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 21	99.85 16	99.11 59	99.90 1	99.78 26	99.63 17	99.78 26	99.67 25	99.48 9	99.81 177	99.30 41	99.97 19	99.77 34
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 85	98.73 84	99.05 126	98.76 265	97.81 170	99.25 39	99.30 172	98.57 120	98.55 218	99.33 88	97.95 99	99.90 63	97.16 168	99.67 174	99.44 153

3Dnovator+	97.89 3	98.69 105	98.51 117	99.24 94	98.81 260	98.40 106	99.02 64	99.19 207	98.99 91	98.07 255	99.28 95	97.11 159	99.84 135	96.84 200	99.32 254	99.47 143

DeepC-MVS	97.60 4	98.97 65	98.93 66	99.10 113	99.35 150	97.98 150	98.01 172	99.46 106	97.56 195	99.54 55	99.50 58	98.97 23	99.84 135	98.06 117	99.92 54	99.49 126
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	98.32 161	98.01 185	99.23 96	98.39 324	98.97 66	95.03 364	99.18 211	96.88 253	99.33 95	98.78 213	98.16 84	99.28 373	96.74 208	99.62 188	99.44 153

DeepC-MVS_fast	96.85 6	98.30 164	98.15 172	98.75 172	98.61 295	97.23 204	97.76 205	99.09 230	97.31 222	98.75 192	98.66 234	97.56 127	99.64 287	96.10 257	99.55 214	99.39 173
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	97.09 264	96.68 275	98.32 225	98.32 327	97.16 212	98.86 81	99.37 136	89.48 388	96.29 353	99.15 125	96.56 190	99.90 63	92.90 344	99.20 274	97.89 360

ACMH	96.65 7	99.25 33	99.24 39	99.26 89	99.72 43	98.38 108	99.07 60	99.55 72	98.30 133	99.65 45	99.45 69	99.22 15	99.76 222	98.44 94	99.77 124	99.64 62
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMH+	96.62 9	99.08 56	99.00 62	99.33 77	99.71 46	98.83 76	98.60 102	99.58 54	99.11 72	99.53 59	99.18 115	98.81 32	99.67 268	96.71 213	99.77 124	99.50 122

COLMAP_ROB	96.50 10	98.99 61	98.85 74	99.41 59	99.58 76	99.10 60	98.74 86	99.56 68	99.09 82	99.33 95	99.19 112	98.40 63	99.72 247	95.98 260	99.76 135	99.42 160
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	96.63 286	95.95 296	98.65 180	98.93 232	98.09 134	96.93 277	99.28 183	83.58 401	98.13 250	97.78 313	96.13 207	99.40 354	93.52 333	99.29 261	98.45 328
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMM	96.08 12	98.91 72	98.73 84	99.48 50	99.55 92	99.14 52	98.07 161	99.37 136	97.62 185	99.04 141	98.96 174	98.84 30	99.79 199	97.43 155	99.65 180	99.49 126
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
HY-MVS	95.94 13	95.90 308	95.35 317	97.55 289	97.95 348	94.79 290	98.81 85	96.94 353	92.28 367	95.17 375	98.57 249	89.90 325	99.75 230	91.20 372	97.33 374	98.10 351

OpenMVS_ROB	95.38 14	95.84 310	95.18 322	97.81 263	98.41 323	97.15 213	97.37 248	98.62 300	83.86 400	98.65 201	98.37 271	94.29 274	99.68 265	88.41 386	98.62 330	96.60 391

ACMP	95.32 15	98.41 148	98.09 177	99.36 63	99.51 104	98.79 79	97.68 213	99.38 131	95.76 299	98.81 185	98.82 207	98.36 65	99.82 162	94.75 295	99.77 124	99.48 136
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PLC	94.65 16	96.51 289	95.73 300	98.85 152	98.75 267	97.91 157	96.42 303	99.06 233	90.94 381	95.59 364	97.38 338	94.41 269	99.59 304	90.93 376	98.04 356	99.05 250
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
PVSNet	93.40 17	95.67 314	95.70 301	95.57 360	98.83 254	88.57 386	92.50 398	97.72 331	92.69 362	96.49 350	96.44 359	93.72 287	99.43 350	93.61 330	99.28 262	98.71 305

