485	0.00 508	0.00 510	0.00 496	0.00 509	0.00 503	0.00 504	0.00 503	0.00 507	0.00 504	0.00 502	0.00 502	0.00 500

HFP-MVS		96.42 60	96.26 60	96.90 87	99.69 13	90.96 155	99.47 78	97.81 83	90.54 164	96.88 96	99.05 75	87.57 97	99.96 33	95.65 127	99.72 32	99.78 46

v148		86.38 347	85.06 347	90.37 361	89.47 419	84.10 363	98.52 219	95.48 372	83.80 362	80.93 371	90.22 410	74.60 309	96.31 358	80.92 363	71.55 426	90.69 408

sosnet		0.00 470	0.00 473	0.00 485	0.00 508	0.00 510	0.00 496	0.00 509	0.00 503	0.00 504	0.00 503	0.00 507	0.00 504	0.00 502	0.00 502	0.00 500

uncertanet		0.00 470	0.00 473	0.00 485	0.00 508	0.00 510	0.00 496	0.00 509	0.00 503	0.00 504	0.00 503	0.00 507	0.00 504	0.00 502	0.00 502	0.00 500

AllTest		84.97 369	83.12 375	90.52 355	96.82 179	78.84 423	95.89 389	92.17 450	77.96 426	75.94 421	95.50 289	55.48 438	99.18 163	71.15 430	87.14 306	93.55 324

TestCases				90.52 355	96.82 179	78.84 423		92.17 450	77.96 426	75.94 421	95.50 289	55.48 438	99.18 163	71.15 430	87.14 306	93.55 324

v7n		84.42 378	82.75 381	89.43 387	88.15 433	81.86 394	96.75 359	95.67 354	80.53 412	78.38 409	89.43 422	69.89 352	96.35 355	73.83 417	72.13 422	90.07 420

region2R		96.30 64	96.17 68	96.70 100	99.70 12	90.31 173	99.46 82	97.66 115	90.55 163	97.07 92	99.07 70	86.85 116	99.97 25	95.43 135	99.74 29	99.81 40

RRT-MVS		93.39 177	92.64 183	95.64 170	96.11 219	88.75 239	97.40 327	95.77 340	89.46 208	92.70 201	95.42 292	72.98 328	98.81 184	96.91 95	96.97 163	99.37 107

balanced_ft_v1		94.96 117	94.35 121	96.78 92	97.54 138	92.05 121	98.03 290	96.20 280	90.90 148	96.83 101	95.51 288	76.75 286	98.77 186	98.68 48	98.70 112	99.52 90

PS-MVSNAJss		89.54 288	89.05 277	91.00 340	88.77 425	84.36 359	97.39 328	95.97 306	88.47 244	81.88 359	93.80 320	82.48 211	96.50 341	89.34 250	83.34 341	92.15 347

PS-MVSNAJ		96.87 38	96.40 56	98.29 21	97.35 149	97.29 6	99.03 147	97.11 210	95.83 30	98.97 30	99.14 58	82.48 211	99.60 125	98.60 50	99.08 83	98.00 241

jajsoiax		87.35 329	86.51 327	89.87 371	87.75 442	81.74 395	97.03 347	95.98 305	88.47 244	80.15 381	93.80 320	61.47 417	96.36 350	89.44 248	84.47 328	91.50 370

mvs_tets		87.09 332	86.22 330	89.71 377	87.87 438	81.39 400	96.73 361	95.90 327	88.19 260	79.99 383	93.61 325	59.96 424	96.31 358	89.40 249	84.34 329	91.43 375

EI-MVSNet-UG-set		95.43 101	95.29 98	95.86 159	99.07 77	89.87 193	98.43 232	97.80 85	91.78 125	94.11 164	98.77 107	86.25 136	99.48 138	94.95 151	96.45 173	98.22 228

EI-MVSNet-Vis-set		95.76 90	95.63 92	96.17 139	99.14 71	90.33 172	98.49 225	97.82 79	91.92 123	94.75 151	98.88 102	87.06 112	99.48 138	95.40 136	97.17 160	98.70 188

HPM-MVS++		97.72 14	97.59 14	98.14 26	99.53 45	94.76 47	99.19 116	97.75 93	95.66 35	98.21 61	99.29 29	91.10 39	99.99 9	97.68 78	99.87 9	99.68 67

test_prior4						92.00 122	99.41 92

XVS		96.47 58	96.37 57	96.77 93	99.62 27	90.66 164	99.43 89	97.58 139	92.41 110	96.86 97	98.96 88	87.37 102	99.87 75	95.65 127	99.43 65	99.78 46

v1240		85.77 359	84.11 365	90.73 349	89.26 421	85.15 348	97.88 298	95.23 393	81.89 400	82.16 349	90.55 401	69.60 357	96.31 358	75.59 402	74.87 392	90.72 407

pm-mvs1		84.68 372	82.78 380	90.40 358	89.58 415	85.18 346	97.31 332	94.73 408	81.93 399	76.05 420	92.01 356	65.48 397	96.11 371	78.75 380	69.14 433	89.91 425

test_prior2							99.57 64		91.43 135	98.12 65	98.97 83	90.43 55		98.33 63	99.81 23

X-MVStestdata		90.69 258	88.66 288	96.77 93	99.62 27	90.66 164	99.43 89	97.58 139	92.41 110	96.86 97	29.59 501	87.37 102	99.87 75	95.65 127	99.43 65	99.78 46

test_prior				97.01 77	99.58 35	91.77 129		97.57 142					99.49 134			99.79 43

旧先验2							98.67 192		85.75 327	98.96 31			98.97 178	93.84 176

新几何2							98.26 260

新几何1				97.40 58	98.92 88	92.51 113		97.77 92	85.52 329	96.69 109	99.06 73	88.08 91	99.89 69	84.88 309	99.62 50	99.79 43

旧先验1					98.97 80	92.90 102		97.74 94			99.15 55	91.05 41			99.33 69	99.60 82

无先验							98.52 219	97.82 79	87.20 291				99.90 61	87.64 271		99.85 35

原ACMM2							98.69 188

原ACMM1				96.18 137	99.03 78	90.08 183		97.63 128	88.98 225	97.00 94	98.97 83	88.14 90	99.71 112	88.23 264	99.62 50	98.76 177

test222					98.32 103	91.21 143	98.08 283	97.58 139	83.74 363	95.87 127	99.02 79	86.74 119			99.64 42	99.81 40

testdata2													99.88 71	84.16 320

segment_acmp												90.56 53

testdata				95.26 195	98.20 108	87.28 288		97.60 133	85.21 333	98.48 52	99.15 55	88.15 89	98.72 194	90.29 237	99.45 63	99.78 46

testdata1							97.89 296		92.43 107

v8		86.11 350	84.45 361	91.10 337	89.99 405	86.85 296	97.24 337	95.36 381	81.99 397	79.89 385	89.86 416	74.53 311	96.39 348	78.83 379	72.32 420	90.05 422

