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 25	99.85 16	99.11 63	99.90 1	99.78 35	99.63 28	99.78 37	99.67 30	99.48 10	99.81 206	99.30 59	99.97 20	99.77 46
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	98.81 106	98.73 106	99.05 135	98.76 292	97.81 179	99.25 43	99.30 193	98.57 147	98.55 246	99.33 105	97.95 115	99.90 76	97.16 196	99.67 199	99.44 181

3Dnovator+	97.89 3	98.69 126	98.51 140	99.24 101	98.81 287	98.40 112	99.02 69	99.19 229	98.99 109	98.07 287	99.28 115	97.11 178	99.84 163	96.84 228	99.32 280	99.47 171

DeepC-MVS	97.60 4	98.97 84	98.93 85	99.10 122	99.35 168	97.98 157	98.01 191	99.46 122	97.56 227	99.54 73	99.50 67	98.97 27	99.84 163	98.06 144	99.92 65	99.49 153
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	98.32 184	98.01 211	99.23 103	98.39 354	98.97 72	95.03 399	99.18 233	96.88 288	99.33 119	98.78 242	98.16 98	99.28 403	96.74 236	99.62 213	99.44 181

DeepC-MVS_fast	96.85 6	98.30 187	98.15 196	98.75 185	98.61 325	97.23 215	97.76 230	99.09 252	97.31 255	98.75 218	98.66 264	97.56 146	99.64 314	96.10 288	99.55 240	99.39 201
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	97.09 291	96.68 302	98.32 250	98.32 357	97.16 224	98.86 89	99.37 156	89.48 423	96.29 385	99.15 152	96.56 211	99.90 76	92.90 376	99.20 302	97.89 395

ACMH	96.65 7	99.25 40	99.24 50	99.26 96	99.72 43	98.38 114	99.07 64	99.55 88	98.30 165	99.65 60	99.45 82	99.22 16	99.76 250	98.44 122	99.77 146	99.64 78
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMH+	96.62 9	99.08 71	99.00 79	99.33 84	99.71 47	98.83 82	98.60 112	99.58 70	99.11 88	99.53 77	99.18 142	98.81 37	99.67 295	96.71 241	99.77 146	99.50 148

COLMAP_ROB	96.50 10	98.99 80	98.85 95	99.41 65	99.58 84	99.10 64	98.74 95	99.56 84	99.09 98	99.33 119	99.19 138	98.40 73	99.72 274	95.98 291	99.76 158	99.42 188
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	96.63 313	95.95 324	98.65 197	98.93 258	98.09 141	96.93 309	99.28 205	83.58 436	98.13 282	97.78 346	96.13 229	99.40 384	93.52 365	99.29 287	98.45 361
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMM	96.08 12	98.91 91	98.73 106	99.48 55	99.55 101	99.14 56	98.07 179	99.37 156	97.62 218	99.04 166	98.96 204	98.84 35	99.79 227	97.43 183	99.65 205	99.49 153
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
HY-MVS	95.94 13	95.90 336	95.35 346	97.55 315	97.95 377	94.79 313	98.81 94	96.94 382	92.28 402	95.17 407	98.57 280	89.90 351	99.75 257	91.20 405	97.33 408	98.10 384

OpenMVS_ROB	95.38 14	95.84 339	95.18 352	97.81 287	98.41 353	97.15 225	97.37 278	98.62 324	83.86 435	98.65 229	98.37 304	94.29 292	99.68 292	88.41 420	98.62 360	96.60 426

ACMP	95.32 15	98.41 170	98.09 201	99.36 69	99.51 113	98.79 85	97.68 239	99.38 152	95.76 334	98.81 211	98.82 235	98.36 75	99.82 191	94.75 327	99.77 146	99.48 163
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PLC	94.65 16	96.51 316	95.73 328	98.85 165	98.75 294	97.91 166	96.42 337	99.06 255	90.94 416	95.59 396	97.38 370	94.41 287	99.59 332	90.93 409	98.04 387	99.05 280
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
PVSNet	93.40 17	95.67 343	95.70 329	95.57 390	98.83 281	88.57 417	92.50 433	97.72 356	92.69 397	96.49 382	96.44 391	93.72 305	99.43 380	93.61 362	99.28 288	98.71 338

PCF-MVS	92.86 18	94.36 365	93.00 383	98.42 238	98.70 305	97.56 195	93.16 431	99.11 249	79.59 440	97.55 324	97.43 367	92.19 328	99.73 267	79.85 439	99.45 263	97.97 392
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
IB-MVS	91.63 19	92.24 401	90.90 405	96.27 371	97.22 415	91.24 399	94.36 418	93.33 426	92.37 400	92.24 435	94.58 426	66.20 439	99.89 91	93.16 373	94.63 433	97.66 408
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	97.86 230	97.94 219	97.65 303	99.71 47	97.94 163	98.52 121	98.68 319	98.99 109	97.52 327	99.35 99	97.41 160	98.18 434	91.59 398	99.67 199	96.82 423
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PVSNet_0	89.98 21	91.15 406	90.30 409	93.70 414	97.72 387	84.34 438	90.24 437	97.42 364	90.20 420	93.79 426	93.09 435	90.90 344	98.89 423	86.57 428	72.76 444	97.87 397

MVE	83.40 22	92.50 396	91.92 398	94.25 406	98.83 281	91.64 388	92.71 432	83.52 446	95.92 330	86.46 444	95.46 412	95.20 265	95.40 442	80.51 438	98.64 357	95.73 435
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CMPMVS	75.91 23	96.29 324	95.44 341	98.84 166	96.25 435	98.69 93	97.02 302	99.12 247	88.90 426	97.83 305	98.86 226	89.51 353	98.90 422	91.92 390	99.51 251	98.92 306
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
ElysianMVS		99.15 54	99.14 64	99.18 108	99.63 78	97.92 164	98.50 128	99.43 136	99.67 20	99.70 48	99.13 157	96.66 206	99.98 4	99.54 40	99.96 27	99.64 78

StellarMVS		99.15 54	99.14 64	99.18 108	99.63 78	97.92 164	98.50 128	99.43 136	99.67 20	99.70 48	99.13 157	96.66 206	99.98 4	99.54 40	99.96 27	99.64 78

KinetiMVS		99.03 75	99.02 76	99.03 138	99.70 55	97.48 200	98.43 139	99.29 201	99.70 15	99.60 67	99.07 169	96.13 229	99.94 41	99.42 52	99.87 93	99.68 66

LuminaMVS		98.39 178	98.20 187	98.98 148	99.50 118	97.49 198	97.78 224	97.69 358	98.75 129	99.49 86	99.25 127	92.30 327	99.94 41	99.14 72	99.88 89	99.50 148

VortexMVS		97.98 220	98.31 174	97.02 343	98.88 272	91.45 391	98.03 185	99.47 118	98.65 134	99.55 71	99.47 76	91.49 337	99.81 206	99.32 57	99.91 74	99.80 38

AstraMVS		98.16 206	98.07 206	98.41 239	99.51 113	95.86 277	98.00 192	95.14 411	98.97 112	99.43 97	99.24 128	93.25 307	99.84 163	99.21 67	99.87 93	99.54 130

guyue		98.01 215	97.93 221	98.26 256	99.45 143	95.48 290	98.08 176	96.24 394	98.89 121	99.34 117	99.14 155	91.32 339	99.82 191	99.07 77	99.83 111	99.48 163

sc_t1		99.62 7	99.66 8	99.53 37	99.82 19	99.09 67	99.50 11	99.63 61	99.88 4	99.86 22	99.80 11	99.03 23	99.89 91	99.48 49	99.93 53	99.60 94

tt0320-xc		99.64 5	99.68 5	99.50 52	99.72 43	98.98 70	99.51 10	99.85 18	99.86 6	99.88 19	99.82 5	99.02 25	99.90 76	99.54 40	99.95 37	99.61 92

tt0320		99.61 8	99.65 9	99.48 55	99.71 47	98.94 77	99.54 8	99.83 25	99.87 5	99.89 16	99.82 5	98.75 43	99.90 76	99.54 40	99.95 37	99.59 101

fmvsm_s_conf0.5_n_8		99.13 61	99.26 47	98.74 189	99.51 113	96.44 257	97.65 245	99.65 58	99.66 23	99.78 37	99.48 74	97.92 117	99.93 50	99.72 26	99.95 37	99.87 20

fmvsm_s_conf0.5_n_7		98.83 101	99.04 75	98.20 261	99.30 177	94.83 312	97.23 289	99.36 160	98.64 135	99.84 28	99.43 85	98.10 103	99.91 69	99.56 37	99.96 27	99.87 20

fmvsm_s_conf0.5_n_6		99.08 71	99.21 53	98.69 193	99.36 163	96.51 255	97.62 250	99.68 53	98.43 156	99.85 25	99.10 164	99.12 22	99.88 106	99.77 19	99.92 65	99.67 70

fmvsm_s_conf0.5_n_5		99.07 73	99.10 68	98.99 144	99.47 136	97.22 217	97.40 274	99.83 25	97.61 221	99.85 25	99.30 111	98.80 39	99.95 26	99.71 28	99.90 81	99.78 43

fmvsm_s_conf0.5_n_4		99.01 77	99.22 51	98.38 243	99.31 173	95.48 290	97.56 259	99.73 41	98.87 122	99.75 42	99.27 117	98.80 39	99.86 132	99.80 14	99.90 81	99.81 36

SSC-MVS3.2		98.53 157	98.79 100	97.74 296	99.46 138	93.62 358	96.45 333	99.34 172	99.33 62	98.93 189	98.70 255	97.90 118	99.90 76	99.12 73	99.92 65	99.69 65

testing3-2		93.78 377	93.91 369	93.39 418	98.82 284	81.72 445	97.76 230	95.28 409	98.60 142	96.54 376	96.66 385	65.85 441	99.62 320	96.65 245	98.99 330	98.82 319

myMVS_eth3d28		92.92 392	92.31 388	94.77 401	97.84 382	87.59 424	96.19 351	96.11 397	97.08 277	94.27 417	93.49 433	66.07 440	98.78 425	91.78 393	97.93 390	97.92 394

UWE-MVS-28		90.22 407	89.28 410	93.02 422	94.50 443	82.87 441	96.52 330	87.51 441	95.21 351	92.36 434	96.04 396	71.57 427	98.25 433	72.04 443	97.77 392	97.94 393

fmvsm_l_conf0.5_n_3		99.45 18	99.48 18	99.34 78	99.59 83	98.21 131	97.82 218	99.84 22	99.41 54	99.92 8	99.41 90	99.51 8	99.95 26	99.84 7	99.97 20	99.87 20

fmvsm_s_conf0.5_n_3		99.22 45	99.37 30	98.78 178	99.46 138	96.58 253	97.65 245	99.72 42	99.47 44	99.86 22	99.50 67	98.94 29	99.89 91	99.75 22	99.97 20	99.86 26

fmvsm_s_conf0.5_n_2		99.14 57	99.31 39	98.63 203	99.49 126	96.08 270	97.38 276	99.81 30	99.48 41	99.84 28	99.57 49	98.46 69	99.89 91	99.82 9	99.97 20	99.91 13

fmvsm_s_conf0.1_n_2		99.20 48	99.38 28	98.65 197	99.69 58	96.08 270	97.49 268	99.90 11	99.53 38	99.88 19	99.64 37	98.51 65	99.90 76	99.83 8	99.98 12	99.97 4

GDP-MVS		97.50 256	97.11 275	98.67 196	99.02 245	96.85 239	98.16 165	99.71 44	98.32 163	98.52 251	98.54 282	83.39 397	99.95 26	98.79 97	99.56 236	99.19 261

BP-MVS1		97.40 268	96.97 281	98.71 192	99.07 232	96.81 241	98.34 150	97.18 372	98.58 146	98.17 275	98.61 275	84.01 393	99.94 41	98.97 86	99.78 140	99.37 210

reproduce_monomvs		95.00 359	95.25 348	94.22 407	97.51 407	83.34 439	97.86 214	98.44 332	98.51 152	99.29 128	99.30 111	67.68 434	99.56 343	98.89 92	99.81 119	99.77 46

mmtdpeth		99.30 33	99.42 24	98.92 158	99.58 84	96.89 238	99.48 13	99.92 7	99.92 2	98.26 272	99.80 11	98.33 80	99.91 69	99.56 37	99.95 37	99.97 4

reproduce_model		99.15 54	98.97 83	99.67 4	99.33 171	99.44 10	98.15 166	99.47 118	99.12 87	99.52 79	99.32 109	98.31 81	99.90 76	97.78 163	99.73 165	99.66 72

reproduce-ours		99.09 67	98.90 88	99.67 4	99.27 183	99.49 6	98.00 192	99.42 141	99.05 103	99.48 87	99.27 117	98.29 83	99.89 91	97.61 173	99.71 178	99.62 84

our_new_method		99.09 67	98.90 88	99.67 4	99.27 183	99.49 6	98.00 192	99.42 141	99.05 103	99.48 87	99.27 117	98.29 83	99.89 91	97.61 173	99.71 178	99.62 84

mmdepth		0.00 418	0.00 421	0.00 431	0.00 454	0.00 456	0.00 442	0.00 455	0.00 449	0.00 450	0.00 449	0.00 454	0.00 450	0.00 449	0.00 448	0.00 446

monomultidepth		0.00 418	0.00 421	0.00 431	0.00 454	0.00 456	0.00 442	0.00 455	0.00 449	0.00 450	0.00 449	0.00 454	0.00 450	0.00 449	0.00 448	0.00 446

mvs5depth		99.30 33	99.59 12	98.44 236	99.65 68	95.35 296	99.82 3	99.94 2	99.83 7	99.42 101	99.94 2	98.13 101	99.96 14	99.63 32	99.96 27	100.00 1