PCF-MVS	92.86 18	94.36 334	93.00 351	98.42 217	98.70 278	97.56 186	93.16 396	99.11 227	79.59 405	97.55 293	97.43 335	92.19 307	99.73 240	79.85 405	99.45 237	97.97 359
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
IB-MVS	91.63 19	92.24 367	90.90 371	96.27 342	97.22 384	91.24 371	94.36 383	93.33 392	92.37 365	92.24 400	94.58 393	66.20 406	99.89 73	93.16 341	94.63 399	97.66 373
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	97.86 205	97.94 193	97.65 279	99.71 46	97.94 156	98.52 111	98.68 295	98.99 91	97.52 296	99.35 82	97.41 141	98.18 400	91.59 365	99.67 174	96.82 388
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PVSNet_0	89.98 21	91.15 372	90.30 375	93.70 381	97.72 359	84.34 406	90.24 402	97.42 337	90.20 385	93.79 392	93.09 401	90.90 318	98.89 393	86.57 394	72.76 409	97.87 362

MVE	83.40 22	92.50 362	91.92 364	94.25 374	98.83 254	91.64 361	92.71 397	83.52 411	95.92 295	86.46 409	95.46 379	95.20 247	95.40 407	80.51 404	98.64 327	95.73 400
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CMPMVS	75.91 23	96.29 297	95.44 312	98.84 153	96.25 402	98.69 87	97.02 270	99.12 225	88.90 391	97.83 274	98.86 198	89.51 327	98.90 392	91.92 358	99.51 225	98.92 275
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
dongtai		76.24 376	75.95 379	77.12 392	92.39 410	67.91 416	90.16 403	59.44 417	82.04 403	89.42 405	94.67 392	49.68 415	81.74 410	48.06 410	77.66 408	81.72 406

kuosan		69.30 377	68.95 380	70.34 393	87.68 414	65.00 417	91.11 401	59.90 416	69.02 406	74.46 411	88.89 408	48.58 416	68.03 412	28.61 411	72.33 410	77.99 407

MVSMamba_pp		98.01 193	97.90 197	98.32 225	97.95 348	96.59 235	97.57 230	99.38 131	96.07 287	97.99 261	99.01 160	95.57 235	99.80 184	97.76 140	99.82 94	98.57 320

MGCFI-Net		98.34 157	98.28 154	98.51 207	98.47 313	97.59 185	98.96 71	99.48 96	99.18 69	97.40 306	95.50 376	98.66 43	99.50 334	98.18 108	98.71 320	98.44 330

testing91		93.32 352	92.27 355	96.47 337	97.54 370	91.25 370	96.17 320	96.76 357	97.18 238	93.65 394	93.50 399	65.11 408	99.63 290	93.04 342	97.45 365	98.53 322

testing11		93.08 356	92.02 360	96.26 343	97.56 368	90.83 377	96.32 309	95.70 373	96.47 273	92.66 398	93.73 396	64.36 409	99.59 304	93.77 328	97.57 361	98.37 339

testing99		93.04 357	91.98 363	96.23 345	97.53 372	90.70 379	96.35 307	95.94 370	96.87 254	93.41 395	93.43 400	63.84 410	99.59 304	93.24 340	97.19 375	98.40 335

UWE-MVS		92.38 364	91.76 367	94.21 375	97.16 385	84.65 402	95.42 353	88.45 406	95.96 293	96.17 354	95.84 371	66.36 404	99.71 248	91.87 360	98.64 327	98.28 342

ETVMVS		92.60 361	91.08 370	97.18 309	97.70 363	93.65 332	96.54 295	95.70 373	96.51 269	94.68 381	92.39 404	61.80 411	99.50 334	86.97 391	97.41 368	98.40 335

sasdasda		98.34 157	98.26 158	98.58 193	98.46 315	97.82 167	98.96 71	99.46 106	99.19 67	97.46 301	95.46 379	98.59 50	99.46 345	98.08 115	98.71 320	98.46 325

testing222		91.96 369	90.37 373	96.72 333	97.47 378	92.59 347	96.11 322	94.76 379	96.83 256	92.90 397	92.87 402	57.92 412	99.55 318	86.93 392	97.52 362	98.00 358