1314		93.44 174	91.98 206	97.84 36	95.24 255	94.38 59	96.22 380	97.92 67	90.18 176	82.28 347	97.71 171	77.63 278	99.80 99	91.94 218	98.67 114	99.34 112

LFMVS		92.23 219	90.84 238	96.42 118	98.24 107	91.08 151	98.24 263	96.22 278	83.39 370	94.74 152	98.31 144	61.12 420	98.85 182	94.45 162	92.82 242	99.32 113

VDD-MVS		91.24 244	90.18 250	94.45 238	97.08 170	85.84 334	98.40 241	96.10 292	86.99 294	93.36 184	98.16 151	54.27 446	99.20 162	96.59 104	90.63 293	98.31 222

VDDNet		90.08 279	88.54 294	94.69 224	94.41 307	87.68 268	98.21 266	96.40 263	76.21 435	93.33 185	97.75 165	54.93 444	98.77 186	94.71 157	90.96 288	97.61 258

v10		85.73 360	84.01 368	90.87 345	90.03 404	86.73 298	97.20 340	95.22 394	81.25 405	79.85 386	89.75 417	73.30 324	96.28 362	76.87 391	72.64 416	89.61 430

VPNet		88.30 314	86.57 325	93.49 276	91.95 379	91.35 140	98.18 268	97.20 201	88.61 241	84.52 315	94.89 300	62.21 415	96.76 330	89.34 250	72.26 421	92.36 336

MVS		93.92 154	92.28 193	98.83 8	95.69 233	96.82 9	96.22 380	98.17 39	84.89 342	84.34 317	98.61 125	79.32 254	99.83 91	93.88 175	99.43 65	99.86 34

v2v482		87.27 331	85.76 337	91.78 324	89.59 414	87.58 277	98.56 215	95.54 362	84.53 350	82.51 341	91.78 362	73.11 326	96.47 344	82.07 353	74.14 403	91.30 386

V42		87.00 333	85.68 339	90.98 341	89.91 406	86.08 324	98.32 254	95.61 358	83.67 366	82.72 335	90.67 392	74.00 318	96.53 339	81.94 356	74.28 400	90.32 415

SD-MVS		97.51 19	97.40 22	97.81 41	99.01 79	93.79 71	99.33 103	97.38 178	93.73 76	98.83 36	99.02 79	90.87 47	99.88 71	98.69 46	99.74 29	99.77 51
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		90.10 278	88.69 287	94.33 243	92.44 368	87.97 262	99.08 140	96.26 276	89.65 196	86.92 295	93.11 338	68.09 369	96.96 320	82.54 346	90.15 295	98.05 239

MSLP-MVS++		97.50 20	97.45 21	97.63 47	99.65 21	93.21 88	99.70 41	98.13 45	94.61 50	97.78 77	99.46 15	89.85 64	99.81 97	97.97 71	99.91 6	99.88 28

APDe-MVS		97.53 18	97.47 19	97.70 45	99.58 35	93.63 75	99.56 65	97.52 153	93.59 81	98.01 71	99.12 63	90.80 49	99.55 128	99.26 26	99.79 27	99.93 22
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
APD-MVS_3200maxsize		95.64 97	95.65 90	95.62 174	99.24 65	87.80 265	98.42 235	97.22 196	88.93 229	96.64 112	98.98 82	85.49 148	99.36 152	96.68 100	99.27 74	99.70 62

ADS-MVSNet2		87.62 327	86.88 322	89.86 372	96.21 208	79.14 421	87.15 468	92.99 439	83.01 376	89.91 262	87.27 439	78.87 260	92.80 448	74.20 412	92.27 259	97.64 253

EI-MVSNet		89.87 282	89.38 268	91.36 334	94.32 314	85.87 332	97.61 321	96.59 248	85.10 335	85.51 307	97.10 216	81.30 234	96.56 337	83.85 330	83.03 342	91.64 361

Regformer		0.00 470	0.00 473	0.00 485	0.00 508	0.00 510	0.00 496	0.00 509	0.00 503	0.00 504	0.00 503	0.00 507	0.00 504	0.00 502	0.00 502	0.00 500

CVMVSNet		90.30 271	90.91 235	88.46 401	94.32 314	73.58 456	97.61 321	97.59 137	90.16 179	88.43 281	97.10 216	76.83 285	92.86 445	82.64 344	93.54 232	98.93 154

pmmvs4		87.58 328	86.17 332	91.80 319	89.58 415	88.92 233	97.25 336	95.28 383	82.54 388	80.49 375	93.17 337	75.62 303	96.05 374	82.75 341	78.90 366	90.42 413

EU-MVSNet		84.19 381	84.42 363	83.52 446	88.64 428	67.37 476	96.04 386	95.76 342	85.29 332	78.44 408	93.18 335	70.67 349	91.48 462	75.79 401	75.98 383	91.70 358

VNet		95.08 114	94.26 123	97.55 52	98.07 114	93.88 68	98.68 189	98.73 17	90.33 170	97.16 91	97.43 188	79.19 256	99.53 131	96.91 95	91.85 268	99.24 120

test-LLR		93.11 192	92.68 181	94.40 239	94.94 287	87.27 289	99.15 127	97.25 191	90.21 174	91.57 225	94.04 309	84.89 162	97.58 294	85.94 297	96.13 183	98.36 219

TESTMET0.1,1		93.82 160	93.26 164	95.49 178	95.21 259	90.25 174	99.15 127	97.54 148	89.18 216	91.79 220	94.87 301	89.13 71	97.63 290	86.21 293	96.29 180	98.60 199

test-mter		93.27 184	92.89 177	94.40 239	94.94 287	87.27 289	99.15 127	97.25 191	88.95 227	91.57 225	94.04 309	88.03 92	97.58 294	85.94 297	96.13 183	98.36 219

VPA-MVSNet		89.10 294	87.66 307	93.45 278	92.56 365	91.02 153	97.97 294	98.32 32	86.92 299	86.03 301	92.01 356	68.84 363	97.10 316	90.92 228	75.34 387	92.23 342

ACMMPR		96.28 65	96.14 72	96.73 97	99.68 14	90.47 169	99.47 78	97.80 85	90.54 164	96.83 101	99.03 77	86.51 130	99.95 37	95.65 127	99.72 32	99.75 54

testgi		82.29 398	81.00 396	86.17 424	87.24 445	74.84 451	97.39 328	91.62 460	88.63 240	75.85 424	95.42 292	46.07 469	91.55 461	66.87 452	79.94 362	92.12 348

test20.03		78.51 423	77.48 418	81.62 454	83.07 464	71.03 465	96.11 384	92.83 442	81.66 401	69.31 456	89.68 418	57.53 430	87.29 482	58.65 473	68.47 438	86.53 458

thres600view7		93.18 186	92.00 205	96.75 95	97.62 131	94.92 38	99.07 141	99.36 2	87.96 268	90.47 250	96.78 248	83.29 187	98.71 195	82.93 340	90.47 294	96.61 291