MVStest1		95.86 337	95.60 333	96.63 361	95.87 439	91.70 387	97.93 202	98.94 274	98.03 188	99.56 68	99.66 32	71.83 426	98.26 432	99.35 55	99.24 294	99.91 13

ttmdpeth		97.91 222	98.02 210	97.58 310	98.69 310	94.10 335	98.13 168	98.90 283	97.95 194	97.32 342	99.58 47	95.95 244	98.75 426	96.41 268	99.22 298	99.87 20

WBMVS		95.18 354	94.78 360	96.37 367	97.68 395	89.74 414	95.80 375	98.73 316	97.54 230	98.30 266	98.44 297	70.06 428	99.82 191	96.62 247	99.87 93	99.54 130

dongtai		76.24 411	75.95 414	77.12 427	92.39 445	67.91 451	90.16 438	59.44 452	82.04 438	89.42 440	94.67 425	49.68 450	81.74 445	48.06 445	77.66 443	81.72 441

kuosan		69.30 412	68.95 415	70.34 428	87.68 449	65.00 452	91.11 436	59.90 451	69.02 441	74.46 446	88.89 443	48.58 451	68.03 447	28.61 446	72.33 445	77.99 442

MVSMamba_PlusPlus		98.83 101	98.98 82	98.36 247	99.32 172	96.58 253	98.90 83	99.41 145	99.75 11	98.72 221	99.50 67	96.17 227	99.94 41	99.27 61	99.78 140	98.57 354

MGCFI-Net		98.34 180	98.28 177	98.51 226	98.47 343	97.59 194	98.96 77	99.48 110	99.18 83	97.40 337	95.50 409	98.66 51	99.50 364	98.18 135	98.71 350	98.44 364

testing91		93.32 384	92.27 389	96.47 365	97.54 400	91.25 398	96.17 355	96.76 386	97.18 271	93.65 428	93.50 432	65.11 443	99.63 317	93.04 374	97.45 399	98.53 355

testing11		93.08 389	92.02 394	96.26 372	97.56 398	90.83 406	96.32 343	95.70 405	96.47 308	92.66 432	93.73 429	64.36 444	99.59 332	93.77 360	97.57 395	98.37 373

testing99		93.04 390	91.98 397	96.23 374	97.53 402	90.70 408	96.35 341	95.94 401	96.87 289	93.41 429	93.43 434	63.84 445	99.59 332	93.24 372	97.19 409	98.40 369

UBG		93.25 386	92.32 387	96.04 381	97.72 387	90.16 411	95.92 369	95.91 402	96.03 325	93.95 425	93.04 436	69.60 430	99.52 358	90.72 413	97.98 388	98.45 361

UWE-MVS		92.38 398	91.76 401	94.21 408	97.16 416	84.65 434	95.42 389	88.45 440	95.96 328	96.17 386	95.84 404	66.36 437	99.71 275	91.87 392	98.64 357	98.28 376

ETVMVS		92.60 395	91.08 404	97.18 335	97.70 392	93.65 357	96.54 327	95.70 405	96.51 304	94.68 413	92.39 439	61.80 446	99.50 364	86.97 425	97.41 402	98.40 369

sasdasda		98.34 180	98.26 181	98.58 212	98.46 345	97.82 176	98.96 77	99.46 122	99.19 81	97.46 332	95.46 412	98.59 58	99.46 375	98.08 142	98.71 350	98.46 358

testing222		91.96 403	90.37 407	96.72 360	97.47 409	92.59 373	96.11 357	94.76 413	96.83 291	92.90 431	92.87 437	57.92 447	99.55 347	86.93 426	97.52 396	98.00 391

WB-MVSnew		95.73 342	95.57 336	96.23 374	96.70 426	90.70 408	96.07 359	93.86 423	95.60 338	97.04 351	95.45 415	96.00 236	99.55 347	91.04 407	98.31 369	98.43 366

fmvsm_l_conf0.5_n_a		99.19 49	99.27 45	98.94 153	99.65 68	97.05 227	97.80 222	99.76 37	98.70 133	99.78 37	99.11 161	98.79 41	99.95 26	99.85 5	99.96 27	99.83 30

fmvsm_l_conf0.5_n		99.21 46	99.28 44	99.02 141	99.64 74	97.28 212	97.82 218	99.76 37	98.73 130	99.82 31	99.09 168	98.81 37	99.95 26	99.86 4	99.96 27	99.83 30

fmvsm_s_conf0.1_n_a		99.17 50	99.30 42	98.80 172	99.75 34	96.59 251	97.97 201	99.86 16	98.22 173	99.88 19	99.71 22	98.59 58	99.84 163	99.73 24	99.98 12	99.98 3

fmvsm_s_conf0.1_n		99.16 53	99.33 35	98.64 199	99.71 47	96.10 265	97.87 213	99.85 18	98.56 150	99.90 13	99.68 25	98.69 49	99.85 145	99.72 26	99.98 12	99.97 4

fmvsm_s_conf0.5_n_a		99.10 66	99.20 54	98.78 178	99.55 101	96.59 251	97.79 223	99.82 29	98.21 174	99.81 34	99.53 63	98.46 69	99.84 163	99.70 29	99.97 20	99.90 15

fmvsm_s_conf0.5_n		99.09 67	99.26 47	98.61 208	99.55 101	96.09 268	97.74 233	99.81 30	98.55 151	99.85 25	99.55 57	98.60 57	99.84 163	99.69 31	99.98 12	99.89 16

MM		98.22 197	97.99 213	98.91 159	98.66 320	96.97 231	97.89 209	94.44 416	99.54 37	98.95 181	99.14 155	93.50 306	99.92 60	99.80 14	99.96 27	99.85 28

WAC-MVS						90.90 404								91.37 402

Syy-MVS		96.04 331	95.56 337	97.49 321	97.10 418	94.48 324	96.18 353	96.58 389	95.65 336	94.77 411	92.29 440	91.27 340	99.36 389	98.17 137	98.05 385	98.63 348

test_fmvsmconf0.1_n		99.49 15	99.54 14	99.34 78	99.78 24	98.11 138	97.77 227	99.90 11	99.33 62	99.97 3	99.66 32	99.71 3	99.96 14	99.79 16	99.99 5	99.96 8

test_fmvsmconf0.01_n		99.57 10	99.63 10	99.36 69	99.87 12	98.13 137	98.08 176	99.95 1	99.45 47	99.98 2	99.75 16	99.80 1	99.97 7	99.82 9	99.99 5	99.99 2

myMVS_eth3d		91.92 404	90.45 406	96.30 369	97.10 418	90.90 404	96.18 353	96.58 389	95.65 336	94.77 411	92.29 440	53.88 448	99.36 389	89.59 418	98.05 385	98.63 348

testing3		93.51 381	92.09 392	97.75 294	98.60 327	94.40 326	97.32 282	95.26 410	97.56 227	96.79 368	95.50 409	53.57 449	99.77 244	95.26 317	98.97 334	99.08 276

SSC-MVS		98.71 119	98.74 104	98.62 205	99.72 43	96.08 270	98.74 95	98.64 323	99.74 13	99.67 56	99.24 128	94.57 284	99.95 26	99.11 74	99.24 294	99.82 33

test_fmvsmconf_n		99.44 19	99.48 18	99.31 89	99.64 74	98.10 140	97.68 239	99.84 22	99.29 68	99.92 8	99.57 49	99.60 5	99.96 14	99.74 23	99.98 12	99.89 16

WB-MVS		98.52 161	98.55 135	98.43 237	99.65 68	95.59 283	98.52 121	98.77 309	99.65 25	99.52 79	99.00 194	94.34 290	99.93 50	98.65 110	98.83 342	99.76 51

test_fmvsmvis_n_1920		99.26 39	99.49 16	98.54 223	99.66 67	96.97 231	98.00 192	99.85 18	99.24 72	99.92 8	99.50 67	99.39 12	99.95 26	99.89 3	99.98 12	98.71 338

dmvs_re		95.98 334	95.39 344	97.74 296	98.86 275	97.45 203	98.37 146	95.69 407	97.95 194	96.56 375	95.95 399	90.70 345	97.68 437	88.32 421	96.13 424	98.11 383

SDMVSNet		99.23 44	99.32 37	98.96 150	99.68 61	97.35 208	98.84 92	99.48 110	99.69 17	99.63 63	99.68 25	99.03 23	99.96 14	97.97 151	99.92 65	99.57 113

dmvs_testset		92.94 391	92.21 391	95.13 398	98.59 330	90.99 403	97.65 245	92.09 431	96.95 284	94.00 423	93.55 431	92.34 326	96.97 440	72.20 442	92.52 438	97.43 415

sd_testset		99.28 36	99.31 39	99.19 107	99.68 61	98.06 150	99.41 17	99.30 193	99.69 17	99.63 63	99.68 25	99.25 15	99.96 14	97.25 192	99.92 65	99.57 113

test_fmvsm_n_1920		99.33 31	99.45 23	98.99 144	99.57 89	97.73 186	97.93 202	99.83 25	99.22 73	99.93 6	99.30 111	99.42 11	99.96 14	99.85 5	99.99 5	99.29 239

test_cas_vis1_n_1920		98.33 183	98.68 117	97.27 332	99.69 58	92.29 381	98.03 185	99.85 18	97.62 218	99.96 4	99.62 40	93.98 299	99.74 262	99.52 46	99.86 99	99.79 40

test_vis1_n_1920		98.40 172	98.92 86	96.81 356	99.74 36	90.76 407	98.15 166	99.91 9	98.33 161	99.89 16	99.55 57	95.07 269	99.88 106	99.76 20	99.93 53	99.79 40

test_vis1_n		98.31 186	98.50 142	97.73 299	99.76 30	94.17 333	98.68 105	99.91 9	96.31 314	99.79 36	99.57 49	92.85 319	99.42 382	99.79 16	99.84 104	99.60 94

test_fmvs1_n		98.09 209	98.28 177	97.52 318	99.68 61	93.47 360	98.63 108	99.93 5	95.41 347	99.68 54	99.64 37	91.88 333	99.48 370	99.82 9	99.87 93	99.62 84

mvsany_test1		97.60 250	97.54 248	97.77 290	97.72 387	95.35 296	95.36 391	97.13 375	94.13 376	99.71 46	99.33 105	97.93 116	99.30 399	97.60 175	98.94 337	98.67 346

APD_test1		98.83 101	98.66 120	99.34 78	99.78 24	99.47 9	98.42 142	99.45 126	98.28 170	98.98 173	99.19 138	97.76 129	99.58 338	96.57 252	99.55 240	98.97 297

test_vis1_rt		97.75 240	97.72 236	97.83 285	98.81 287	96.35 260	97.30 284	99.69 48	94.61 363	97.87 301	98.05 331	96.26 225	98.32 431	98.74 103	98.18 374	98.82 319

test_vis3_rt		99.14 57	99.17 56	99.07 128	99.78 24	98.38 114	98.92 82	99.94 2	97.80 207	99.91 12	99.67 30	97.15 175	98.91 421	99.76 20	99.56 236	99.92 12

test_fmvs2		98.70 123	98.97 83	97.89 282	99.54 106	94.05 336	98.55 117	99.92 7	96.78 294	99.72 44	99.78 13	96.60 210	99.67 295	99.91 2	99.90 81	99.94 10

test_fmvs1		97.72 242	97.94 219	97.07 342	98.66 320	92.39 378	97.68 239	99.81 30	95.20 352	99.54 73	99.44 83	91.56 336	99.41 383	99.78 18	99.77 146	99.40 200

test_fmvs3		99.12 64	99.41 25	98.25 257	99.76 30	95.07 308	99.05 67	99.94 2	97.78 209	99.82 31	99.84 3	98.56 62	99.71 275	99.96 1	99.96 27	99.97 4

mvsany_test3		98.87 96	98.92 86	98.74 189	99.38 156	96.94 235	98.58 114	99.10 250	96.49 306	99.96 4	99.81 8	98.18 94	99.45 377	98.97 86	99.79 135	99.83 30

testf1		99.25 40	99.16 58	99.51 47	99.89 6	99.63 4	98.71 102	99.69 48	98.90 119	99.43 97	99.35 99	98.86 33	99.67 295	97.81 160	99.81 119	99.24 249

APD_test2		99.25 40	99.16 58	99.51 47	99.89 6	99.63 4	98.71 102	99.69 48	98.90 119	99.43 97	99.35 99	98.86 33	99.67 295	97.81 160	99.81 119	99.24 249

test_f		98.67 134	98.87 91	98.05 275	99.72 43	95.59 283	98.51 126	99.81 30	96.30 316	99.78 37	99.82 5	96.14 228	98.63 428	99.82 9	99.93 53	99.95 9

FE-MVS		95.66 344	94.95 357	97.77 290	98.53 339	95.28 299	99.40 19	96.09 398	93.11 391	97.96 295	99.26 122	79.10 415	99.77 244	92.40 388	98.71 350	98.27 377

FA-MVS(test-final)		96.99 300	96.82 293	97.50 320	98.70 305	94.78 314	99.34 23	96.99 378	95.07 353	98.48 254	99.33 105	88.41 364	99.65 311	96.13 287	98.92 339	98.07 386

balanced_conf03		98.63 140	98.72 108	98.38 243	98.66 320	96.68 250	98.90 83	99.42 141	98.99 109	98.97 177	99.19 138	95.81 249	99.85 145	98.77 101	99.77 146	98.60 350

MonoMVSNet		96.25 326	96.53 313	95.39 395	96.57 428	91.01 402	98.82 93	97.68 360	98.57 147	98.03 292	99.37 94	90.92 343	97.78 436	94.99 321	93.88 436	97.38 416

patch_mono-2		98.51 162	98.63 124	98.17 264	99.38 156	94.78 314	97.36 279	99.69 48	98.16 184	98.49 253	99.29 114	97.06 179	99.97 7	98.29 130	99.91 74	99.76 51