WB-MVSnew		95.73 313	95.57 307	96.23 345	96.70 395	90.70 379	96.07 324	93.86 389	95.60 303	97.04 320	95.45 382	96.00 214	99.55 318	91.04 374	98.31 338	98.43 332

fmvsm_l_conf0.5_n_a		99.19 41	99.27 35	98.94 141	99.65 64	97.05 216	97.80 198	99.76 28	98.70 110	99.78 26	99.11 132	98.79 34	99.95 22	99.85 5	99.96 24	99.83 21

fmvsm_l_conf0.5_n		99.21 39	99.28 34	99.02 131	99.64 69	97.28 201	97.82 195	99.76 28	98.73 107	99.82 21	99.09 138	98.81 32	99.95 22	99.86 4	99.96 24	99.83 21

fmvsm_s_conf0.1_n_a		99.17 42	99.30 32	98.80 159	99.75 34	96.59 235	97.97 179	99.86 13	98.22 141	99.88 17	99.71 17	98.59 50	99.84 135	99.73 19	99.98 12	99.98 2

fmvsm_s_conf0.1_n		99.16 45	99.33 26	98.64 181	99.71 46	96.10 248	97.87 191	99.85 15	98.56 122	99.90 12	99.68 20	98.69 41	99.85 118	99.72 21	99.98 12	99.97 3

fmvsm_s_conf0.5_n_a		99.10 53	99.20 41	98.78 165	99.55 92	96.59 235	97.79 199	99.82 22	98.21 142	99.81 23	99.53 53	98.46 60	99.84 135	99.70 22	99.97 19	99.90 10

fmvsm_s_conf0.5_n		99.09 54	99.26 37	98.61 189	99.55 92	96.09 251	97.74 207	99.81 23	98.55 123	99.85 19	99.55 47	98.60 49	99.84 135	99.69 24	99.98 12	99.89 11

MM		98.22 174	97.99 188	98.91 146	98.66 291	96.97 220	97.89 187	94.44 382	99.54 27	98.95 155	99.14 128	93.50 288	99.92 49	99.80 12	99.96 24	99.85 18

WAC-MVS						90.90 375								91.37 369

Syy-MVS		96.04 303	95.56 308	97.49 295	97.10 387	94.48 301	96.18 318	96.58 360	95.65 301	94.77 379	92.29 405	91.27 316	99.36 359	98.17 110	98.05 354	98.63 315

test_fmvsmconf0.1_n		99.49 12	99.54 10	99.34 72	99.78 24	98.11 131	97.77 202	99.90 9	99.33 49	99.97 3	99.66 27	99.71 3	99.96 11	99.79 13	99.99 5	99.96 5

test_fmvsmconf0.01_n		99.57 7	99.63 7	99.36 63	99.87 12	98.13 130	98.08 159	99.95 1	99.45 35	99.98 2	99.75 11	99.80 1	99.97 4	99.82 8	99.99 5	99.99 1

myMVS_eth3d		91.92 370	90.45 372	96.30 340	97.10 387	90.90 375	96.18 318	96.58 360	95.65 301	94.77 379	92.29 405	53.88 413	99.36 359	89.59 384	98.05 354	98.63 315

testing3		93.51 349	92.09 358	97.75 270	98.60 297	94.40 303	97.32 252	95.26 377	97.56 195	96.79 337	95.50 376	53.57 414	99.77 216	95.26 286	98.97 304	99.08 246

SSC-MVS		98.71 98	98.74 82	98.62 186	99.72 43	96.08 253	98.74 86	98.64 299	99.74 6	99.67 41	99.24 104	94.57 266	99.95 22	99.11 51	99.24 268	99.82 24

test_fmvsmconf_n		99.44 15	99.48 14	99.31 82	99.64 69	98.10 133	97.68 213	99.84 18	99.29 54	99.92 8	99.57 41	99.60 5	99.96 11	99.74 18	99.98 12	99.89 11

WB-MVS		98.52 138	98.55 112	98.43 216	99.65 64	95.59 264	98.52 111	98.77 286	99.65 14	99.52 61	99.00 164	94.34 272	99.93 39	98.65 82	98.83 312	99.76 38

test_fmvsmvis_n_1920		99.26 32	99.49 12	98.54 204	99.66 63	96.97 220	98.00 173	99.85 15	99.24 58	99.92 8	99.50 58	99.39 11	99.95 22	99.89 3	99.98 12	98.71 305

dmvs_re		95.98 306	95.39 315	97.74 272	98.86 248	97.45 192	98.37 133	95.69 375	97.95 161	96.56 344	95.95 366	90.70 319	97.68 402	88.32 387	96.13 390	98.11 350