ADS-MVSNet		88.99 295	87.30 314	94.07 257	96.21 208	87.56 278	87.15 468	96.78 234	83.01 376	89.91 262	87.27 439	78.87 260	97.01 319	74.20 412	92.27 259	97.64 253

MP-MVS		96.00 73	95.82 80	96.54 112	99.47 51	90.13 182	99.36 99	97.41 174	90.64 158	95.49 139	98.95 91	85.51 147	99.98 13	96.00 121	99.59 55	99.52 90
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		18.81 465	23.05 468	6.10 484	4.48 506	2.29 509	97.78 304	3.00 507	3.27 500	18.60 500	62.71 488	1.53 506	2.49 503	14.26 500	1.80 500	13.50 498

thres400		93.39 177	92.27 194	96.73 97	97.68 128	94.84 43	99.18 118	99.36 2	88.45 247	90.79 240	96.90 238	83.31 185	98.75 190	84.11 322	90.69 290	96.61 291

test123		16.58 467	19.47 469	7.91 483	3.59 507	5.37 508	94.32 416	1.39 508	2.49 501	13.98 501	44.60 498	2.91 505	2.65 502	11.35 501	0.57 501	15.70 497

thres200		93.69 163	92.59 186	96.97 83	97.76 124	94.74 48	99.35 101	99.36 2	89.23 213	91.21 236	96.97 230	83.42 184	98.77 186	85.08 305	90.96 288	97.39 263

test0.0.03 1		88.96 296	88.61 289	90.03 370	91.09 395	84.43 358	98.97 155	97.02 221	90.21 174	80.29 379	96.31 267	84.89 162	91.93 459	72.98 422	85.70 320	93.73 322

pmmvs3		72.86 442	69.76 447	82.17 450	73.86 487	74.19 453	94.20 419	89.01 480	64.23 479	67.72 462	80.91 475	41.48 475	88.65 479	62.40 463	54.02 481	83.68 477

EMVS		39.96 463	39.88 465	40.18 481	59.57 500	32.12 505	84.79 478	64.57 503	26.27 496	26.14 497	44.18 499	18.73 493	59.29 500	17.03 498	17.67 497	29.12 496

E-PMN		41.02 462	40.93 464	41.29 480	61.97 497	33.83 503	84.00 481	65.17 502	27.17 495	27.56 495	46.72 496	17.63 495	60.41 499	19.32 497	18.82 495	29.61 495

PGM-MVS		95.85 84	95.65 90	96.45 116	99.50 47	89.77 199	98.22 264	98.90 13	89.19 215	96.74 107	98.95 91	85.91 142	99.92 49	93.94 173	99.46 61	99.66 71

LCM-MVSNet-Re		88.59 311	88.61 289	88.51 400	95.53 242	72.68 461	96.85 354	88.43 481	88.45 247	73.14 440	90.63 395	75.82 299	94.38 430	92.95 201	95.71 192	98.48 206

LCM-MVSNet		60.07 453	56.37 455	71.18 466	54.81 501	48.67 494	82.17 486	89.48 477	37.95 491	49.13 486	69.12 485	13.75 498	81.76 486	59.28 470	51.63 486	83.10 479

MCST-MVS		98.18 2	97.95 9	98.86 6	99.85 4	96.60 11	99.70 41	97.98 62	97.18 11	95.96 123	99.33 27	92.62 30	100.00 1	98.99 41	99.93 1	99.98 7

mvs_anonymous		92.50 211	91.65 216	95.06 208	96.60 187	89.64 203	97.06 346	96.44 261	86.64 306	84.14 318	93.93 316	82.49 210	96.17 368	91.47 222	96.08 186	99.35 110

MVS_Test		93.67 166	92.67 182	96.69 101	96.72 185	92.66 106	97.22 339	96.03 301	87.69 282	95.12 146	94.03 311	81.55 226	98.28 215	89.17 256	96.46 172	99.14 128

MDA-MVSNet-bldmvs		77.82 428	74.75 434	87.03 414	88.33 431	78.52 427	96.34 373	92.85 441	75.57 444	48.87 487	87.89 431	57.32 432	92.49 453	60.79 467	64.80 451	90.08 419

CDPH-MVS		96.56 56	96.18 65	97.70 45	99.59 33	93.92 67	99.13 135	97.44 170	89.02 224	97.90 74	99.22 37	88.90 77	99.49 134	94.63 159	99.79 27	99.68 67

test12				97.83 40	99.33 58	94.45 56		97.55 144		97.56 78		88.60 81	99.50 133		99.71 36	99.55 87

casdiffmvs		93.98 152	93.43 156	95.61 175	95.07 277	89.86 194	98.80 170	95.84 335	90.98 146	92.74 199	97.66 174	79.71 247	98.10 234	94.72 156	95.37 198	98.87 162
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		94.59 134	94.19 126	95.81 161	95.54 241	90.69 162	98.70 185	95.68 352	91.61 128	95.96 123	97.81 159	80.11 243	98.06 245	96.52 106	95.76 190	98.67 192
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		94.04 149	93.80 147	94.74 221	93.07 359	90.25 174	98.12 274	98.16 42	89.86 187	86.53 299	96.95 231	95.56 6	98.05 248	91.44 223	94.53 213	95.93 309

baseline1		92.61 208	91.28 224	96.58 109	97.05 173	94.63 53	97.72 311	96.20 280	89.82 190	88.56 279	96.85 242	86.85 116	97.82 266	88.42 261	80.10 361	97.30 267

YYNet1		79.64 416	77.04 421	87.43 412	87.80 440	79.98 413	96.23 379	94.44 415	73.83 453	51.83 484	87.53 434	67.96 372	92.07 458	66.00 454	67.75 443	90.23 417

PMMVS2		58.97 454	55.07 457	70.69 468	62.72 496	55.37 487	85.97 470	80.52 494	49.48 487	45.94 488	68.31 486	15.73 496	80.78 490	49.79 484	37.12 493	75.91 482

MDA-MVSNet_test_wron		79.65 415	77.05 420	87.45 411	87.79 441	80.13 412	96.25 378	94.44 415	73.87 452	51.80 485	87.47 438	68.04 370	92.12 457	66.02 453	67.79 442	90.09 418

tpmvs		89.16 291	87.76 304	93.35 280	97.19 160	84.75 355	90.58 462	97.36 182	81.99 397	84.56 313	89.31 424	83.98 177	98.17 226	74.85 407	90.00 298	97.12 272

PM-MVS		74.88 439	72.85 440	80.98 456	78.98 480	64.75 479	90.81 459	85.77 486	80.95 410	68.23 461	82.81 463	29.08 486	92.84 446	76.54 395	62.46 458	85.36 469