EGC-MVSNET		85.24 408	80.54 411	99.34 78	99.77 27	99.20 38	99.08 61	99.29 201	12.08 446	20.84 447	99.42 86	97.55 147	99.85 145	97.08 204	99.72 173	98.96 299

test2506		92.39 397	91.89 399	93.89 412	99.38 156	82.28 443	99.32 26	66.03 450	99.08 100	98.77 215	99.57 49	66.26 438	99.84 163	98.71 106	99.95 37	99.54 130

test1111		96.49 319	96.82 293	95.52 391	99.42 151	87.08 426	99.22 45	87.14 442	99.11 88	99.46 92	99.58 47	88.69 358	99.86 132	98.80 96	99.95 37	99.62 84

ECVR-MVS		96.42 321	96.61 307	95.85 383	99.38 156	88.18 421	99.22 45	86.00 444	99.08 100	99.36 113	99.57 49	88.47 363	99.82 191	98.52 119	99.95 37	99.54 130

test_blank		0.00 418	0.00 421	0.00 431	0.00 454	0.00 456	0.00 442	0.00 455	0.00 449	0.00 450	0.00 449	0.00 454	0.00 450	0.00 449	0.00 448	0.00 446

tt0805		98.69 126	98.62 126	98.90 162	99.75 34	99.30 21	99.15 56	96.97 379	98.86 124	98.87 202	97.62 357	98.63 54	98.96 418	99.41 53	98.29 370	98.45 361

DVP-MVS++		98.90 93	98.70 114	99.51 47	98.43 349	99.15 51	99.43 15	99.32 180	98.17 181	99.26 135	99.02 182	98.18 94	99.88 106	97.07 205	99.45 263	99.49 153

FOURS1					99.73 37	99.67 3	99.43 15	99.54 92	99.43 51	99.26 135

MSC_two_6792asdad				99.32 86	98.43 349	98.37 116		98.86 294					99.89 91	97.14 199	99.60 220	99.71 58

PC_three_1452									93.27 388	99.40 106	98.54 282	98.22 90	97.00 439	95.17 318	99.45 263	99.49 153

No_MVS				99.32 86	98.43 349	98.37 116		98.86 294					99.89 91	97.14 199	99.60 220	99.71 58

test_one_0601					99.39 155	99.20 38		99.31 185	98.49 153	98.66 228	99.02 182	97.64 139

eth-test2					0.00 454

eth-test					0.00 454

GeoE		99.05 74	98.99 81	99.25 99	99.44 145	98.35 120	98.73 99	99.56 84	98.42 157	98.91 192	98.81 237	98.94 29	99.91 69	98.35 126	99.73 165	99.49 153

test_method		79.78 409	79.50 412	80.62 425	80.21 450	45.76 453	70.82 441	98.41 336	31.08 445	80.89 445	97.71 350	84.85 384	97.37 438	91.51 400	80.03 442	98.75 335

Anonymous20240521		98.69 126	98.87 91	98.16 266	99.77 27	95.11 307	99.08 61	99.44 130	99.34 61	99.33 119	99.55 57	94.10 298	99.94 41	99.25 64	99.96 27	99.42 188

h-mvs33		97.77 239	97.33 263	99.10 122	99.21 197	97.84 172	98.35 148	98.57 326	99.11 88	98.58 241	99.02 182	88.65 361	99.96 14	98.11 139	96.34 420	99.49 153

hse-mvs2		97.46 261	97.07 276	98.64 199	98.73 296	97.33 209	97.45 272	97.64 363	99.11 88	98.58 241	97.98 335	88.65 361	99.79 227	98.11 139	97.39 403	98.81 324

CL-MVSNet_self_test		97.44 264	97.22 268	98.08 271	98.57 334	95.78 281	94.30 419	98.79 306	96.58 303	98.60 237	98.19 320	94.74 282	99.64 314	96.41 268	98.84 341	98.82 319

KD-MVS_2432*1600		92.87 393	91.99 395	95.51 392	91.37 446	89.27 415	94.07 421	98.14 346	95.42 344	97.25 344	96.44 391	67.86 432	99.24 405	91.28 403	96.08 425	98.02 388

KD-MVS_self_test		99.25 40	99.18 55	99.44 62	99.63 78	99.06 69	98.69 104	99.54 92	99.31 65	99.62 66	99.53 63	97.36 163	99.86 132	99.24 66	99.71 178	99.39 201

AUN-MVS		96.24 328	95.45 340	98.60 210	98.70 305	97.22 217	97.38 276	97.65 361	95.95 329	95.53 403	97.96 339	82.11 405	99.79 227	96.31 274	97.44 400	98.80 329

ZD-MVS					99.01 246	98.84 81		99.07 254	94.10 377	98.05 290	98.12 324	96.36 222	99.86 132	92.70 384	99.19 305

SR-MVS-dyc-post		98.81 106	98.55 135	99.57 20	99.20 201	99.38 12	98.48 134	99.30 193	98.64 135	98.95 181	98.96 204	97.49 157	99.86 132	96.56 256	99.39 270	99.45 177

RE-MVS-def			98.58 133		99.20 201	99.38 12	98.48 134	99.30 193	98.64 135	98.95 181	98.96 204	97.75 130		96.56 256	99.39 270	99.45 177

SED-MVS		98.91 91	98.72 108	99.49 53	99.49 126	99.17 43	98.10 174	99.31 185	98.03 188	99.66 57	99.02 182	98.36 75	99.88 106	96.91 217	99.62 213	99.41 191

IU-MVS					99.49 126	99.15 51		98.87 289	92.97 392	99.41 103				96.76 234	99.62 213	99.66 72

OPU-MVS				98.82 168	98.59 330	98.30 121	98.10 174				98.52 286	98.18 94	98.75 426	94.62 331	99.48 260	99.41 191

test_241102_TWO								99.30 193	98.03 188	99.26 135	99.02 182	97.51 153	99.88 106	96.91 217	99.60 220	99.66 72

test_241102_ONE					99.49 126	99.17 43		99.31 185	97.98 191	99.66 57	98.90 216	98.36 75	99.48 370

SF-MVS		98.53 157	98.27 180	99.32 86	99.31 173	98.75 86	98.19 160	99.41 145	96.77 295	98.83 206	98.90 216	97.80 127	99.82 191	95.68 307	99.52 249	99.38 208

cl22		95.79 340	95.39 344	96.98 346	96.77 425	92.79 370	94.40 417	98.53 328	94.59 364	97.89 299	98.17 321	82.82 402	99.24 405	96.37 270	99.03 323	98.92 306

miper_ehance_all_eth		97.06 293	97.03 278	97.16 339	97.83 383	93.06 364	94.66 409	99.09 252	95.99 327	98.69 223	98.45 296	92.73 322	99.61 327	96.79 230	99.03 323	98.82 319

miper_enhance_ethall		96.01 332	95.74 327	96.81 356	96.41 433	92.27 382	93.69 428	98.89 286	91.14 414	98.30 266	97.35 373	90.58 346	99.58 338	96.31 274	99.03 323	98.60 350

ZNCC-MVS		98.68 131	98.40 159	99.54 30	99.57 89	99.21 32	98.46 136	99.29 201	97.28 258	98.11 284	98.39 301	98.00 110	99.87 124	96.86 227	99.64 207	99.55 126

dcpmvs_2		98.78 110	99.11 66	97.78 289	99.56 97	93.67 355	99.06 65	99.86 16	99.50 40	99.66 57	99.26 122	97.21 173	99.99 2	98.00 149	99.91 74	99.68 66

cl____		97.02 296	96.83 292	97.58 310	97.82 384	94.04 338	94.66 409	99.16 240	97.04 279	98.63 231	98.71 252	88.68 360	99.69 283	97.00 209	99.81 119	99.00 292

DIV-MVS_self_test		97.02 296	96.84 291	97.58 310	97.82 384	94.03 339	94.66 409	99.16 240	97.04 279	98.63 231	98.71 252	88.69 358	99.69 283	97.00 209	99.81 119	99.01 288

eth_miper_zixun_eth		97.23 282	97.25 266	97.17 337	98.00 376	92.77 371	94.71 406	99.18 233	97.27 259	98.56 244	98.74 248	91.89 332	99.69 283	97.06 207	99.81 119	99.05 280

9.14			97.78 230		99.07 232		97.53 263	99.32 180	95.53 341	98.54 248	98.70 255	97.58 144	99.76 250	94.32 344	99.46 261

uanet_test		0.00 418	0.00 421	0.00 431	0.00 454	0.00 456	0.00 442	0.00 455	0.00 449	0.00 450	0.00 449	0.00 454	0.00 450	0.00 449	0.00 448	0.00 446

DCPMVS		0.00 418	0.00 421	0.00 431	0.00 454	0.00 456	0.00 442	0.00 455	0.00 449	0.00 450	0.00 449	0.00 454	0.00 450	0.00 449	0.00 448	0.00 446

save fliter					99.11 223	97.97 158	96.53 329	99.02 266	98.24 171

ET-MVSNet_ETH3D		94.30 368	93.21 379	97.58 310	98.14 369	94.47 325	94.78 405	93.24 427	94.72 361	89.56 439	95.87 402	78.57 418	99.81 206	96.91 217	97.11 412	98.46 358

UniMVSNet_ETH3D		99.69 2	99.69 4	99.69 3	99.84 17	99.34 19	99.69 5	99.58 70	99.90 3	99.86 22	99.78 13	99.58 6	99.95 26	99.00 84	99.95 37	99.78 43

EIA-MVS		98.00 216	97.74 233	98.80 172	98.72 298	98.09 141	98.05 182	99.60 67	97.39 247	96.63 372	95.55 407	97.68 133	99.80 214	96.73 238	99.27 289	98.52 356

miper_refine_blended		92.87 393	91.99 395	95.51 392	91.37 446	89.27 415	94.07 421	98.14 346	95.42 344	97.25 344	96.44 391	67.86 432	99.24 405	91.28 403	96.08 425	98.02 388

miper_lstm_enhance		97.18 286	97.16 271	97.25 334	98.16 367	92.85 369	95.15 397	99.31 185	97.25 261	98.74 220	98.78 242	90.07 349	99.78 238	97.19 194	99.80 130	99.11 275

ETV-MVS		98.03 212	97.86 227	98.56 219	98.69 310	98.07 147	97.51 266	99.50 101	98.10 186	97.50 329	95.51 408	98.41 72	99.88 106	96.27 277	99.24 294	97.71 407

CS-MVS		99.13 61	99.10 68	99.24 101	99.06 237	99.15 51	99.36 22	99.88 14	99.36 60	98.21 274	98.46 295	98.68 50	99.93 50	99.03 82	99.85 100	98.64 347

D2MVS		97.84 236	97.84 228	97.83 285	99.14 219	94.74 316	96.94 307	98.88 287	95.84 332	98.89 195	98.96 204	94.40 288	99.69 283	97.55 176	99.95 37	99.05 280

DVP-MVS		98.77 113	98.52 139	99.52 43	99.50 118	99.21 32	98.02 188	98.84 298	97.97 192	99.08 157	99.02 182	97.61 142	99.88 106	96.99 211	99.63 210	99.48 163
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									98.17 181	99.08 157	99.02 182	97.89 119	99.88 106	97.07 205	99.71 178	99.70 63

test_0728_SECOND				99.60 14	99.50 118	99.23 30	98.02 188	99.32 180					99.88 106	96.99 211	99.63 210	99.68 66

test0726					99.50 118	99.21 32	98.17 164	99.35 166	97.97 192	99.26 135	99.06 170	97.61 142

SR-MVS		98.71 119	98.43 155	99.57 20	99.18 211	99.35 16	98.36 147	99.29 201	98.29 168	98.88 198	98.85 229	97.53 150	99.87 124	96.14 285	99.31 282	99.48 163

DPM-MVS		96.32 323	95.59 335	98.51 226	98.76 292	97.21 219	94.54 415	98.26 340	91.94 404	96.37 383	97.25 374	93.06 314	99.43 380	91.42 401	98.74 346	98.89 311

GST-MVS		98.61 144	98.30 175	99.52 43	99.51 113	99.20 38	98.26 154	99.25 214	97.44 244	98.67 226	98.39 301	97.68 133	99.85 145	96.00 289	99.51 251	99.52 142

test_yl		96.69 309	96.29 319	97.90 280	98.28 359	95.24 300	97.29 285	97.36 366	98.21 174	98.17 275	97.86 342	86.27 372	99.55 347	94.87 325	98.32 367	98.89 311

thisisatest0530		95.27 352	94.45 363	97.74 296	99.19 204	94.37 327	97.86 214	90.20 437	97.17 272	98.22 273	97.65 354	73.53 425	99.90 76	96.90 222	99.35 276	98.95 300

Anonymous20240529		98.93 89	98.87 91	99.12 118	99.19 204	98.22 130	99.01 70	98.99 272	99.25 71	99.54 73	99.37 94	97.04 180	99.80 214	97.89 154	99.52 249	99.35 221

Anonymous202405211		97.90 223	97.50 251	99.08 126	98.90 266	98.25 124	98.53 120	96.16 395	98.87 122	99.11 152	98.86 226	90.40 348	99.78 238	97.36 186	99.31 282	99.19 261

DCV-MVSNet		96.69 309	96.29 319	97.90 280	98.28 359	95.24 300	97.29 285	97.36 366	98.21 174	98.17 275	97.86 342	86.27 372	99.55 347	94.87 325	98.32 367	98.89 311

tttt0517		95.64 345	94.98 355	97.64 305	99.36 163	93.81 350	98.72 100	90.47 436	98.08 187	98.67 226	98.34 308	73.88 424	99.92 60	97.77 164	99.51 251	99.20 256

our_test_3		97.39 269	97.73 235	96.34 368	98.70 305	89.78 413	94.61 412	98.97 273	96.50 305	99.04 166	98.85 229	95.98 241	99.84 163	97.26 191	99.67 199	99.41 191

thisisatest0515		94.12 372	93.16 380	96.97 347	98.60 327	92.90 368	93.77 427	90.61 435	94.10 377	96.91 358	95.87 402	74.99 423	99.80 214	94.52 334	99.12 316	98.20 379

ppachtmachnet_test		97.50 256	97.74 233	96.78 358	98.70 305	91.23 400	94.55 414	99.05 258	96.36 311	99.21 143	98.79 240	96.39 218	99.78 238	96.74 236	99.82 115	99.34 223