SDMVSNet		99.23 38	99.32 28	98.96 138	99.68 57	97.35 197	98.84 84	99.48 96	99.69 9	99.63 48	99.68 20	99.03 21	99.96 11	97.97 124	99.92 54	99.57 90

dmvs_testset		92.94 358	92.21 357	95.13 367	98.59 300	90.99 374	97.65 219	92.09 397	96.95 249	94.00 390	93.55 398	92.34 306	96.97 405	72.20 408	92.52 403	97.43 380

sd_testset		99.28 29	99.31 30	99.19 100	99.68 57	98.06 143	99.41 12	99.30 172	99.69 9	99.63 48	99.68 20	99.25 14	99.96 11	97.25 164	99.92 54	99.57 90

test_fmvsm_n_1920		99.33 26	99.45 18	98.99 134	99.57 80	97.73 177	97.93 180	99.83 20	99.22 59	99.93 6	99.30 93	99.42 10	99.96 11	99.85 5	99.99 5	99.29 210

test_cas_vis1_n_1920		98.33 160	98.68 94	97.27 306	99.69 55	92.29 355	98.03 167	99.85 15	97.62 185	99.96 4	99.62 33	93.98 281	99.74 235	99.52 31	99.86 78	99.79 29

test_vis1_n_1920		98.40 150	98.92 67	96.81 329	99.74 36	90.76 378	98.15 151	99.91 7	98.33 130	99.89 15	99.55 47	95.07 251	99.88 82	99.76 16	99.93 43	99.79 29

test_vis1_n		98.31 163	98.50 119	97.73 274	99.76 30	94.17 310	98.68 95	99.91 7	96.31 279	99.79 25	99.57 41	92.85 300	99.42 352	99.79 13	99.84 83	99.60 73

test_fmvs1_n		98.09 186	98.28 154	97.52 292	99.68 57	93.47 334	98.63 98	99.93 4	95.41 312	99.68 39	99.64 31	91.88 312	99.48 340	99.82 8	99.87 75	99.62 66

mvsany_test1		97.60 226	97.54 224	97.77 266	97.72 359	95.35 275	95.36 355	97.13 346	94.13 341	99.71 33	99.33 88	97.93 100	99.30 369	97.60 145	98.94 307	98.67 313

APD_test1		98.83 82	98.66 97	99.34 72	99.78 24	99.47 6	98.42 129	99.45 110	98.28 138	98.98 148	99.19 112	97.76 110	99.58 310	96.57 222	99.55 214	98.97 266

test_vis1_rt		97.75 216	97.72 211	97.83 261	98.81 260	96.35 243	97.30 254	99.69 36	94.61 328	97.87 269	98.05 298	96.26 204	98.32 399	98.74 75	98.18 343	98.82 287

test_vis3_rt		99.14 46	99.17 43	99.07 119	99.78 24	98.38 108	98.92 76	99.94 2	97.80 173	99.91 11	99.67 25	97.15 156	98.91 391	99.76 16	99.56 211	99.92 9

test_fmvs2		98.70 102	98.97 65	97.89 258	99.54 97	94.05 312	98.55 107	99.92 6	96.78 259	99.72 31	99.78 8	96.60 189	99.67 268	99.91 2	99.90 67	99.94 7

test_fmvs1		97.72 218	97.94 193	97.07 316	98.66 291	92.39 352	97.68 213	99.81 23	95.20 317	99.54 55	99.44 70	91.56 314	99.41 353	99.78 15	99.77 124	99.40 172

test_fmvs3		99.12 51	99.41 19	98.25 234	99.76 30	95.07 286	99.05 63	99.94 2	97.78 176	99.82 21	99.84 2	98.56 54	99.71 248	99.96 1	99.96 24	99.97 3

mvsany_test3		98.87 77	98.92 67	98.74 176	99.38 139	96.94 224	98.58 104	99.10 228	96.49 271	99.96 4	99.81 5	98.18 80	99.45 347	98.97 62	99.79 114	99.83 21

testf1		99.25 33	99.16 45	99.51 42	99.89 6	99.63 3	98.71 92	99.69 36	98.90 99	99.43 75	99.35 82	98.86 28	99.67 268	97.81 133	99.81 99	99.24 220

APD_test2		99.25 33	99.16 45	99.51 42	99.89 6	99.63 3	98.71 92	99.69 36	98.90 99	99.43 75	99.35 82	98.86 28	99.67 268	97.81 133	99.81 99	99.24 220

test_f		98.67 113	98.87 70	98.05 251	99.72 43	95.59 264	98.51 116	99.81 23	96.30 281	99.78 26	99.82 4	96.14 206	98.63 396	99.82 8	99.93 43	99.95 6

FE-MVS		95.66 315	94.95 327	97.77 266	98.53 309	95.28 277	99.40 15	96.09 367	93.11 356	97.96 263	99.26 99	79.10 387	99.77 216	92.40 356	98.71 320	98.27 343