HQP_MVS		91.26 241	90.95 234	92.16 309	93.84 335	86.07 326	99.02 148	96.30 272	93.38 86	86.99 293	96.52 257	72.92 329	97.75 279	93.46 187	86.17 315	92.67 332

plane_prior7					93.84 335	85.73 335

plane_prior6					93.92 332	86.02 328						72.92 329

plane_prior5								96.30 272					97.75 279	93.46 187	86.17 315	92.67 332

plane_prior4											96.52 257

plane_prior3						85.91 330			93.65 79	86.99 293

plane_prior2							99.02 148		93.38 86

plane_prior1					93.90 334

plane_prior						86.07 326	99.14 130		93.81 75						86.26 314

PS-CasMVS		85.81 357	84.58 359	89.49 385	90.77 399	82.11 391	97.20 340	97.36 182	84.83 343	79.12 397	92.84 344	67.42 377	95.16 416	78.39 383	73.25 413	91.21 391

UniMVSNet_NR-MVSNet		89.60 286	88.55 293	92.75 295	92.17 374	90.07 184	98.74 178	98.15 43	88.37 252	83.21 327	93.98 314	82.86 197	95.93 380	86.95 278	72.47 418	92.25 340

PEN-MVS		85.21 366	83.93 369	89.07 394	89.89 408	81.31 402	97.09 345	97.24 194	84.45 353	78.66 400	92.68 347	68.44 366	94.87 421	75.98 399	70.92 429	91.04 395

TransMVSNet (Re)		81.97 401	79.61 410	89.08 393	89.70 413	84.01 364	97.26 335	91.85 456	78.84 420	73.07 443	91.62 366	67.17 379	95.21 415	67.50 448	59.46 467	88.02 446

DTE-MVSNet		84.14 382	82.80 378	88.14 403	88.95 424	79.87 414	96.81 355	96.24 277	83.50 368	77.60 414	92.52 349	67.89 373	94.24 432	72.64 425	69.05 434	90.32 415

DU-MVS		88.83 302	87.51 310	92.79 293	91.46 390	90.07 184	98.71 182	97.62 130	88.87 231	83.21 327	93.68 322	74.63 307	95.93 380	86.95 278	72.47 418	92.36 336

UniMVSNet (Re)		89.50 289	88.32 297	93.03 285	92.21 373	90.96 155	98.90 162	98.39 29	89.13 221	83.22 326	92.03 354	81.69 225	96.34 356	86.79 282	72.53 417	91.81 357

CP-MVSNet		86.54 343	85.45 343	89.79 375	91.02 397	82.78 383	97.38 330	97.56 143	85.37 331	79.53 390	93.03 340	71.86 340	95.25 414	79.92 370	73.43 412	91.34 384

WR-MVS_H		86.53 344	85.49 342	89.66 380	91.04 396	83.31 374	97.53 324	98.20 38	84.95 341	79.64 387	90.90 385	78.01 276	95.33 412	76.29 397	72.81 414	90.35 414

WR-MVS		88.54 312	87.22 317	92.52 302	91.93 381	89.50 206	98.56 215	97.84 74	86.99 294	81.87 361	93.81 319	74.25 316	95.92 382	85.29 303	74.43 397	92.12 348

NR-MVSNet		87.74 325	86.00 334	92.96 289	91.46 390	90.68 163	96.65 364	97.42 173	88.02 266	73.42 437	93.68 322	77.31 280	95.83 388	84.26 318	71.82 425	92.36 336

Baseline_NR-MVSNet		85.83 356	84.82 353	88.87 398	88.73 426	83.34 373	98.63 198	91.66 458	80.41 416	82.44 342	91.35 375	74.63 307	95.42 409	84.13 321	71.39 427	87.84 447

TranMVSNet+NR-MVSNet		87.75 322	86.31 329	92.07 312	90.81 398	88.56 244	98.33 252	97.18 202	87.76 277	81.87 361	93.90 317	72.45 333	95.43 408	83.13 338	71.30 428	92.23 342

TSAR-MVS + GP.		96.95 35	96.91 33	97.07 74	98.88 90	91.62 134	99.58 63	96.54 254	95.09 44	96.84 99	98.63 123	91.16 37	99.77 107	99.04 38	96.42 174	99.81 40

n2								0.00 509

nn								0.00 509

mPP-MVS		95.90 81	95.75 85	96.38 122	99.58 35	89.41 210	99.26 111	97.41 174	90.66 155	94.82 149	98.95 91	86.15 138	99.98 13	95.24 142	99.64 42	99.74 55

door-mid								84.90 489

XVG-OURS-SEG-HR		90.95 252	90.66 244	91.83 316	95.18 263	81.14 406	95.92 388	95.92 320	88.40 251	90.33 253	97.85 157	70.66 350	99.38 150	92.83 205	88.83 301	94.98 317

mvsmamba		94.27 143	93.91 142	95.35 187	96.42 196	88.61 242	97.77 306	96.38 267	91.17 144	94.05 166	95.27 295	78.41 271	97.96 257	97.36 84	98.40 127	99.48 97

MVSFormer		94.71 130	94.08 131	96.61 106	95.05 278	94.87 41	97.77 306	96.17 287	86.84 300	98.04 69	98.52 129	85.52 145	95.99 376	89.83 240	98.97 92	98.96 148

jason		95.40 104	94.86 112	97.03 76	92.91 360	94.23 62	99.70 41	96.30 272	93.56 82	96.73 108	98.52 129	81.46 231	97.91 258	96.08 118	98.47 126	98.96 148
jason: jason.
lupinMVS		96.32 63	95.94 74	97.44 53	95.05 278	94.87 41	99.86 9	96.50 256	93.82 74	98.04 69	98.77 107	85.52 145	98.09 236	96.98 92	98.97 92	99.37 107

test_djsdf		88.26 316	87.73 305	89.84 373	88.05 435	82.21 390	97.77 306	96.17 287	86.84 300	82.41 345	91.95 360	72.07 337	95.99 376	89.83 240	84.50 327	91.32 385

HPM-MVS_fast		94.89 118	94.62 115	95.70 166	99.11 73	88.44 249	99.14 130	97.11 210	85.82 324	95.69 135	98.47 138	83.46 183	99.32 157	93.16 198	99.63 49	99.35 110

K. test v3		81.04 407	79.77 409	84.83 436	87.41 443	70.23 469	95.60 400	93.93 428	83.70 365	67.51 464	89.35 423	55.76 436	93.58 440	76.67 394	68.03 440	90.67 409

lessismore_v0				85.08 434	85.59 454	69.28 471		90.56 471		67.68 463	90.21 411	54.21 447	95.46 407	73.88 415	62.64 457	90.50 412

SixPastTwentyTwo		82.63 397	81.58 390	85.79 429	88.12 434	71.01 466	95.17 405	92.54 445	84.33 354	72.93 444	92.08 353	60.41 423	95.61 403	74.47 409	74.15 402	90.75 405