SMA-MVS		98.40 172	98.03 209	99.51 47	99.16 214	99.21 32	98.05 182	99.22 222	94.16 375	98.98 173	99.10 164	97.52 152	99.79 227	96.45 266	99.64 207	99.53 139
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																98.81 324

DPE-MVS		98.59 147	98.26 181	99.57 20	99.27 183	99.15 51	97.01 303	99.39 150	97.67 214	99.44 96	98.99 195	97.53 150	99.89 91	95.40 315	99.68 193	99.66 72
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part2					99.36 163	99.10 64				99.05 164

thres100view900		94.19 369	93.67 374	95.75 386	99.06 237	91.35 394	98.03 185	94.24 420	98.33 161	97.40 337	94.98 420	79.84 409	99.62 320	83.05 433	98.08 382	96.29 427

tfpnnormal		98.90 93	98.90 88	98.91 159	99.67 65	97.82 176	99.00 72	99.44 130	99.45 47	99.51 84	99.24 128	98.20 93	99.86 132	95.92 293	99.69 188	99.04 284

tfpn200view9		94.03 373	93.44 376	95.78 385	98.93 258	91.44 392	97.60 254	94.29 418	97.94 196	97.10 347	94.31 427	79.67 411	99.62 320	83.05 433	98.08 382	96.29 427

c3_l		97.36 270	97.37 259	97.31 329	98.09 372	93.25 362	95.01 400	99.16 240	97.05 278	98.77 215	98.72 251	92.88 317	99.64 314	96.93 216	99.76 158	99.05 280

CHOSEN 280x420		95.51 349	95.47 338	95.65 389	98.25 361	88.27 420	93.25 430	98.88 287	93.53 385	94.65 414	97.15 377	86.17 374	99.93 50	97.41 184	99.93 53	98.73 337

CANet		97.87 229	97.76 231	98.19 263	97.75 386	95.51 288	96.76 318	99.05 258	97.74 210	96.93 355	98.21 318	95.59 255	99.89 91	97.86 159	99.93 53	99.19 261

Fast-Effi-MVS+-dtu		98.27 191	98.09 201	98.81 170	98.43 349	98.11 138	97.61 253	99.50 101	98.64 135	97.39 339	97.52 362	98.12 102	99.95 26	96.90 222	98.71 350	98.38 371

Effi-MVS+-dtu		98.26 193	97.90 224	99.35 75	98.02 375	99.49 6	98.02 188	99.16 240	98.29 168	97.64 316	97.99 334	96.44 217	99.95 26	96.66 244	98.93 338	98.60 350

CANet_DTU		97.26 278	97.06 277	97.84 284	97.57 397	94.65 321	96.19 351	98.79 306	97.23 267	95.14 408	98.24 315	93.22 309	99.84 163	97.34 187	99.84 104	99.04 284

MVS_0304		97.44 264	97.01 280	98.72 191	96.42 432	96.74 246	97.20 294	91.97 432	98.46 155	98.30 266	98.79 240	92.74 321	99.91 69	99.30 59	99.94 48	99.52 142

MP-MVS-pluss		98.57 148	98.23 185	99.60 14	99.69 58	99.35 16	97.16 298	99.38 152	94.87 359	98.97 177	98.99 195	98.01 109	99.88 106	97.29 189	99.70 185	99.58 108
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MSP-MVS		98.40 172	98.00 212	99.61 12	99.57 89	99.25 28	98.57 115	99.35 166	97.55 229	99.31 127	97.71 350	94.61 283	99.88 106	96.14 285	99.19 305	99.70 63
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												84.74 386				98.81 324

sam_mvs												84.29 392

IterMVS-SCA-FT		97.85 235	98.18 191	96.87 352	99.27 183	91.16 401	95.53 383	99.25 214	99.10 95	99.41 103	99.35 99	93.10 312	99.96 14	98.65 110	99.94 48	99.49 153

TSAR-MVS + MP.		98.63 140	98.49 146	99.06 134	99.64 74	97.90 167	98.51 126	98.94 274	96.96 283	99.24 140	98.89 222	97.83 122	99.81 206	96.88 224	99.49 259	99.48 163
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		97.86 230	98.17 192	96.92 349	98.98 251	93.91 345	96.45 333	99.17 237	97.85 204	98.41 260	97.14 378	98.47 66	99.92 60	98.02 146	99.05 319	96.92 420

OPM-MVS		98.56 149	98.32 173	99.25 99	99.41 153	98.73 90	97.13 300	99.18 233	97.10 276	98.75 218	98.92 212	98.18 94	99.65 311	96.68 243	99.56 236	99.37 210
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMMP_NAP		98.75 115	98.48 147	99.57 20	99.58 84	99.29 23	97.82 218	99.25 214	96.94 285	98.78 212	99.12 160	98.02 108	99.84 163	97.13 201	99.67 199	99.59 101

ambc				98.24 259	98.82 284	95.97 274	98.62 110	99.00 271		99.27 131	99.21 135	96.99 185	99.50 364	96.55 259	99.50 258	99.26 245

MTGPA								99.20 225

SPE-MVS-test		99.13 61	99.09 70	99.26 96	99.13 221	98.97 72	99.31 30	99.88 14	99.44 49	98.16 278	98.51 287	98.64 52	99.93 50	98.91 89	99.85 100	98.88 314

Effi-MVS+		98.02 213	97.82 229	98.62 205	98.53 339	97.19 221	97.33 281	99.68 53	97.30 256	96.68 370	97.46 366	98.56 62	99.80 214	96.63 246	98.20 373	98.86 316

xiu_mvs_v2_base		97.16 288	97.49 252	96.17 377	98.54 337	92.46 376	95.45 387	98.84 298	97.25 261	97.48 331	96.49 388	98.31 81	99.90 76	96.34 273	98.68 355	96.15 431

xiu_mvs_v1_base		97.86 230	98.17 192	96.92 349	98.98 251	93.91 345	96.45 333	99.17 237	97.85 204	98.41 260	97.14 378	98.47 66	99.92 60	98.02 146	99.05 319	96.92 420

new-patchmatchnet		98.35 179	98.74 104	97.18 335	99.24 190	92.23 383	96.42 337	99.48 110	98.30 165	99.69 52	99.53 63	97.44 159	99.82 191	98.84 95	99.77 146	99.49 153

pmmvs6		99.67 3	99.70 3	99.60 14	99.90 4	99.27 26	99.53 9	99.76 37	99.64 26	99.84 28	99.83 4	99.50 9	99.87 124	99.36 54	99.92 65	99.64 78

pmmvs5		97.64 248	97.49 252	98.08 271	99.14 219	95.12 306	96.70 322	99.05 258	93.77 382	98.62 233	98.83 232	93.23 308	99.75 257	98.33 129	99.76 158	99.36 217

test_post1							97.59 256				20.48 448	83.07 400	99.66 306	94.16 345

test_post											21.25 447	83.86 395	99.70 279

Fast-Effi-MVS+		97.67 246	97.38 258	98.57 215	98.71 301	97.43 205	97.23 289	99.45 126	94.82 360	96.13 387	96.51 387	98.52 64	99.91 69	96.19 281	98.83 342	98.37 373

patchmatchnet-post											98.77 244	84.37 389	99.85 145

Anonymous20231211		99.27 37	99.27 45	99.26 96	99.29 180	98.18 132	99.49 12	99.51 99	99.70 15	99.80 35	99.68 25	96.84 191	99.83 181	99.21 67	99.91 74	99.77 46

pmmvs-eth3d		98.47 165	98.34 169	98.86 164	99.30 177	97.76 182	97.16 298	99.28 205	95.54 340	99.42 101	99.19 138	97.27 168	99.63 317	97.89 154	99.97 20	99.20 256

GG-mvs-BLEND				94.76 402	94.54 442	92.13 384	99.31 30	80.47 448		88.73 442	91.01 442	67.59 435	98.16 435	82.30 437	94.53 434	93.98 438

xiu_mvs_v1_base_debi		97.86 230	98.17 192	96.92 349	98.98 251	93.91 345	96.45 333	99.17 237	97.85 204	98.41 260	97.14 378	98.47 66	99.92 60	98.02 146	99.05 319	96.92 420

Anonymous20231206		98.21 199	98.21 186	98.20 261	99.51 113	95.43 294	98.13 168	99.32 180	96.16 319	98.93 189	98.82 235	96.00 236	99.83 181	97.32 188	99.73 165	99.36 217

MTAPA		98.88 95	98.64 123	99.61 12	99.67 65	99.36 15	98.43 139	99.20 225	98.83 128	98.89 195	98.90 216	96.98 186	99.92 60	97.16 196	99.70 185	99.56 119

MTMP							97.93 202	91.91 433

gm-plane-assit					94.83 441	81.97 444			88.07 429		94.99 419		99.60 328	91.76 394

test9_res														93.28 371	99.15 310	99.38 208

MVP-Stereo		98.08 210	97.92 222	98.57 215	98.96 254	96.79 242	97.90 208	99.18 233	96.41 310	98.46 255	98.95 208	95.93 245	99.60 328	96.51 262	98.98 333	99.31 234
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST9					98.71 301	98.08 145	95.96 364	99.03 263	91.40 410	95.85 393	97.53 360	96.52 213	99.76 250

train_agg		97.10 290	96.45 315	99.07 128	98.71 301	98.08 145	95.96 364	99.03 263	91.64 405	95.85 393	97.53 360	96.47 215	99.76 250	93.67 361	99.16 308	99.36 217

gg-mvs-nofinetune		92.37 399	91.20 403	95.85 383	95.80 440	92.38 379	99.31 30	81.84 447	99.75 11	91.83 436	99.74 18	68.29 431	99.02 415	87.15 424	97.12 411	96.16 430

SCA		96.41 322	96.66 305	95.67 387	98.24 362	88.35 419	95.85 373	96.88 384	96.11 320	97.67 315	98.67 261	93.10 312	99.85 145	94.16 345	99.22 298	98.81 324

Patchmatch-test		96.55 315	96.34 317	97.17 337	98.35 355	93.06 364	98.40 143	97.79 354	97.33 252	98.41 260	98.67 261	83.68 396	99.69 283	95.16 319	99.31 282	98.77 332

test_8					98.67 315	98.01 153	95.91 370	99.02 266	91.64 405	95.79 395	97.50 363	96.47 215	99.76 250

MS-PatchMatch		97.68 245	97.75 232	97.45 324	98.23 364	93.78 351	97.29 285	98.84 298	96.10 321	98.64 230	98.65 266	96.04 233	99.36 389	96.84 228	99.14 311	99.20 256

Patchmatch-RL test		97.26 278	97.02 279	97.99 279	99.52 111	95.53 287	96.13 356	99.71 44	97.47 236	99.27 131	99.16 148	84.30 391	99.62 320	97.89 154	99.77 146	98.81 324

cdsmvs_eth3d_5k		24.66 413	32.88 416	0.00 431	0.00 454	0.00 456	0.00 442	99.10 250	0.00 449	0.00 450	97.58 358	99.21 17	0.00 450	0.00 449	0.00 448	0.00 446

pcd_1.5k_mvsjas		8.17 416	10.90 419	0.00 431	0.00 454	0.00 456	0.00 442	0.00 455	0.00 449	0.00 450	0.00 449	98.07 104	0.00 450	0.00 449	0.00 448	0.00 446

agg_prior2														92.50 387	99.16 308	99.37 210

agg_prior					98.68 314	97.99 154		99.01 269		95.59 396			99.77 244

tmp_tt		78.77 410	78.73 413	78.90 426	58.45 451	74.76 450	94.20 420	78.26 449	39.16 444	86.71 443	92.82 438	80.50 407	75.19 446	86.16 429	92.29 439	86.74 440

canonicalmvs		98.34 180	98.26 181	98.58 212	98.46 345	97.82 176	98.96 77	99.46 122	99.19 81	97.46 332	95.46 412	98.59 58	99.46 375	98.08 142	98.71 350	98.46 358

anonymousdsp		99.51 14	99.47 21	99.62 9	99.88 9	99.08 68	99.34 23	99.69 48	98.93 117	99.65 60	99.72 21	98.93 31	99.95 26	99.11 74	100.00 1	99.82 33

alignmvs		97.35 271	96.88 288	98.78 178	98.54 337	98.09 141	97.71 236	97.69 358	99.20 77	97.59 320	95.90 401	88.12 366	99.55 347	98.18 135	98.96 335	98.70 341

nrg030		99.40 26	99.35 32	99.54 30	99.58 84	99.13 59	98.98 75	99.48 110	99.68 19	99.46 92	99.26 122	98.62 55	99.73 267	99.17 71	99.92 65	99.76 51

v144192		98.54 155	98.57 134	98.45 234	99.21 197	95.98 273	97.63 249	99.36 160	97.15 275	99.32 125	99.18 142	95.84 248	99.84 163	99.50 47	99.91 74	99.54 130

FIs		99.14 57	99.09 70	99.29 90	99.70 55	98.28 122	99.13 58	99.52 98	99.48 41	99.24 140	99.41 90	96.79 197	99.82 191	98.69 108	99.88 89	99.76 51

v1921920		98.54 155	98.60 131	98.38 243	99.20 201	95.76 282	97.56 259	99.36 160	97.23 267	99.38 109	99.17 146	96.02 234	99.84 163	99.57 35	99.90 81	99.54 130