FA-MVS(test-final)		96.99 273	96.82 266	97.50 294	98.70 278	94.78 291	99.34 19	96.99 349	95.07 318	98.48 225	99.33 88	88.41 338	99.65 284	96.13 256	98.92 309	98.07 353

iter_conf05_11		97.26 250	97.11 250	97.69 276	97.89 353	95.88 257	95.06 363	99.03 241	95.33 313	97.39 308	97.10 349	95.79 227	99.76 222	96.68 215	99.74 139	97.43 380

bld_raw_dy_0_64		97.85 210	97.71 212	98.26 233	98.31 328	96.74 232	95.53 346	99.31 163	97.79 174	97.85 272	97.56 327	95.70 230	99.82 162	97.52 151	99.84 83	98.22 344

patch_mono-2		98.51 139	98.63 101	98.17 240	99.38 139	94.78 291	97.36 249	99.69 36	98.16 152	98.49 224	99.29 94	97.06 160	99.97 4	98.29 103	99.91 61	99.76 38

EGC-MVSNET		85.24 373	80.54 376	99.34 72	99.77 27	99.20 34	99.08 57	99.29 180	12.08 411	20.84 412	99.42 72	97.55 128	99.85 118	97.08 176	99.72 150	98.96 268

test2506		92.39 363	91.89 365	93.89 379	99.38 139	82.28 409	99.32 22	66.03 415	99.08 84	98.77 189	99.57 41	66.26 405	99.84 135	98.71 78	99.95 31	99.54 107

test1111		96.49 292	96.82 266	95.52 361	99.42 134	87.08 394	99.22 41	87.14 407	99.11 72	99.46 70	99.58 40	88.69 332	99.86 106	98.80 70	99.95 31	99.62 66

ECVR-MVS		96.42 294	96.61 280	95.85 353	99.38 139	88.18 390	99.22 41	86.00 409	99.08 84	99.36 90	99.57 41	88.47 337	99.82 162	98.52 91	99.95 31	99.54 107

test_blank		0.00 383	0.00 386	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.00 414	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

tt0805		98.69 105	98.62 103	98.90 149	99.75 34	99.30 17	99.15 52	96.97 350	98.86 102	98.87 176	97.62 324	98.63 46	98.96 388	99.41 36	98.29 339	98.45 328

DVP-MVS++		98.90 74	98.70 91	99.51 42	98.43 319	99.15 47	99.43 10	99.32 158	98.17 149	99.26 110	99.02 151	98.18 80	99.88 82	97.07 177	99.45 237	99.49 126

FOURS1					99.73 37	99.67 2	99.43 10	99.54 77	99.43 39	99.26 110

MSC_two_6792asdad				99.32 79	98.43 319	98.37 110		98.86 271					99.89 73	97.14 171	99.60 195	99.71 45

PC_three_1452									93.27 353	99.40 82	98.54 251	98.22 76	97.00 404	95.17 287	99.45 237	99.49 126

No_MVS				99.32 79	98.43 319	98.37 110		98.86 271					99.89 73	97.14 171	99.60 195	99.71 45

test_one_0601					99.39 138	99.20 34		99.31 163	98.49 124	98.66 200	99.02 151	97.64 120

eth-test2					0.00 419

eth-test					0.00 419

GeoE		99.05 57	98.99 64	99.25 92	99.44 128	98.35 114	98.73 89	99.56 68	98.42 126	98.91 166	98.81 209	98.94 25	99.91 58	98.35 98	99.73 143	99.49 126

test_method		79.78 374	79.50 377	80.62 390	80.21 415	45.76 418	70.82 406	98.41 311	31.08 410	80.89 410	97.71 317	84.85 358	97.37 403	91.51 367	80.03 407	98.75 302

Anonymous20240521		98.69 105	98.87 70	98.16 242	99.77 27	95.11 285	99.08 57	99.44 114	99.34 48	99.33 95	99.55 47	94.10 280	99.94 34	99.25 44	99.96 24	99.42 160

h-mvs33		97.77 215	97.33 239	99.10 113	99.21 173	97.84 163	98.35 135	98.57 302	99.11 72	98.58 213	99.02 151	88.65 335	99.96 11	98.11 112	96.34 386	99.49 126

hse-mvs2		97.46 235	97.07 251	98.64 181	98.73 269	97.33 198	97.45 244	97.64 336	99.11 72	98.58 213	97.98 302	88.65 335	99.79 199	98.11 112	97.39 369	98.81 291