OurMVSNet-221017-0		84.13 383	83.59 372	85.77 430	87.81 439	70.24 468	94.89 408	93.65 434	86.08 318	76.53 416	93.28 333	61.41 418	96.14 370	80.95 362	77.69 377	90.93 397

HPM-MVS		95.41 103	95.22 101	95.99 152	99.29 60	89.14 217	99.17 121	97.09 214	87.28 290	95.40 140	98.48 137	84.93 161	99.38 150	95.64 131	99.65 40	99.47 99
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
XVG-OURS		90.83 254	90.49 246	91.86 315	95.23 256	81.25 403	95.79 396	95.92 320	88.96 226	90.02 260	98.03 154	71.60 343	99.35 155	91.06 226	87.78 305	94.98 317

XVG-ACMP-BASELINE		85.86 355	84.95 350	88.57 399	89.90 407	77.12 439	94.30 417	95.60 359	87.40 288	82.12 350	92.99 342	53.42 450	97.66 287	85.02 307	83.83 333	90.92 398

casdiffmvs_mvg		94.00 150	93.33 161	96.03 147	95.22 257	90.90 158	99.09 139	95.99 303	90.58 161	91.55 228	97.37 192	79.91 246	98.06 245	95.01 147	95.22 201	99.13 130
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		88.86 299	88.47 295	90.06 366	93.35 352	80.95 408	98.22 264	95.94 315	87.73 280	83.17 329	96.11 272	66.28 391	97.77 272	90.19 238	85.19 322	91.46 373

LGP-MVS_train				90.06 366	93.35 352	80.95 408		95.94 315	87.73 280	83.17 329	96.11 272	66.28 391	97.77 272	90.19 238	85.19 322	91.46 373

baseline		93.91 155	93.30 162	95.72 165	95.10 275	90.07 184	97.48 325	95.91 326	91.03 145	93.54 180	97.68 172	79.58 248	98.02 253	94.27 167	95.14 203	99.08 139

test11								97.68 109

door								85.30 487

EPNet_dtu		92.28 217	92.15 202	92.70 299	97.29 153	84.84 353	98.64 196	97.82 79	92.91 97	93.02 190	97.02 227	85.48 150	95.70 398	72.25 428	94.89 206	97.55 259
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x2688		94.35 140	93.82 146	95.95 155	97.40 145	88.74 240	98.41 238	98.27 33	92.18 119	91.43 230	96.40 262	78.88 258	99.81 97	93.59 181	97.81 140	99.30 115

EPNet		96.82 40	96.68 47	97.25 68	98.65 97	93.10 92	99.48 76	98.76 14	96.54 22	97.84 75	98.22 148	87.49 99	99.66 116	95.35 137	97.78 143	99.00 144
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS						86.39 307

HQP-NCC					93.95 327		99.16 122		93.92 66	87.57 286

ACMP_Plane					93.95 327		99.16 122		93.92 66	87.57 286

APD-MVS		96.95 35	96.72 45	97.63 47	99.51 46	93.58 78	99.16 122	97.44 170	90.08 182	98.59 46	99.07 70	89.06 72	99.42 145	97.92 72	99.66 39	99.88 28
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS														93.82 178

HQP4-MVS										87.57 286			97.77 272			92.72 330

HQP3-MVS								96.37 268							86.29 312

HQP2-MVS												73.34 322

CNVR-MVS		98.46 1	98.38 1	98.72 12	99.80 5	96.19 17	99.80 26	97.99 61	97.05 13	99.41 11	99.59 3	92.89 29	100.00 1	98.99 41	99.90 7	99.96 11

NCCC		98.12 5	98.11 3	98.13 27	99.76 7	94.46 55	99.81 20	97.88 69	96.54 22	98.84 35	99.46 15	92.55 31	99.98 13	98.25 67	99.93 1	99.94 20

114514_t		94.06 148	93.05 170	97.06 75	99.08 76	92.26 118	98.97 155	97.01 222	82.58 387	92.57 203	98.22 148	80.68 240	99.30 158	89.34 250	99.02 89	99.63 79

CP-MVS		96.22 66	96.15 71	96.42 118	99.67 15	89.62 204	99.70 41	97.61 131	90.07 183	96.00 122	99.16 51	87.43 100	99.92 49	96.03 120	99.72 32	99.70 62

DSMNet-mixed		81.60 404	81.43 392	82.10 452	84.36 457	60.79 481	93.63 427	86.74 485	79.00 418	79.32 394	87.15 441	63.87 406	89.78 472	66.89 451	91.92 266	95.73 312

tpm2		91.77 230	91.09 228	93.82 268	94.83 293	85.56 339	92.51 441	97.16 205	84.00 358	93.83 174	90.66 393	87.54 98	97.17 311	87.73 270	91.55 275	98.72 185

NP-MVS					93.94 330	86.22 314					96.67 255

EG-PatchMatch MVS		79.92 411	77.59 417	86.90 417	87.06 447	77.90 434	96.20 382	94.06 426	74.61 449	66.53 468	88.76 426	40.40 478	96.20 365	67.02 450	83.66 337	86.61 457

tpm cat1		88.89 298	87.27 315	93.76 271	95.79 229	85.32 344	90.76 460	97.09 214	76.14 436	85.72 305	88.59 427	82.92 196	98.04 250	76.96 390	91.43 281	97.90 245

SteuartSystems-ACMMP		97.25 23	97.34 24	97.01 77	97.38 147	91.46 139	99.75 35	97.66 115	94.14 63	98.13 63	99.26 30	92.16 35	99.66 116	97.91 73	99.64 42	99.90 24
Skip Steuart: Steuart Systems R&D Blog.
CostFormer		92.89 197	92.48 189	94.12 255	94.99 282	85.89 331	92.89 436	97.00 223	86.98 297	95.00 148	90.78 387	90.05 63	97.51 298	92.92 204	91.73 271	98.96 148

CR-MVSNet		88.83 302	87.38 313	93.16 284	93.47 347	86.24 312	84.97 476	94.20 424	88.92 230	90.76 242	86.88 443	84.43 171	94.82 423	70.64 433	92.17 263	98.41 209

JIA-IIPM		85.97 353	84.85 352	89.33 388	93.23 354	73.68 455	85.05 475	97.13 208	69.62 466	91.56 227	68.03 487	88.03 92	96.96 320	77.89 385	93.12 239	97.34 264

Patchmtry		83.61 389	81.64 389	89.50 383	93.36 351	82.84 382	84.10 479	94.20 424	69.47 467	79.57 389	86.88 443	84.43 171	94.78 424	68.48 445	74.30 399	90.88 399

PatchT		85.44 363	83.19 374	92.22 306	93.13 356	83.00 376	83.80 482	96.37 268	70.62 460	90.55 247	79.63 478	84.81 164	94.87 421	58.18 474	91.59 273	98.79 171

tpmrst		92.78 202	92.16 201	94.65 225	96.27 205	87.45 282	91.83 446	97.10 213	89.10 223	94.68 153	90.69 391	88.22 86	97.73 283	89.78 243	91.80 269	98.77 175