UA-Net		99.47 16	99.40 26	99.70 2	99.49 126	99.29 23	99.80 4	99.72 42	99.82 8	99.04 166	99.81 8	98.05 107	99.96 14	98.85 94	99.99 5	99.86 26

v1192		98.60 145	98.66 120	98.41 239	99.27 183	95.88 276	97.52 264	99.36 160	97.41 245	99.33 119	99.20 137	96.37 221	99.82 191	99.57 35	99.92 65	99.55 126

FC-MVSNet-test		99.27 37	99.25 49	99.34 78	99.77 27	98.37 116	99.30 35	99.57 77	99.61 33	99.40 106	99.50 67	97.12 176	99.85 145	99.02 83	99.94 48	99.80 38

v1144		98.60 145	98.66 120	98.41 239	99.36 163	95.90 275	97.58 257	99.34 172	97.51 232	99.27 131	99.15 152	96.34 223	99.80 214	99.47 50	99.93 53	99.51 145

sosnet-low-res		0.00 418	0.00 421	0.00 431	0.00 454	0.00 456	0.00 442	0.00 455	0.00 449	0.00 450	0.00 449	0.00 454	0.00 450	0.00 449	0.00 448	0.00 446

HFP-MVS		98.71 119	98.44 154	99.51 47	99.49 126	99.16 47	98.52 121	99.31 185	97.47 236	98.58 241	98.50 291	97.97 114	99.85 145	96.57 252	99.59 224	99.53 139

v148		98.45 167	98.60 131	98.00 278	99.44 145	94.98 309	97.44 273	99.06 255	98.30 165	99.32 125	98.97 201	96.65 208	99.62 320	98.37 125	99.85 100	99.39 201

sosnet		0.00 418	0.00 421	0.00 431	0.00 454	0.00 456	0.00 442	0.00 455	0.00 449	0.00 450	0.00 449	0.00 454	0.00 450	0.00 449	0.00 448	0.00 446

uncertanet		0.00 418	0.00 421	0.00 431	0.00 454	0.00 456	0.00 442	0.00 455	0.00 449	0.00 450	0.00 449	0.00 454	0.00 450	0.00 449	0.00 448	0.00 446

AllTest		98.44 168	98.20 187	99.16 113	99.50 118	98.55 102	98.25 155	99.58 70	96.80 292	98.88 198	99.06 170	97.65 136	99.57 340	94.45 337	99.61 218	99.37 210

TestCases				99.16 113	99.50 118	98.55 102		99.58 70	96.80 292	98.88 198	99.06 170	97.65 136	99.57 340	94.45 337	99.61 218	99.37 210

v7n		99.53 12	99.57 13	99.41 65	99.88 9	98.54 105	99.45 14	99.61 66	99.66 23	99.68 54	99.66 32	98.44 71	99.95 26	99.73 24	99.96 27	99.75 55

region2R		98.69 126	98.40 159	99.54 30	99.53 109	99.17 43	98.52 121	99.31 185	97.46 241	98.44 257	98.51 287	97.83 122	99.88 106	96.46 265	99.58 229	99.58 108

RRT-MVS		97.88 227	97.98 214	97.61 307	98.15 368	93.77 352	98.97 76	99.64 60	99.16 85	98.69 223	99.42 86	91.60 334	99.89 91	97.63 172	98.52 364	99.16 271

mamv4		99.44 19	99.39 27	99.58 19	99.30 177	99.74 2	99.04 68	99.81 30	99.77 10	99.82 31	99.57 49	97.82 125	99.98 4	99.53 44	99.89 87	99.01 288

PS-MVSNAJss		99.46 17	99.49 16	99.35 75	99.90 4	98.15 134	99.20 48	99.65 58	99.48 41	99.92 8	99.71 22	98.07 104	99.96 14	99.53 44	100.00 1	99.93 11

PS-MVSNAJ		97.08 292	97.39 257	96.16 379	98.56 335	92.46 376	95.24 394	98.85 297	97.25 261	97.49 330	95.99 398	98.07 104	99.90 76	96.37 270	98.67 356	96.12 432

jajsoiax		99.58 9	99.61 11	99.48 55	99.87 12	98.61 97	99.28 40	99.66 57	99.09 98	99.89 16	99.68 25	99.53 7	99.97 7	99.50 47	99.99 5	99.87 20

mvs_tets		99.63 6	99.67 6	99.49 53	99.88 9	98.61 97	99.34 23	99.71 44	99.27 70	99.90 13	99.74 18	99.68 4	99.97 7	99.55 39	99.99 5	99.88 19

EI-MVSNet-UG-set		98.69 126	98.71 111	98.62 205	99.10 225	96.37 259	97.23 289	98.87 289	99.20 77	99.19 145	98.99 195	97.30 165	99.85 145	98.77 101	99.79 135	99.65 77

EI-MVSNet-Vis-set		98.68 131	98.70 114	98.63 203	99.09 228	96.40 258	97.23 289	98.86 294	99.20 77	99.18 149	98.97 201	97.29 167	99.85 145	98.72 105	99.78 140	99.64 78

HPM-MVS++		98.10 207	97.64 243	99.48 55	99.09 228	99.13 59	97.52 264	98.75 313	97.46 241	96.90 361	97.83 345	96.01 235	99.84 163	95.82 301	99.35 276	99.46 173

test_prior4						97.97 158	95.86 371

XVS		98.72 118	98.45 152	99.53 37	99.46 138	99.21 32	98.65 106	99.34 172	98.62 140	97.54 325	98.63 271	97.50 154	99.83 181	96.79 230	99.53 246	99.56 119

v1240		98.55 153	98.62 126	98.32 250	99.22 195	95.58 285	97.51 266	99.45 126	97.16 273	99.45 95	99.24 128	96.12 231	99.85 145	99.60 33	99.88 89	99.55 126

pm-mvs1		99.44 19	99.48 18	99.33 84	99.80 21	98.63 94	99.29 36	99.63 61	99.30 67	99.65 60	99.60 45	99.16 21	99.82 191	99.07 77	99.83 111	99.56 119

test_prior2							95.74 377		96.48 307	96.11 388	97.63 356	95.92 246		94.16 345	99.20 302

X-MVStestdata		94.32 366	92.59 385	99.53 37	99.46 138	99.21 32	98.65 106	99.34 172	98.62 140	97.54 325	45.85 444	97.50 154	99.83 181	96.79 230	99.53 246	99.56 119

test_prior				98.95 152	98.69 310	97.95 162		99.03 263					99.59 332			99.30 237

旧先验2							95.76 376		88.56 428	97.52 327			99.66 306	94.48 335

新几何2							95.93 367

新几何1				98.91 159	98.94 256	97.76 182		98.76 310	87.58 430	96.75 369	98.10 326	94.80 279	99.78 238	92.73 383	99.00 328	99.20 256

旧先验1					98.82 284	97.45 203		98.76 310			98.34 308	95.50 259			99.01 327	99.23 251

无先验							95.74 377	98.74 315	89.38 424				99.73 267	92.38 389		99.22 255

原ACMM2							95.53 383

原ACMM1				98.35 248	98.90 266	96.25 263		98.83 302	92.48 399	96.07 390	98.10 326	95.39 262	99.71 275	92.61 386	98.99 330	99.08 276

test222					98.92 262	96.93 236	95.54 382	98.78 308	85.72 433	96.86 364	98.11 325	94.43 286			99.10 318	99.23 251

testdata2													99.79 227	92.80 381

segment_acmp												97.02 183

testdata				98.09 268	98.93 258	95.40 295		98.80 305	90.08 421	97.45 334	98.37 304	95.26 264	99.70 279	93.58 364	98.95 336	99.17 268

testdata1							95.44 388		96.32 313

v8		99.01 77	99.16 58	98.57 215	99.47 136	96.31 262	98.90 83	99.47 118	99.03 106	99.52 79	99.57 49	96.93 187	99.81 206	99.60 33	99.98 12	99.60 94

1314		95.74 341	95.60 333	96.17 377	97.53 402	92.75 372	98.07 179	98.31 339	91.22 412	94.25 418	96.68 384	95.53 256	99.03 414	91.64 397	97.18 410	96.74 424

LFMVS		97.20 284	96.72 299	98.64 199	98.72 298	96.95 234	98.93 81	94.14 422	99.74 13	98.78 212	99.01 191	84.45 388	99.73 267	97.44 182	99.27 289	99.25 246

VDD-MVS		98.56 149	98.39 162	99.07 128	99.13 221	98.07 147	98.59 113	97.01 377	99.59 34	99.11 152	99.27 117	94.82 276	99.79 227	98.34 127	99.63 210	99.34 223

VDDNet		98.21 199	97.95 217	99.01 142	99.58 84	97.74 184	99.01 70	97.29 370	99.67 20	98.97 177	99.50 67	90.45 347	99.80 214	97.88 157	99.20 302	99.48 163

v10		98.97 84	99.11 66	98.55 220	99.44 145	96.21 264	98.90 83	99.55 88	98.73 130	99.48 87	99.60 45	96.63 209	99.83 181	99.70 29	99.99 5	99.61 92

VPNet		98.87 96	98.83 96	99.01 142	99.70 55	97.62 193	98.43 139	99.35 166	99.47 44	99.28 129	99.05 177	96.72 203	99.82 191	98.09 141	99.36 274	99.59 101

MVS		93.19 387	92.09 392	96.50 364	96.91 421	94.03 339	98.07 179	98.06 350	68.01 442	94.56 416	96.48 389	95.96 243	99.30 399	83.84 432	96.89 415	96.17 429

v2v482		98.56 149	98.62 126	98.37 246	99.42 151	95.81 280	97.58 257	99.16 240	97.90 200	99.28 129	99.01 191	95.98 241	99.79 227	99.33 56	99.90 81	99.51 145

V42		98.78 110	98.78 102	98.76 183	99.44 145	97.04 228	98.27 153	99.19 229	97.87 202	99.25 139	99.16 148	96.84 191	99.78 238	99.21 67	99.84 104	99.46 173

SD-MVS		98.40 172	98.68 117	97.54 316	98.96 254	97.99 154	97.88 210	99.36 160	98.20 178	99.63 63	99.04 179	98.76 42	95.33 443	96.56 256	99.74 162	99.31 234
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		95.86 337	95.32 347	97.49 321	98.60 327	94.15 334	93.83 426	97.93 352	95.49 342	96.68 370	97.42 368	83.21 398	99.30 399	96.22 279	98.55 363	99.01 288

MSLP-MVS++		98.02 213	98.14 198	97.64 305	98.58 332	95.19 303	97.48 269	99.23 221	97.47 236	97.90 298	98.62 273	97.04 180	98.81 424	97.55 176	99.41 268	98.94 304

APDe-MVS		98.99 80	98.79 100	99.60 14	99.21 197	99.15 51	98.87 87	99.48 110	97.57 225	99.35 115	99.24 128	97.83 122	99.89 91	97.88 157	99.70 185	99.75 55
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
APD-MVS_3200maxsize		98.84 100	98.61 130	99.53 37	99.19 204	99.27 26	98.49 131	99.33 178	98.64 135	99.03 169	98.98 199	97.89 119	99.85 145	96.54 260	99.42 267	99.46 173

ADS-MVSNet2		95.43 350	94.98 355	96.76 359	98.14 369	91.74 386	97.92 205	97.76 355	90.23 417	96.51 379	98.91 213	85.61 379	99.85 145	92.88 377	96.90 413	98.69 342

EI-MVSNet		98.40 172	98.51 140	98.04 276	99.10 225	94.73 317	97.20 294	98.87 289	98.97 112	99.06 159	99.02 182	96.00 236	99.80 214	98.58 113	99.82 115	99.60 94

Regformer		0.00 418	0.00 421	0.00 431	0.00 454	0.00 456	0.00 442	0.00 455	0.00 449	0.00 450	0.00 449	0.00 454	0.00 450	0.00 449	0.00 448	0.00 446

CVMVSNet		96.25 326	97.21 269	93.38 419	99.10 225	80.56 447	97.20 294	98.19 345	96.94 285	99.00 171	99.02 182	89.50 354	99.80 214	96.36 272	99.59 224	99.78 43

pmmvs4		97.58 253	97.28 264	98.51 226	98.84 279	96.93 236	95.40 390	98.52 329	93.60 384	98.61 235	98.65 266	95.10 268	99.60 328	96.97 214	99.79 135	98.99 293

EU-MVSNet		97.66 247	98.50 142	95.13 398	99.63 78	85.84 429	98.35 148	98.21 342	98.23 172	99.54 73	99.46 78	95.02 270	99.68 292	98.24 131	99.87 93	99.87 20

VNet		98.42 169	98.30 175	98.79 175	98.79 291	97.29 211	98.23 156	98.66 320	99.31 65	98.85 203	98.80 238	94.80 279	99.78 238	98.13 138	99.13 313	99.31 234

test-LLR		93.90 375	93.85 370	94.04 409	96.53 429	84.62 435	94.05 423	92.39 429	96.17 317	94.12 420	95.07 416	82.30 403	99.67 295	95.87 297	98.18 374	97.82 398

TESTMET0.1,1		92.19 402	91.77 400	93.46 416	96.48 431	82.80 442	94.05 423	91.52 434	94.45 369	94.00 423	94.88 422	66.65 436	99.56 343	95.78 302	98.11 380	98.02 388

test-mter		92.33 400	91.76 401	94.04 409	96.53 429	84.62 435	94.05 423	92.39 429	94.00 380	94.12 420	95.07 416	65.63 442	99.67 295	95.87 297	98.18 374	97.82 398

VPA-MVSNet		99.30 33	99.30 42	99.28 91	99.49 126	98.36 119	99.00 72	99.45 126	99.63 28	99.52 79	99.44 83	98.25 85	99.88 106	99.09 76	99.84 104	99.62 84