BH-w/o		92.32 215	91.79 213	93.91 265	96.85 178	86.18 320	99.11 138	95.74 343	88.13 261	84.81 311	97.00 228	77.26 281	97.91 258	89.16 257	98.03 136	97.64 253

tpm		89.67 285	88.95 279	91.82 318	92.54 366	81.43 398	92.95 435	95.92 320	87.81 275	90.50 249	89.44 421	84.99 160	95.65 400	83.67 333	82.71 345	98.38 213

DELS-MVS		97.12 29	96.60 49	98.68 13	98.03 116	96.57 12	99.84 14	97.84 74	96.36 27	95.20 144	98.24 147	88.17 87	99.83 91	96.11 117	99.60 54	99.64 76
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		91.46 236	90.84 238	93.33 281	96.51 192	84.83 354	98.84 166	95.50 368	86.44 314	83.50 322	96.70 253	75.49 305	97.77 272	86.78 283	97.81 140	97.40 262

RPMNet		85.07 368	81.88 387	94.64 227	93.47 347	86.24 312	84.97 476	97.21 197	64.85 478	90.76 242	78.80 480	80.95 238	99.27 159	53.76 480	92.17 263	98.41 209

MVSTER		92.71 203	92.32 191	93.86 266	97.29 153	92.95 100	99.01 150	96.59 248	90.09 181	85.51 307	94.00 313	94.61 16	96.56 337	90.77 233	83.03 342	92.08 350

CPTT-MVS		94.60 133	94.43 120	95.09 205	99.66 17	86.85 296	99.44 85	97.47 163	83.22 372	94.34 161	98.96 88	82.50 209	99.55 128	94.81 153	99.50 59	98.88 159

GBi-Net		86.67 340	84.96 348	91.80 319	95.11 272	88.81 236	96.77 356	95.25 386	82.94 379	82.12 350	90.25 407	62.89 410	94.97 418	79.04 375	80.24 358	91.62 363

PVSNet_Blended_VisFu		94.67 131	94.11 129	96.34 125	97.14 165	91.10 149	99.32 104	97.43 172	92.10 122	91.53 229	96.38 265	83.29 187	99.68 114	93.42 189	96.37 175	98.25 224

PVSNet_BlendedMVS		93.36 180	93.20 165	93.84 267	98.77 94	91.61 136	99.47 78	98.04 57	91.44 134	94.21 162	92.63 348	83.50 181	99.87 75	97.41 82	83.37 340	90.05 422

UnsupCasMVSNet_eth		78.90 418	76.67 423	85.58 431	82.81 469	74.94 450	91.98 445	96.31 271	84.64 349	65.84 472	87.71 432	51.33 455	92.23 455	72.89 423	56.50 478	89.56 431

UnsupCasMVSNet_bld		73.85 441	70.14 445	84.99 435	79.44 479	75.73 446	88.53 465	95.24 389	70.12 464	61.94 476	74.81 484	41.41 476	93.62 439	68.65 444	51.13 487	85.62 466

PVSNet_Blended		95.94 79	95.66 88	96.75 95	98.77 94	91.61 136	99.88 5	98.04 57	93.64 80	94.21 162	97.76 164	83.50 181	99.87 75	97.41 82	97.75 144	98.79 171

FMVSNet5		82.29 398	80.54 398	87.52 409	93.79 339	84.01 364	93.73 425	92.47 446	76.92 431	74.27 431	86.15 453	63.69 408	89.24 476	69.07 441	74.79 393	89.29 434

test1		86.67 340	84.96 348	91.80 319	95.11 272	88.81 236	96.77 356	95.25 386	82.94 379	82.12 350	90.25 407	62.89 410	94.97 418	79.04 375	80.24 358	91.62 363

new_pmnet		76.02 433	73.71 436	82.95 447	83.88 459	72.85 460	91.26 455	92.26 449	70.44 462	62.60 475	81.37 471	47.64 467	92.32 454	61.85 464	72.10 423	83.68 477

FMVSNet3		88.81 304	87.08 318	93.99 262	96.52 191	94.59 54	98.08 283	96.20 280	85.85 323	82.12 350	91.60 367	74.05 317	95.40 410	79.04 375	80.24 358	91.99 353

dp		90.16 277	88.83 284	94.14 254	96.38 201	86.42 305	91.57 451	97.06 216	84.76 345	88.81 276	90.19 412	84.29 173	97.43 303	75.05 404	91.35 285	98.56 200

FMVSNet2		86.90 334	84.79 354	93.24 282	95.11 272	92.54 112	97.67 316	95.86 333	82.94 379	80.55 374	91.17 380	62.89 410	95.29 413	77.23 387	79.71 364	91.90 354

FMVSNet1		83.94 385	81.32 394	91.80 319	91.94 380	88.81 236	96.77 356	95.25 386	77.98 424	78.25 410	90.25 407	50.37 461	94.97 418	73.27 420	77.81 376	91.62 363

N_pmnet		70.19 444	69.87 446	71.12 467	88.24 432	30.63 506	95.85 394	28.70 505	70.18 463	68.73 458	86.55 446	64.04 405	93.81 436	53.12 481	73.46 410	88.94 439

cascas		90.93 253	89.33 269	95.76 163	95.69 233	93.03 95	98.99 152	96.59 248	80.49 413	86.79 298	94.45 306	65.23 400	98.60 199	93.52 183	92.18 262	95.66 313

BH-RMVSNet		91.25 243	89.99 252	95.03 211	96.75 184	88.55 245	98.65 194	94.95 400	87.74 279	87.74 285	97.80 160	68.27 367	98.14 227	80.53 368	97.49 151	98.41 209

UGNet		91.91 228	90.85 237	95.10 204	97.06 171	88.69 241	98.01 291	98.24 36	92.41 110	92.39 210	93.61 325	60.52 422	99.68 114	88.14 265	97.25 156	96.92 281
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		95.97 76	95.11 106	98.54 15	97.62 131	96.65 10	99.44 85	98.74 15	92.25 117	95.21 143	98.46 140	86.56 127	99.46 140	95.00 148	92.69 245	99.50 95

XXY-MVS		87.75 322	86.02 333	92.95 290	90.46 402	89.70 202	97.71 313	95.90 327	84.02 357	80.95 370	94.05 308	67.51 376	97.10 316	85.16 304	78.41 368	92.04 352

EC-MVSNet		95.09 113	95.17 102	94.84 217	95.42 247	88.17 255	99.48 76	95.92 320	91.47 133	97.34 85	98.36 142	82.77 201	97.41 304	97.24 86	98.58 120	98.94 153

sss		94.85 123	93.94 139	97.58 49	96.43 195	94.09 66	98.93 157	99.16 8	89.50 206	95.27 142	97.85 157	81.50 228	99.65 120	92.79 206	94.02 222	98.99 145