ACMMPR		98.70 123	98.42 157	99.54 30	99.52 111	99.14 56	98.52 121	99.31 185	97.47 236	98.56 244	98.54 282	97.75 130	99.88 106	96.57 252	99.59 224	99.58 108

testgi		98.32 184	98.39 162	98.13 267	99.57 89	95.54 286	97.78 224	99.49 108	97.37 249	99.19 145	97.65 354	98.96 28	99.49 367	96.50 263	98.99 330	99.34 223

test20.03		98.78 110	98.77 103	98.78 178	99.46 138	97.20 220	97.78 224	99.24 219	99.04 105	99.41 103	98.90 216	97.65 136	99.76 250	97.70 169	99.79 135	99.39 201

thres600view7		94.45 364	93.83 371	96.29 370	99.06 237	91.53 389	97.99 197	94.24 420	98.34 160	97.44 335	95.01 418	79.84 409	99.67 295	84.33 431	98.23 371	97.66 408

ADS-MVSNet		95.24 353	94.93 358	96.18 376	98.14 369	90.10 412	97.92 205	97.32 369	90.23 417	96.51 379	98.91 213	85.61 379	99.74 262	92.88 377	96.90 413	98.69 342

MP-MVS		98.46 166	98.09 201	99.54 30	99.57 89	99.22 31	98.50 128	99.19 229	97.61 221	97.58 321	98.66 264	97.40 161	99.88 106	94.72 330	99.60 220	99.54 130
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		17.12 414	20.53 417	6.87 430	12.05 452	4.20 455	93.62 429	6.73 453	4.62 448	10.41 448	24.33 445	8.28 453	3.56 449	9.69 448	15.07 446	12.86 445

thres400		94.14 371	93.44 376	96.24 373	98.93 258	91.44 392	97.60 254	94.29 418	97.94 196	97.10 347	94.31 427	79.67 411	99.62 320	83.05 433	98.08 382	97.66 408

test123		17.04 415	20.11 418	7.82 429	10.25 453	4.91 454	94.80 404	4.47 454	4.93 447	10.00 449	24.28 446	9.69 452	3.64 448	10.14 447	12.43 447	14.92 444

thres200		93.72 379	93.14 381	95.46 394	98.66 320	91.29 396	96.61 326	94.63 415	97.39 247	96.83 365	93.71 430	79.88 408	99.56 343	82.40 436	98.13 379	95.54 436

test0.0.03 1		94.51 363	93.69 373	96.99 345	96.05 436	93.61 359	94.97 401	93.49 424	96.17 317	97.57 323	94.88 422	82.30 403	99.01 417	93.60 363	94.17 435	98.37 373

pmmvs3		95.03 357	94.40 364	96.93 348	97.70 392	92.53 375	95.08 398	97.71 357	88.57 427	97.71 312	98.08 329	79.39 413	99.82 191	96.19 281	99.11 317	98.43 366

EMVS		93.83 376	94.02 368	93.23 420	96.83 424	84.96 432	89.77 440	96.32 393	97.92 198	97.43 336	96.36 394	86.17 374	98.93 420	87.68 423	97.73 393	95.81 434

E-PMN		94.17 370	94.37 365	93.58 415	96.86 422	85.71 431	90.11 439	97.07 376	98.17 181	97.82 307	97.19 375	84.62 387	98.94 419	89.77 416	97.68 394	96.09 433

PGM-MVS		98.66 135	98.37 165	99.55 27	99.53 109	99.18 42	98.23 156	99.49 108	97.01 282	98.69 223	98.88 223	98.00 110	99.89 91	95.87 297	99.59 224	99.58 108

LCM-MVSNet-Re		98.64 138	98.48 147	99.11 120	98.85 278	98.51 107	98.49 131	99.83 25	98.37 158	99.69 52	99.46 78	98.21 92	99.92 60	94.13 349	99.30 285	98.91 309

LCM-MVSNet		99.93 1	99.92 1	99.94 1	99.99 1	99.97 1	99.90 1	99.89 13	99.98 1	99.99 1	99.96 1	99.77 2	100.00 1	99.81 13	100.00 1	99.85 28

MCST-MVS		98.00 216	97.63 244	99.10 122	99.24 190	98.17 133	96.89 312	98.73 316	95.66 335	97.92 296	97.70 352	97.17 174	99.66 306	96.18 283	99.23 297	99.47 171

mvs_anonymous		97.83 238	98.16 195	96.87 352	98.18 366	91.89 385	97.31 283	98.90 283	97.37 249	98.83 206	99.46 78	96.28 224	99.79 227	98.90 90	98.16 377	98.95 300

MVS_Test		98.18 202	98.36 166	97.67 301	98.48 342	94.73 317	98.18 161	99.02 266	97.69 213	98.04 291	99.11 161	97.22 172	99.56 343	98.57 115	98.90 340	98.71 338

MDA-MVSNet-bldmvs		97.94 221	97.91 223	98.06 273	99.44 145	94.96 310	96.63 325	99.15 245	98.35 159	98.83 206	99.11 161	94.31 291	99.85 145	96.60 249	98.72 348	99.37 210

CDPH-MVS		97.26 278	96.66 305	99.07 128	99.00 247	98.15 134	96.03 360	99.01 269	91.21 413	97.79 308	97.85 344	96.89 189	99.69 283	92.75 382	99.38 273	99.39 201

test12				98.93 155	98.58 332	97.83 173		98.66 320		96.53 377		95.51 258	99.69 283		99.13 313	99.27 242

casdiffmvs		98.95 87	99.00 79	98.81 170	99.38 156	97.33 209	97.82 218	99.57 77	99.17 84	99.35 115	99.17 146	98.35 78	99.69 283	98.46 121	99.73 165	99.41 191
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		98.22 197	98.24 184	98.17 264	99.00 247	95.44 293	96.38 339	99.58 70	97.79 208	98.53 249	98.50 291	96.76 200	99.74 262	97.95 153	99.64 207	99.34 223
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		93.73 378	92.83 384	96.42 366	97.70 392	91.28 397	96.84 314	89.77 438	93.96 381	92.44 433	95.93 400	79.14 414	99.77 244	92.94 375	96.76 417	98.21 378

baseline1		95.96 335	95.44 341	97.52 318	98.51 341	93.99 342	98.39 144	96.09 398	98.21 174	98.40 264	97.76 348	86.88 368	99.63 317	95.42 314	89.27 441	98.95 300

YYNet1		97.60 250	97.67 238	97.39 328	99.04 241	93.04 367	95.27 392	98.38 337	97.25 261	98.92 191	98.95 208	95.48 260	99.73 267	96.99 211	98.74 346	99.41 191

PMMVS2		98.07 211	98.08 204	98.04 276	99.41 153	94.59 323	94.59 413	99.40 148	97.50 233	98.82 209	98.83 232	96.83 193	99.84 163	97.50 181	99.81 119	99.71 58

MDA-MVSNet_test_wron		97.60 250	97.66 241	97.41 327	99.04 241	93.09 363	95.27 392	98.42 334	97.26 260	98.88 198	98.95 208	95.43 261	99.73 267	97.02 208	98.72 348	99.41 191

tpmvs		95.02 358	95.25 348	94.33 405	96.39 434	85.87 428	98.08 176	96.83 385	95.46 343	95.51 404	98.69 257	85.91 377	99.53 354	94.16 345	96.23 422	97.58 411

PM-MVS		98.82 104	98.72 108	99.12 118	99.64 74	98.54 105	97.98 198	99.68 53	97.62 218	99.34 117	99.18 142	97.54 148	99.77 244	97.79 162	99.74 162	99.04 284

HQP_MVS		97.99 219	97.67 238	98.93 155	99.19 204	97.65 190	97.77 227	99.27 208	98.20 178	97.79 308	97.98 335	94.90 272	99.70 279	94.42 339	99.51 251	99.45 177

plane_prior7					99.19 204	97.87 169

plane_prior6					98.99 250	97.70 188						94.90 272

plane_prior5								99.27 208					99.70 279	94.42 339	99.51 251	99.45 177

plane_prior4											97.98 335

plane_prior3						97.78 181			97.41 245	97.79 308

plane_prior2							97.77 227		98.20 178

plane_prior1					99.05 240

plane_prior						97.65 190	97.07 301		96.72 297						99.36 274

PS-CasMVS		99.40 26	99.33 35	99.62 9	99.71 47	99.10 64	99.29 36	99.53 95	99.53 38	99.46 92	99.41 90	98.23 87	99.95 26	98.89 92	99.95 37	99.81 36

UniMVSNet_NR-MVSNet		98.86 99	98.68 117	99.40 67	99.17 212	98.74 87	97.68 239	99.40 148	99.14 86	99.06 159	98.59 278	96.71 204	99.93 50	98.57 115	99.77 146	99.53 139

PEN-MVS		99.41 25	99.34 34	99.62 9	99.73 37	99.14 56	99.29 36	99.54 92	99.62 31	99.56 68	99.42 86	98.16 98	99.96 14	98.78 98	99.93 53	99.77 46

TransMVSNet (Re)		99.44 19	99.47 21	99.36 69	99.80 21	98.58 100	99.27 42	99.57 77	99.39 55	99.75 42	99.62 40	99.17 19	99.83 181	99.06 79	99.62 213	99.66 72

DTE-MVSNet		99.43 23	99.35 32	99.66 7	99.71 47	99.30 21	99.31 30	99.51 99	99.64 26	99.56 68	99.46 78	98.23 87	99.97 7	98.78 98	99.93 53	99.72 57

DU-MVS		98.82 104	98.63 124	99.39 68	99.16 214	98.74 87	97.54 262	99.25 214	98.84 127	99.06 159	98.76 246	96.76 200	99.93 50	98.57 115	99.77 146	99.50 148

UniMVSNet (Re)		98.87 96	98.71 111	99.35 75	99.24 190	98.73 90	97.73 235	99.38 152	98.93 117	99.12 151	98.73 249	96.77 198	99.86 132	98.63 112	99.80 130	99.46 173

CP-MVSNet		99.21 46	99.09 70	99.56 25	99.65 68	98.96 76	99.13 58	99.34 172	99.42 52	99.33 119	99.26 122	97.01 184	99.94 41	98.74 103	99.93 53	99.79 40

WR-MVS_H		99.33 31	99.22 51	99.65 8	99.71 47	99.24 29	99.32 26	99.55 88	99.46 46	99.50 85	99.34 103	97.30 165	99.93 50	98.90 90	99.93 53	99.77 46

WR-MVS		98.40 172	98.19 190	99.03 138	99.00 247	97.65 190	96.85 313	98.94 274	98.57 147	98.89 195	98.50 291	95.60 254	99.85 145	97.54 178	99.85 100	99.59 101

NR-MVSNet		98.95 87	98.82 97	99.36 69	99.16 214	98.72 92	99.22 45	99.20 225	99.10 95	99.72 44	98.76 246	96.38 220	99.86 132	98.00 149	99.82 115	99.50 148

Baseline_NR-MVSNet		98.98 83	98.86 94	99.36 69	99.82 19	98.55 102	97.47 271	99.57 77	99.37 57	99.21 143	99.61 43	96.76 200	99.83 181	98.06 144	99.83 111	99.71 58

TranMVSNet+NR-MVSNet		99.17 50	99.07 73	99.46 61	99.37 162	98.87 80	98.39 144	99.42 141	99.42 52	99.36 113	99.06 170	98.38 74	99.95 26	98.34 127	99.90 81	99.57 113

TSAR-MVS + GP.		98.18 202	97.98 214	98.77 182	98.71 301	97.88 168	96.32 343	98.66 320	96.33 312	99.23 142	98.51 287	97.48 158	99.40 384	97.16 196	99.46 261	99.02 287

n2								0.00 455

nn								0.00 455

mPP-MVS		98.64 138	98.34 169	99.54 30	99.54 106	99.17 43	98.63 108	99.24 219	97.47 236	98.09 286	98.68 259	97.62 141	99.89 91	96.22 279	99.62 213	99.57 113

door-mid								99.57 77

XVG-OURS-SEG-HR		98.49 163	98.28 177	99.14 116	99.49 126	98.83 82	96.54 327	99.48 110	97.32 254	99.11 152	98.61 275	99.33 14	99.30 399	96.23 278	98.38 366	99.28 241

mvsmamba		97.57 254	97.26 265	98.51 226	98.69 310	96.73 247	98.74 95	97.25 371	97.03 281	97.88 300	99.23 133	90.95 342	99.87 124	96.61 248	99.00 328	98.91 309

MVSFormer		98.26 193	98.43 155	97.77 290	98.88 272	93.89 348	99.39 20	99.56 84	99.11 88	98.16 278	98.13 322	93.81 302	99.97 7	99.26 62	99.57 233	99.43 185

jason		97.45 263	97.35 261	97.76 293	99.24 190	93.93 344	95.86 371	98.42 334	94.24 373	98.50 252	98.13 322	94.82 276	99.91 69	97.22 193	99.73 165	99.43 185
jason: jason.
lupinMVS		97.06 293	96.86 289	97.65 303	98.88 272	93.89 348	95.48 386	97.97 351	93.53 385	98.16 278	97.58 358	93.81 302	99.91 69	96.77 233	99.57 233	99.17 268

test_djsdf		99.52 13	99.51 15	99.53 37	99.86 14	98.74 87	99.39 20	99.56 84	99.11 88	99.70 48	99.73 20	99.00 26	99.97 7	99.26 62	99.98 12	99.89 16

HPM-MVS_fast		99.01 77	98.82 97	99.57 20	99.71 47	99.35 16	99.00 72	99.50 101	97.33 252	98.94 188	98.86 226	98.75 43	99.82 191	97.53 179	99.71 178	99.56 119

K. test v3		98.00 216	97.66 241	99.03 138	99.79 23	97.56 195	99.19 52	92.47 428	99.62 31	99.52 79	99.66 32	89.61 352	99.96 14	99.25 64	99.81 119	99.56 119

lessismore_v0				98.97 149	99.73 37	97.53 197		86.71 443		99.37 111	99.52 66	89.93 350	99.92 60	98.99 85	99.72 173	99.44 181

SixPastTwentyTwo		98.75 115	98.62 126	99.16 113	99.83 18	97.96 161	99.28 40	98.20 343	99.37 57	99.70 48	99.65 36	92.65 323	99.93 50	99.04 81	99.84 104	99.60 94

OurMVSNet-221017-0		99.37 29	99.31 39	99.53 37	99.91 3	98.98 70	99.63 7	99.58 70	99.44 49	99.78 37	99.76 15	96.39 218	99.92 60	99.44 51	99.92 65	99.68 66

HPM-MVS		98.79 108	98.53 138	99.59 18	99.65 68	99.29 23	99.16 54	99.43 136	96.74 296	98.61 235	98.38 303	98.62 55	99.87 124	96.47 264	99.67 199	99.59 101
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
XVG-OURS		98.53 157	98.34 169	99.11 120	99.50 118	98.82 84	95.97 362	99.50 101	97.30 256	99.05 164	98.98 199	99.35 13	99.32 396	95.72 304	99.68 193	99.18 264

XVG-ACMP-BASELINE		98.56 149	98.34 169	99.22 104	99.54 106	98.59 99	97.71 236	99.46 122	97.25 261	98.98 173	98.99 195	97.54 148	99.84 163	95.88 294	99.74 162	99.23 251

casdiffmvs_mvg		99.12 64	99.16 58	98.99 144	99.43 150	97.73 186	98.00 192	99.62 63	99.22 73	99.55 71	99.22 134	98.93 31	99.75 257	98.66 109	99.81 119	99.50 148
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		98.71 119	98.46 151	99.47 59	99.57 89	98.97 72	98.23 156	99.48 110	96.60 301	99.10 155	99.06 170	98.71 47	99.83 181	95.58 311	99.78 140	99.62 84

LGP-MVS_train				99.47 59	99.57 89	98.97 72		99.48 110	96.60 301	99.10 155	99.06 170	98.71 47	99.83 181	95.58 311	99.78 140	99.62 84

baseline		98.96 86	99.02 76	98.76 183	99.38 156	97.26 214	98.49 131	99.50 101	98.86 124	99.19 145	99.06 170	98.23 87	99.69 283	98.71 106	99.76 158	99.33 228

test11								98.87 289

door								99.41 145

EPNet_dtu		94.93 360	94.78 360	95.38 396	93.58 444	87.68 423	96.78 316	95.69 407	97.35 251	89.14 441	98.09 328	88.15 365	99.49 367	94.95 324	99.30 285	98.98 294
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x2688		97.49 259	97.14 274	98.54 223	99.68 61	96.09 268	96.50 331	99.62 63	91.58 407	98.84 205	98.97 201	92.36 325	99.88 106	96.76 234	99.95 37	99.67 70

EPNet		96.14 329	95.44 341	98.25 257	90.76 448	95.50 289	97.92 205	94.65 414	98.97 112	92.98 430	98.85 229	89.12 356	99.87 124	95.99 290	99.68 193	99.39 201
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS						96.79 242

HQP-NCC					98.67 315		96.29 345		96.05 322	95.55 399

ACMP_Plane					98.67 315		96.29 345		96.05 322	95.55 399

APD-MVS		98.10 207	97.67 238	99.42 63	99.11 223	98.93 78	97.76 230	99.28 205	94.97 356	98.72 221	98.77 244	97.04 180	99.85 145	93.79 359	99.54 242	99.49 153
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS														92.82 379

HQP4-MVS										95.56 398			99.54 352			99.32 230

HQP3-MVS								99.04 261							99.26 292

HQP2-MVS												93.84 300

CNVR-MVS		98.17 204	97.87 226	99.07 128	98.67 315	98.24 125	97.01 303	98.93 277	97.25 261	97.62 317	98.34 308	97.27 168	99.57 340	96.42 267	99.33 279	99.39 201

NCCC		97.86 230	97.47 255	99.05 135	98.61 325	98.07 147	96.98 305	98.90 283	97.63 217	97.04 351	97.93 340	95.99 240	99.66 306	95.31 316	98.82 344	99.43 185

114514_t		96.50 318	95.77 326	98.69 193	99.48 134	97.43 205	97.84 217	99.55 88	81.42 439	96.51 379	98.58 279	95.53 256	99.67 295	93.41 369	99.58 229	98.98 294

CP-MVS		98.70 123	98.42 157	99.52 43	99.36 163	99.12 61	98.72 100	99.36 160	97.54 230	98.30 266	98.40 300	97.86 121	99.89 91	96.53 261	99.72 173	99.56 119

DSMNet-mixed		97.42 266	97.60 246	96.87 352	99.15 218	91.46 390	98.54 119	99.12 247	92.87 395	97.58 321	99.63 39	96.21 226	99.90 76	95.74 303	99.54 242	99.27 242

tpm2		93.09 388	92.58 386	94.62 403	97.56 398	86.53 427	97.66 243	95.79 404	86.15 432	94.07 422	98.23 317	75.95 421	99.53 354	90.91 410	96.86 416	97.81 400

NP-MVS					98.84 279	97.39 207					96.84 381

EG-PatchMatch MVS		98.99 80	99.01 78	98.94 153	99.50 118	97.47 201	98.04 184	99.59 68	98.15 185	99.40 106	99.36 98	98.58 61	99.76 250	98.78 98	99.68 193	99.59 101

tpm cat1		93.29 385	93.13 382	93.75 413	97.39 411	84.74 433	97.39 275	97.65 361	83.39 437	94.16 419	98.41 299	82.86 401	99.39 386	91.56 399	95.35 430	97.14 419

SteuartSystems-ACMMP		98.79 108	98.54 137	99.54 30	99.73 37	99.16 47	98.23 156	99.31 185	97.92 198	98.90 193	98.90 216	98.00 110	99.88 106	96.15 284	99.72 173	99.58 108
Skip Steuart: Steuart Systems R&D Blog.
CostFormer		93.97 374	93.78 372	94.51 404	97.53 402	85.83 430	97.98 198	95.96 400	89.29 425	94.99 410	98.63 271	78.63 417	99.62 320	94.54 333	96.50 418	98.09 385

CR-MVSNet		96.28 325	95.95 324	97.28 331	97.71 390	94.22 329	98.11 172	98.92 280	92.31 401	96.91 358	99.37 94	85.44 382	99.81 206	97.39 185	97.36 406	97.81 400

JIA-IIPM		95.52 348	95.03 354	97.00 344	96.85 423	94.03 339	96.93 309	95.82 403	99.20 77	94.63 415	99.71 22	83.09 399	99.60 328	94.42 339	94.64 432	97.36 417

Patchmtry		97.35 271	96.97 281	98.50 230	97.31 413	96.47 256	98.18 161	98.92 280	98.95 116	98.78 212	99.37 94	85.44 382	99.85 145	95.96 292	99.83 111	99.17 268

PatchT		96.65 312	96.35 316	97.54 316	97.40 410	95.32 298	97.98 198	96.64 388	99.33 62	96.89 362	99.42 86	84.32 390	99.81 206	97.69 171	97.49 397	97.48 413

tpmrst		95.07 356	95.46 339	93.91 411	97.11 417	84.36 437	97.62 250	96.96 380	94.98 355	96.35 384	98.80 238	85.46 381	99.59 332	95.60 309	96.23 422	97.79 403

BH-w/o		95.13 355	94.89 359	95.86 382	98.20 365	91.31 395	95.65 379	97.37 365	93.64 383	96.52 378	95.70 405	93.04 315	99.02 415	88.10 422	95.82 427	97.24 418

tpm		94.67 362	94.34 366	95.66 388	97.68 395	88.42 418	97.88 210	94.90 412	94.46 367	96.03 392	98.56 281	78.66 416	99.79 227	95.88 294	95.01 431	98.78 331

DELS-MVS		98.27 191	98.20 187	98.48 231	98.86 275	96.70 248	95.60 381	99.20 225	97.73 211	98.45 256	98.71 252	97.50 154	99.82 191	98.21 133	99.59 224	98.93 305
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		96.83 305	96.75 298	97.08 340	98.74 295	93.33 361	96.71 321	98.26 340	96.72 297	98.44 257	97.37 371	95.20 265	99.47 373	91.89 391	97.43 401	98.44 364

RPMNet		97.02 296	96.93 283	97.30 330	97.71 390	94.22 329	98.11 172	99.30 193	99.37 57	96.91 358	99.34 103	86.72 369	99.87 124	97.53 179	97.36 406	97.81 400

MVSTER		96.86 304	96.55 311	97.79 288	97.91 380	94.21 331	97.56 259	98.87 289	97.49 235	99.06 159	99.05 177	80.72 406	99.80 214	98.44 122	99.82 115	99.37 210

CPTT-MVS		97.84 236	97.36 260	99.27 94	99.31 173	98.46 110	98.29 151	99.27 208	94.90 358	97.83 305	98.37 304	94.90 272	99.84 163	93.85 358	99.54 242	99.51 145

GBi-Net		98.65 136	98.47 149	99.17 110	98.90 266	98.24 125	99.20 48	99.44 130	98.59 143	98.95 181	99.55 57	94.14 294	99.86 132	97.77 164	99.69 188	99.41 191

PVSNet_Blended_VisFu		98.17 204	98.15 196	98.22 260	99.73 37	95.15 304	97.36 279	99.68 53	94.45 369	98.99 172	99.27 117	96.87 190	99.94 41	97.13 201	99.91 74	99.57 113

PVSNet_BlendedMVS		97.55 255	97.53 249	97.60 308	98.92 262	93.77 352	96.64 324	99.43 136	94.49 365	97.62 317	99.18 142	96.82 194	99.67 295	94.73 328	99.93 53	99.36 217

UnsupCasMVSNet_eth		97.89 225	97.60 246	98.75 185	99.31 173	97.17 223	97.62 250	99.35 166	98.72 132	98.76 217	98.68 259	92.57 324	99.74 262	97.76 168	95.60 428	99.34 223

UnsupCasMVSNet_bld		97.30 275	96.92 285	98.45 234	99.28 181	96.78 245	96.20 350	99.27 208	95.42 344	98.28 270	98.30 312	93.16 310	99.71 275	94.99 321	97.37 404	98.87 315

PVSNet_Blended		96.88 303	96.68 302	97.47 323	98.92 262	93.77 352	94.71 406	99.43 136	90.98 415	97.62 317	97.36 372	96.82 194	99.67 295	94.73 328	99.56 236	98.98 294

FMVSNet5		96.01 332	95.20 351	98.41 239	97.53 402	96.10 265	98.74 95	99.50 101	97.22 270	98.03 292	99.04 179	69.80 429	99.88 106	97.27 190	99.71 178	99.25 246

test1		98.65 136	98.47 149	99.17 110	98.90 266	98.24 125	99.20 48	99.44 130	98.59 143	98.95 181	99.55 57	94.14 294	99.86 132	97.77 164	99.69 188	99.41 191

new_pmnet		96.99 300	96.76 297	97.67 301	98.72 298	94.89 311	95.95 366	98.20 343	92.62 398	98.55 246	98.54 282	94.88 275	99.52 358	93.96 353	99.44 266	98.59 353

FMVSNet3		97.50 256	97.24 267	98.29 254	98.08 373	95.83 279	97.86 214	98.91 282	97.89 201	98.95 181	98.95 208	87.06 367	99.81 206	97.77 164	99.69 188	99.23 251

dp		93.47 382	93.59 375	93.13 421	96.64 427	81.62 446	97.66 243	96.42 392	92.80 396	96.11 388	98.64 269	78.55 419	99.59 332	93.31 370	92.18 440	98.16 381

FMVSNet2		98.49 163	98.40 159	98.75 185	98.90 266	97.14 226	98.61 111	99.13 246	98.59 143	99.19 145	99.28 115	94.14 294	99.82 191	97.97 151	99.80 130	99.29 239

FMVSNet1		99.17 50	99.17 56	99.17 110	99.55 101	98.24 125	99.20 48	99.44 130	99.21 75	99.43 97	99.55 57	97.82 125	99.86 132	98.42 124	99.89 87	99.41 191

N_pmnet		97.63 249	97.17 270	98.99 144	99.27 183	97.86 170	95.98 361	93.41 425	95.25 349	99.47 91	98.90 216	95.63 253	99.85 145	96.91 217	99.73 165	99.27 242

cascas		94.79 361	94.33 367	96.15 380	96.02 438	92.36 380	92.34 435	99.26 213	85.34 434	95.08 409	94.96 421	92.96 316	98.53 429	94.41 342	98.59 361	97.56 412

BH-RMVSNet		96.83 305	96.58 310	97.58 310	98.47 343	94.05 336	96.67 323	97.36 366	96.70 299	97.87 301	97.98 335	95.14 267	99.44 379	90.47 414	98.58 362	99.25 246

UGNet		98.53 157	98.45 152	98.79 175	97.94 378	96.96 233	99.08 61	98.54 327	99.10 95	96.82 366	99.47 76	96.55 212	99.84 163	98.56 118	99.94 48	99.55 126
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		96.67 311	96.27 321	97.87 283	98.81 287	94.61 322	96.77 317	97.92 353	94.94 357	97.12 346	97.74 349	91.11 341	99.82 191	93.89 355	98.15 378	99.18 264

XXY-MVS		99.14 57	99.15 63	99.10 122	99.76 30	97.74 184	98.85 90	99.62 63	98.48 154	99.37 111	99.49 73	98.75 43	99.86 132	98.20 134	99.80 130	99.71 58

EC-MVSNet		99.09 67	99.05 74	99.20 105	99.28 181	98.93 78	99.24 44	99.84 22	99.08 100	98.12 283	98.37 304	98.72 46	99.90 76	99.05 80	99.77 146	98.77 332

sss		97.21 283	96.93 283	98.06 273	98.83 281	95.22 302	96.75 319	98.48 331	94.49 365	97.27 343	97.90 341	92.77 320	99.80 214	96.57 252	99.32 280	99.16 271