Test_1112_low_res		92.27 218	90.97 233	96.18 137	95.53 242	91.10 149	98.47 230	94.66 411	88.28 258	86.83 297	93.50 329	87.00 114	98.65 198	84.69 311	89.74 300	98.80 170

1112_ss		92.71 203	91.55 218	96.20 135	95.56 240	91.12 147	98.48 227	94.69 410	88.29 257	86.89 296	98.50 131	87.02 113	98.66 197	84.75 310	89.77 299	98.81 168

ab-mvs-re		8.21 468	10.94 471	0.00 485	0.00 508	0.00 510	0.00 496	0.00 509	0.00 503	0.00 504	98.50 131	0.00 507	0.00 504	0.00 502	0.00 502	0.00 500

ab-mvs		91.05 250	89.17 272	96.69 101	95.96 223	91.72 132	92.62 440	97.23 195	85.61 328	89.74 266	93.89 318	68.55 364	99.42 145	91.09 225	87.84 304	98.92 156

TR-MVS		90.77 255	89.44 265	94.76 219	96.31 203	88.02 260	97.92 295	95.96 312	85.52 329	88.22 282	97.23 205	66.80 384	98.09 236	84.58 314	92.38 255	98.17 232

MDTV_nov1_ep13_2view						91.17 146	91.38 453		87.45 287	93.08 188		86.67 123		87.02 276		98.95 152

MDTV_nov1_ep13			90.47 248		96.14 215	88.55 245	91.34 454	97.51 155	89.58 201	92.24 211	90.50 404	86.99 115	97.61 292	77.64 386	92.34 257

MIMVSNet1		75.92 434	73.30 438	83.81 443	81.29 474	75.57 447	92.26 443	92.05 453	73.09 456	67.48 465	86.18 452	40.87 477	87.64 481	55.78 477	70.68 430	88.21 445

MIMVSNet		84.48 376	81.83 388	92.42 304	91.73 386	87.36 285	85.52 471	94.42 419	81.40 403	81.91 358	87.58 433	51.92 453	92.81 447	73.84 416	88.15 303	97.08 276

IterMVS-LS		88.34 313	87.44 311	91.04 339	94.10 322	85.85 333	98.10 277	95.48 372	85.12 334	82.03 355	91.21 379	81.35 233	95.63 402	83.86 329	75.73 385	91.63 362
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet		93.47 172	93.04 171	94.76 219	94.75 296	89.45 208	98.82 167	97.03 219	87.91 270	90.97 237	96.48 260	89.06 72	96.36 350	89.50 246	92.81 244	98.49 205
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref															82.64 346

IterMVS		85.81 357	84.67 357	89.22 389	93.51 346	83.67 369	96.32 374	94.80 406	85.09 336	78.69 398	90.17 413	66.57 389	93.17 444	79.48 373	77.42 378	90.81 400
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon		95.85 84	95.15 103	97.95 34	99.87 2	94.38 59	99.60 61	97.48 161	86.58 307	94.42 157	99.13 60	87.36 105	99.98 13	93.64 180	98.33 130	99.48 97

MVS_111021_LR		95.78 88	95.94 74	95.28 194	98.19 110	87.69 267	98.80 170	99.26 7	93.39 85	95.04 147	98.69 118	84.09 175	99.76 108	96.96 93	99.06 86	98.38 213

DP-MVS		88.75 306	86.56 326	95.34 188	98.92 88	87.45 282	97.64 320	93.52 436	70.55 461	81.49 366	97.25 203	74.43 312	99.88 71	71.14 432	94.09 220	98.67 192

ACMMP++															83.83 333

HQP-MVS		91.50 234	91.23 225	92.29 305	93.95 327	86.39 307	99.16 122	96.37 268	93.92 66	87.57 286	96.67 255	73.34 322	97.77 272	93.82 178	86.29 312	92.72 330

QAPM		91.41 237	89.49 264	97.17 72	95.66 235	93.42 84	98.60 208	97.51 155	80.92 411	81.39 368	97.41 189	72.89 331	99.87 75	82.33 350	98.68 113	98.21 229

Vis-MVSNet		92.64 206	91.85 210	95.03 211	95.12 267	88.23 254	98.48 227	96.81 231	91.61 128	92.16 214	97.22 206	71.58 344	98.00 255	85.85 300	97.81 140	98.88 159
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet		79.01 417	75.13 431	90.66 350	93.82 338	81.69 396	85.16 473	93.75 431	54.54 485	74.17 432	59.15 491	57.46 431	96.58 336	63.74 459	94.38 215	93.72 323

IS-MVSNet		93.00 196	92.51 187	94.49 235	96.14 215	87.36 285	98.31 255	95.70 349	88.58 243	90.17 255	97.50 183	83.02 195	97.22 310	87.06 275	96.07 187	98.90 158

HyFIR lowres test		93.68 165	93.29 163	94.87 215	97.57 137	88.04 259	98.18 268	98.47 26	87.57 284	91.24 235	95.05 299	85.49 148	97.46 300	93.22 197	92.82 242	99.10 134

EPMVS		92.59 209	91.59 217	95.59 176	97.22 157	90.03 188	91.78 447	98.04 57	90.42 168	91.66 224	90.65 394	86.49 131	97.46 300	81.78 358	96.31 177	99.28 117

PAPM_NR		95.43 101	95.05 108	96.57 111	99.42 52	90.14 180	98.58 213	97.51 155	90.65 157	92.44 208	98.90 98	87.77 96	99.90 61	90.88 229	99.32 70	99.68 67

TAMVS		92.62 207	92.09 204	94.20 252	94.10 322	87.68 268	98.41 238	96.97 225	87.53 286	89.74 266	96.04 275	84.77 166	96.49 343	88.97 258	92.31 258	98.42 208

PAPR		96.35 61	95.82 80	97.94 35	99.63 23	94.19 64	99.42 91	97.55 144	92.43 107	93.82 175	99.12 63	87.30 107	99.91 56	94.02 172	99.06 86	99.74 55

RPSCF		85.33 364	85.55 341	84.67 438	94.63 300	62.28 480	93.73 425	93.76 430	74.38 451	85.23 310	97.06 224	64.09 403	98.31 212	80.98 361	86.08 317	93.41 326

Vis-MVSNet (Re-imp)		93.26 185	93.00 174	94.06 258	96.14 215	86.71 299	98.68 189	96.70 238	88.30 256	89.71 268	97.64 175	85.43 151	96.39 348	88.06 267	96.32 176	99.08 139

test_0402		78.81 419	76.33 424	86.26 423	91.18 394	78.44 428	95.88 391	91.34 464	68.55 468	70.51 451	89.91 415	52.65 452	94.99 417	47.14 485	79.78 363	85.34 470

MVS_111021_HR		96.69 46	96.69 46	96.72 99	98.58 99	91.00 154	99.14 130	99.45 1	93.86 71	95.15 145	98.73 111	88.48 82	99.76 108	97.23 87	99.56 56	99.40 104

CSCG		94.87 122	94.71 114	95.36 185	99.54 41	86.49 303	99.34 102	98.15 43	82.71 385	90.15 256	99.25 32	89.48 69	99.86 81	94.97 150	98.82 102	99.72 59

PatchMatch-RL		91.47 235	90.54 245	94.26 247	98.20 108	86.36 309	96.94 350	97.14 206	87.75 278	88.98 275	95.75 284	71.80 341	99.40 149	80.92 363	97.39 154	97.02 278

API-MVS		94.78 125	94.18 128	96.59 108	99.21 68	90.06 187	98.80 170	97.78 90	83.59 367	93.85 172	99.21 40	83.79 178	99.97 25	92.37 211	99.00 90	99.74 55

Test By Simon												83.62 180

TDRefinement		78.01 426	75.31 429	86.10 425	70.06 491	73.84 454	93.59 428	91.58 461	74.51 450	73.08 442	91.04 381	49.63 464	97.12 313	74.88 406	59.47 466	87.33 453

USDC		84.74 370	82.93 376	90.16 364	91.73 386	83.54 371	95.00 407	93.30 438	88.77 237	73.19 439	93.30 332	53.62 449	97.65 289	75.88 400	81.54 351	89.30 433

EPP-MVSNet		93.75 162	93.67 151	94.01 261	95.86 226	85.70 336	98.67 192	97.66 115	84.46 352	91.36 233	97.18 210	91.16 37	97.79 270	92.93 202	93.75 229	98.53 202

PMMVS		93.62 168	93.90 143	92.79 293	96.79 183	81.40 399	98.85 164	96.81 231	91.25 141	96.82 103	98.15 152	77.02 284	98.13 230	93.15 200	96.30 178	98.83 166

PAPM		96.35 61	95.94 74	97.58 49	94.10 322	95.25 28	98.93 157	98.17 39	94.26 58	93.94 169	98.72 113	89.68 67	97.88 262	96.36 108	99.29 73	99.62 81

ACMMP		94.67 131	94.30 122	95.79 162	99.25 64	88.13 257	98.41 238	98.67 21	90.38 169	91.43 230	98.72 113	82.22 218	99.95 37	93.83 177	95.76 190	99.29 116
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		93.64 167	92.74 180	96.36 124	98.96 83	90.01 190	99.19 116	95.89 329	86.22 315	89.40 272	98.85 103	80.66 241	99.84 87	88.57 260	96.92 165	99.24 120

PatchmatchNet		92.05 225	91.04 230	95.06 208	96.17 212	89.04 220	91.26 455	97.26 190	89.56 203	90.64 244	90.56 400	88.35 84	97.11 314	79.53 371	96.07 187	99.03 143
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS		96.65 51	96.46 55	97.21 69	99.34 55	91.77 129	99.70 41	98.05 55	86.48 312	98.05 68	99.20 41	89.33 70	99.96 33	98.38 60	99.62 50	99.90 24

F-COLMAP		92.07 224	91.75 215	93.02 286	98.16 111	82.89 380	98.79 175	95.97 306	86.54 309	87.92 283	97.80 160	78.69 267	99.65 120	85.97 295	95.93 189	96.53 296

ANet_high		50.71 459	46.17 462	64.33 473	44.27 503	52.30 492	76.13 490	78.73 495	64.95 477	27.37 496	55.23 493	14.61 497	67.74 496	36.01 491	18.23 496	72.95 486

wuyk23d		16.71 466	16.73 470	16.65 482	60.15 498	25.22 507	41.24 495	5.17 506	6.56 499	5.48 502	3.61 502	3.64 503	22.72 501	15.20 499	9.52 499	1.99 499

OMC-MVS		93.90 156	93.62 152	94.73 222	98.63 98	87.00 294	98.04 289	96.56 252	92.19 118	92.46 207	98.73 111	79.49 253	99.14 169	92.16 213	94.34 218	98.03 240

MG-MVS		97.24 24	96.83 39	98.47 17	99.79 6	95.71 21	99.07 141	99.06 10	94.45 56	96.42 114	98.70 117	88.81 78	99.74 110	95.35 137	99.86 12	99.97 8

AdaColmap		93.82 160	93.06 169	96.10 144	99.88 1	89.07 219	98.33 252	97.55 144	86.81 302	90.39 252	98.65 120	75.09 306	99.98 13	93.32 190	97.53 150	99.26 119

uanet		0.00 470	0.00 473	0.00 485	0.00 508	0.00 510	0.00 496	0.00 509	0.00 503	0.00 504	0.00 503	0.00 507	0.00 504	0.00 502	0.00 502	0.00 500

ITE_SJBPF				87.93 404	92.26 371	76.44 443		93.47 437	87.67 283	79.95 384	95.49 291	56.50 434	97.38 305	75.24 403	82.33 348	89.98 424

DeepMVS_CX				76.08 460	90.74 400	51.65 493		90.84 466	86.47 313	57.89 481	87.98 429	35.88 483	92.60 449	65.77 455	65.06 450	83.97 476

TinyColmap		80.42 410	77.94 415	87.85 405	92.09 375	78.58 426	93.74 424	89.94 473	74.99 447	69.77 453	91.78 362	46.09 468	97.58 294	65.17 457	77.89 371	87.38 451

MAR-MVS		94.43 139	94.09 130	95.45 179	99.10 75	87.47 281	98.39 246	97.79 87	88.37 252	94.02 167	99.17 50	78.64 268	99.91 56	92.48 208	98.85 101	98.96 148
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		81.94 402	81.17 395	84.25 440	87.23 446	68.87 474	93.35 431	91.93 455	83.35 371	75.40 426	93.00 341	49.25 466	96.65 333	78.88 378	78.11 370	87.22 455

MSDG		88.29 315	86.37 328	94.04 260	96.90 177	86.15 322	96.52 366	94.36 421	77.89 428	79.22 395	96.95 231	69.72 354	99.59 126	73.20 421	92.58 252	96.37 303

LS3D		90.19 274	88.72 286	94.59 233	98.97 80	86.33 310	96.90 352	96.60 245	74.96 448	84.06 320	98.74 110	75.78 300	99.83 91	74.93 405	97.57 147	97.62 257

CLD-MVS		91.06 249	90.71 242	92.10 311	94.05 326	86.10 323	99.55 66	96.29 275	94.16 61	84.70 312	97.17 211	69.62 356	97.82 266	94.74 155	86.08 317	92.39 335
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS		61.57 450	60.32 453	65.34 472	60.14 499	42.44 500	91.02 458	89.72 475	44.15 488	42.63 491	80.93 473	19.02 492	80.59 491	42.50 487	72.76 415	73.00 485

Gipuma		54.77 457	52.22 461	62.40 476	86.50 449	59.37 484	50.20 494	90.35 472	36.52 492	41.20 493	49.49 494	18.33 494	81.29 487	32.10 492	65.34 449	46.54 494
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015

High-resolution multi-view benchmark