Test_1112_low_res		96.99 300	96.55 311	98.31 252	99.35 168	95.47 292	95.84 374	99.53 95	91.51 409	96.80 367	98.48 294	91.36 338	99.83 181	96.58 250	99.53 246	99.62 84

1112_ss		97.29 277	96.86 289	98.58 212	99.34 170	96.32 261	96.75 319	99.58 70	93.14 390	96.89 362	97.48 364	92.11 330	99.86 132	96.91 217	99.54 242	99.57 113

ab-mvs-re		8.12 417	10.83 420	0.00 431	0.00 454	0.00 456	0.00 442	0.00 455	0.00 449	0.00 450	97.48 364	0.00 454	0.00 450	0.00 449	0.00 448	0.00 446

ab-mvs		98.41 170	98.36 166	98.59 211	99.19 204	97.23 215	99.32 26	98.81 303	97.66 215	98.62 233	99.40 93	96.82 194	99.80 214	95.88 294	99.51 251	98.75 335

TR-MVS		95.55 347	95.12 353	96.86 355	97.54 400	93.94 343	96.49 332	96.53 391	94.36 372	97.03 353	96.61 386	94.26 293	99.16 411	86.91 427	96.31 421	97.47 414

MDTV_nov1_ep13_2view						74.92 449	97.69 238		90.06 422	97.75 311		85.78 378		93.52 365		98.69 342

MDTV_nov1_ep13			95.22 350		97.06 420	83.20 440	97.74 233	96.16 395	94.37 371	96.99 354	98.83 232	83.95 394	99.53 354	93.90 354	97.95 389

MIMVSNet1		99.38 28	99.32 37	99.55 27	99.86 14	99.19 41	99.41 17	99.59 68	99.59 34	99.71 46	99.57 49	97.12 176	99.90 76	99.21 67	99.87 93	99.54 130

MIMVSNet		96.62 314	96.25 322	97.71 300	99.04 241	94.66 320	99.16 54	96.92 383	97.23 267	97.87 301	99.10 164	86.11 376	99.65 311	91.65 396	99.21 301	98.82 319

IterMVS-LS		98.55 153	98.70 114	98.09 268	99.48 134	94.73 317	97.22 293	99.39 150	98.97 112	99.38 109	99.31 110	96.00 236	99.93 50	98.58 113	99.97 20	99.60 94
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet		97.69 244	97.35 261	98.69 193	98.73 296	97.02 230	96.92 311	98.75 313	95.89 331	98.59 239	98.67 261	92.08 331	99.74 262	96.72 239	99.81 119	99.32 230
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref															99.77 146

IterMVS		97.73 241	98.11 200	96.57 362	99.24 190	90.28 410	95.52 385	99.21 223	98.86 124	99.33 119	99.33 105	93.11 311	99.94 41	98.49 120	99.94 48	99.48 163
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon		97.33 273	96.92 285	98.57 215	99.09 228	97.99 154	96.79 315	99.35 166	93.18 389	97.71 312	98.07 330	95.00 271	99.31 397	93.97 352	99.13 313	98.42 368

MVS_111021_LR		98.30 187	98.12 199	98.83 167	99.16 214	98.03 152	96.09 358	99.30 193	97.58 224	98.10 285	98.24 315	98.25 85	99.34 393	96.69 242	99.65 205	99.12 274

DP-MVS		98.93 89	98.81 99	99.28 91	99.21 197	98.45 111	98.46 136	99.33 178	99.63 28	99.48 87	99.15 152	97.23 171	99.75 257	97.17 195	99.66 204	99.63 83

ACMMP++															99.68 193

HQP-MVS		97.00 299	96.49 314	98.55 220	98.67 315	96.79 242	96.29 345	99.04 261	96.05 322	95.55 399	96.84 381	93.84 300	99.54 352	92.82 379	99.26 292	99.32 230

QAPM		97.31 274	96.81 295	98.82 168	98.80 290	97.49 198	99.06 65	99.19 229	90.22 419	97.69 314	99.16 148	96.91 188	99.90 76	90.89 411	99.41 268	99.07 278

Vis-MVSNet		99.34 30	99.36 31	99.27 94	99.73 37	98.26 123	99.17 53	99.78 35	99.11 88	99.27 131	99.48 74	98.82 36	99.95 26	98.94 88	99.93 53	99.59 101
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet		94.32 366	95.62 332	90.42 424	98.46 345	75.36 448	96.29 345	89.13 439	95.25 349	95.38 405	99.75 16	92.88 317	99.19 409	94.07 351	99.39 270	96.72 425

IS-MVSNet		98.19 201	97.90 224	99.08 126	99.57 89	97.97 158	99.31 30	98.32 338	99.01 108	98.98 173	99.03 181	91.59 335	99.79 227	95.49 313	99.80 130	99.48 163

HyFIR lowres test		97.19 285	96.60 309	98.96 150	99.62 82	97.28 212	95.17 395	99.50 101	94.21 374	99.01 170	98.32 311	86.61 370	99.99 2	97.10 203	99.84 104	99.60 94

EPMVS		93.72 379	93.27 378	95.09 400	96.04 437	87.76 422	98.13 168	85.01 445	94.69 362	96.92 356	98.64 269	78.47 420	99.31 397	95.04 320	96.46 419	98.20 379

PAPM_NR		96.82 307	96.32 318	98.30 253	99.07 232	96.69 249	97.48 269	98.76 310	95.81 333	96.61 374	96.47 390	94.12 297	99.17 410	90.82 412	97.78 391	99.06 279

TAMVS		98.24 196	98.05 207	98.80 172	99.07 232	97.18 222	97.88 210	98.81 303	96.66 300	99.17 150	99.21 135	94.81 278	99.77 244	96.96 215	99.88 89	99.44 181

PAPR		95.29 351	94.47 362	97.75 294	97.50 408	95.14 305	94.89 403	98.71 318	91.39 411	95.35 406	95.48 411	94.57 284	99.14 413	84.95 430	97.37 404	98.97 297

RPSCF		98.62 143	98.36 166	99.42 63	99.65 68	99.42 11	98.55 117	99.57 77	97.72 212	98.90 193	99.26 122	96.12 231	99.52 358	95.72 304	99.71 178	99.32 230

Vis-MVSNet (Re-imp)		97.46 261	97.16 271	98.34 249	99.55 101	96.10 265	98.94 80	98.44 332	98.32 163	98.16 278	98.62 273	88.76 357	99.73 267	93.88 356	99.79 135	99.18 264

test_0402		98.76 114	98.71 111	98.93 155	99.56 97	98.14 136	98.45 138	99.34 172	99.28 69	98.95 181	98.91 213	98.34 79	99.79 227	95.63 308	99.91 74	98.86 316

MVS_111021_HR		98.25 195	98.08 204	98.75 185	99.09 228	97.46 202	95.97 362	99.27 208	97.60 223	97.99 294	98.25 314	98.15 100	99.38 388	96.87 225	99.57 233	99.42 188

CSCG		98.68 131	98.50 142	99.20 105	99.45 143	98.63 94	98.56 116	99.57 77	97.87 202	98.85 203	98.04 332	97.66 135	99.84 163	96.72 239	99.81 119	99.13 273

PatchMatch-RL		97.24 281	96.78 296	98.61 208	99.03 244	97.83 173	96.36 340	99.06 255	93.49 387	97.36 341	97.78 346	95.75 250	99.49 367	93.44 368	98.77 345	98.52 356

API-MVS		97.04 295	96.91 287	97.42 326	97.88 381	98.23 129	98.18 161	98.50 330	97.57 225	97.39 339	96.75 383	96.77 198	99.15 412	90.16 415	99.02 326	94.88 437

Test By Simon												96.52 213

TDRefinement		99.42 24	99.38 28	99.55 27	99.76 30	99.33 20	99.68 6	99.71 44	99.38 56	99.53 77	99.61 43	98.64 52	99.80 214	98.24 131	99.84 104	99.52 142

USDC		97.41 267	97.40 256	97.44 325	98.94 256	93.67 355	95.17 395	99.53 95	94.03 379	98.97 177	99.10 164	95.29 263	99.34 393	95.84 300	99.73 165	99.30 237

EPP-MVSNet		98.30 187	98.04 208	99.07 128	99.56 97	97.83 173	99.29 36	98.07 349	99.03 106	98.59 239	99.13 157	92.16 329	99.90 76	96.87 225	99.68 193	99.49 153

PMMVS		96.51 316	95.98 323	98.09 268	97.53 402	95.84 278	94.92 402	98.84 298	91.58 407	96.05 391	95.58 406	95.68 252	99.66 306	95.59 310	98.09 381	98.76 334

PAPM		91.88 405	90.34 408	96.51 363	98.06 374	92.56 374	92.44 434	97.17 373	86.35 431	90.38 438	96.01 397	86.61 370	99.21 408	70.65 444	95.43 429	97.75 404

ACMMP		98.75 115	98.50 142	99.52 43	99.56 97	99.16 47	98.87 87	99.37 156	97.16 273	98.82 209	99.01 191	97.71 132	99.87 124	96.29 276	99.69 188	99.54 130
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		97.17 287	96.71 300	98.55 220	98.56 335	98.05 151	96.33 342	98.93 277	96.91 287	97.06 350	97.39 369	94.38 289	99.45 377	91.66 395	99.18 307	98.14 382

PatchmatchNet		95.58 346	95.67 331	95.30 397	97.34 412	87.32 425	97.65 245	96.65 387	95.30 348	97.07 349	98.69 257	84.77 385	99.75 257	94.97 323	98.64 357	98.83 318
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS		98.29 190	97.95 217	99.34 78	98.44 348	99.16 47	98.12 171	99.38 152	96.01 326	98.06 288	98.43 298	97.80 127	99.67 295	95.69 306	99.58 229	99.20 256

F-COLMAP		97.30 275	96.68 302	99.14 116	99.19 204	98.39 113	97.27 288	99.30 193	92.93 393	96.62 373	98.00 333	95.73 251	99.68 292	92.62 385	98.46 365	99.35 221

ANet_high		99.57 10	99.67 6	99.28 91	99.89 6	98.09 141	99.14 57	99.93 5	99.82 8	99.93 6	99.81 8	99.17 19	99.94 41	99.31 58	100.00 1	99.82 33

wuyk23d		96.06 330	97.62 245	91.38 423	98.65 324	98.57 101	98.85 90	96.95 381	96.86 290	99.90 13	99.16 148	99.18 18	98.40 430	89.23 419	99.77 146	77.18 443

OMC-MVS		97.88 227	97.49 252	99.04 137	98.89 271	98.63 94	96.94 307	99.25 214	95.02 354	98.53 249	98.51 287	97.27 168	99.47 373	93.50 367	99.51 251	99.01 288

MG-MVS		96.77 308	96.61 307	97.26 333	98.31 358	93.06 364	95.93 367	98.12 348	96.45 309	97.92 296	98.73 249	93.77 304	99.39 386	91.19 406	99.04 322	99.33 228

AdaColmap		97.14 289	96.71 300	98.46 233	98.34 356	97.80 180	96.95 306	98.93 277	95.58 339	96.92 356	97.66 353	95.87 247	99.53 354	90.97 408	99.14 311	98.04 387

uanet		0.00 418	0.00 421	0.00 431	0.00 454	0.00 456	0.00 442	0.00 455	0.00 449	0.00 450	0.00 449	0.00 454	0.00 450	0.00 449	0.00 448	0.00 446

ITE_SJBPF				98.87 163	99.22 195	98.48 109		99.35 166	97.50 233	98.28 270	98.60 277	97.64 139	99.35 392	93.86 357	99.27 289	98.79 330

DeepMVS_CX				93.44 417	98.24 362	94.21 331		94.34 417	64.28 443	91.34 437	94.87 424	89.45 355	92.77 444	77.54 441	93.14 437	93.35 439

TinyColmap		97.89 225	97.98 214	97.60 308	98.86 275	94.35 328	96.21 349	99.44 130	97.45 243	99.06 159	98.88 223	97.99 113	99.28 403	94.38 343	99.58 229	99.18 264

MAR-MVS		96.47 320	95.70 329	98.79 175	97.92 379	99.12 61	98.28 152	98.60 325	92.16 403	95.54 402	96.17 395	94.77 281	99.52 358	89.62 417	98.23 371	97.72 406
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		97.90 223	97.69 237	98.52 225	99.17 212	97.66 189	97.19 297	99.47 118	96.31 314	97.85 304	98.20 319	96.71 204	99.52 358	94.62 331	99.72 173	98.38 371

MSDG		97.71 243	97.52 250	98.28 255	98.91 265	96.82 240	94.42 416	99.37 156	97.65 216	98.37 265	98.29 313	97.40 161	99.33 395	94.09 350	99.22 298	98.68 345

LS3D		98.63 140	98.38 164	99.36 69	97.25 414	99.38 12	99.12 60	99.32 180	99.21 75	98.44 257	98.88 223	97.31 164	99.80 214	96.58 250	99.34 278	98.92 306

CLD-MVS		97.49 259	97.16 271	98.48 231	99.07 232	97.03 229	94.71 406	99.21 223	94.46 367	98.06 288	97.16 376	97.57 145	99.48 370	94.46 336	99.78 140	98.95 300
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS		93.44 383	92.23 390	97.08 340	99.25 189	97.86 170	95.61 380	97.16 374	92.90 394	93.76 427	98.65 266	75.94 422	95.66 441	79.30 440	97.49 397	97.73 405

Gipuma		99.03 75	99.16 58	98.64 199	99.94 2	98.51 107	99.32 26	99.75 40	99.58 36	98.60 237	99.62 40	98.22 90	99.51 363	97.70 169	99.73 165	97.89 395
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015

High-resolution multi-view benchmark