CL-MVSNet_self_test		97.44 238	97.22 243	98.08 247	98.57 304	95.78 262	94.30 384	98.79 283	96.58 268	98.60 209	98.19 287	94.74 264	99.64 287	96.41 238	98.84 311	98.82 287

KD-MVS_2432*1600		92.87 359	91.99 361	95.51 362	91.37 411	89.27 384	94.07 386	98.14 321	95.42 309	97.25 313	96.44 359	67.86 400	99.24 375	91.28 370	96.08 391	98.02 355

KD-MVS_self_test		99.25 33	99.18 42	99.44 56	99.63 73	99.06 64	98.69 94	99.54 77	99.31 51	99.62 51	99.53 53	97.36 144	99.86 106	99.24 46	99.71 155	99.39 173

AUN-MVS		96.24 300	95.45 311	98.60 191	98.70 278	97.22 206	97.38 247	97.65 334	95.95 294	95.53 371	97.96 306	82.11 377	99.79 199	96.31 243	97.44 366	98.80 296

ZD-MVS					99.01 220	98.84 75		99.07 232	94.10 342	98.05 258	98.12 291	96.36 201	99.86 106	92.70 352	99.19 277

SR-MVS-dyc-post		98.81 85	98.55 112	99.57 16	99.20 177	99.38 8	98.48 122	99.30 172	98.64 111	98.95 155	98.96 174	97.49 138	99.86 106	96.56 226	99.39 244	99.45 149

RE-MVS-def			98.58 110		99.20 177	99.38 8	98.48 122	99.30 172	98.64 111	98.95 155	98.96 174	97.75 111		96.56 226	99.39 244	99.45 149

SED-MVS		98.91 72	98.72 86	99.49 47	99.49 114	99.17 39	98.10 157	99.31 163	98.03 156	99.66 42	99.02 151	98.36 65	99.88 82	96.91 189	99.62 188	99.41 163

IU-MVS					99.49 114	99.15 47		98.87 266	92.97 357	99.41 79				96.76 206	99.62 188	99.66 57

OPU-MVS				98.82 155	98.59 300	98.30 115	98.10 157				98.52 254	98.18 80	98.75 395	94.62 299	99.48 234	99.41 163

test_241102_TWO								99.30 172	98.03 156	99.26 110	99.02 151	97.51 134	99.88 82	96.91 189	99.60 195	99.66 57

test_241102_ONE					99.49 114	99.17 39		99.31 163	97.98 158	99.66 42	98.90 187	98.36 65	99.48 340

SF-MVS		98.53 135	98.27 157	99.32 79	99.31 153	98.75 80	98.19 146	99.41 124	96.77 260	98.83 180	98.90 187	97.80 108	99.82 162	95.68 276	99.52 223	99.38 180

cl22		95.79 311	95.39 315	96.98 319	96.77 394	92.79 344	94.40 382	98.53 304	94.59 329	97.89 267	98.17 288	82.82 374	99.24 375	96.37 239	99.03 295	98.92 275

miper_ehance_all_eth		97.06 266	97.03 253	97.16 313	97.83 355	93.06 338	94.66 374	99.09 230	95.99 292	98.69 196	98.45 264	92.73 302	99.61 299	96.79 202	99.03 295	98.82 287

miper_enhance_ethall		96.01 304	95.74 299	96.81 329	96.41 400	92.27 356	93.69 393	98.89 263	91.14 379	98.30 238	97.35 341	90.58 320	99.58 310	96.31 243	99.03 295	98.60 317

ZNCC-MVS		98.68 110	98.40 136	99.54 26	99.57 80	99.21 28	98.46 124	99.29 180	97.28 225	98.11 252	98.39 268	98.00 94	99.87 99	96.86 199	99.64 182	99.55 103

dcpmvs_2		98.78 89	99.11 52	97.78 265	99.56 88	93.67 330	99.06 61	99.86 13	99.50 30	99.66 42	99.26 99	97.21 154	99.99 2	98.00 122	99.91 61	99.68 53

cl____		97.02 269	96.83 265	97.58 285	97.82 356	94.04 314	94.66 374	99.16 218	97.04 245	98.63 203	98.71 223	88.68 334	99.69 256	97.00 181	99.81 99	99.00 261

DIV-MVS_self_test		97.02 269	96.84 264	97.58 285	97.82 356	94.03 315	94.66 374	99.16 218	97.04 245	98.63 203	98.71 223	88.69 332	99.69 256	97.00 181	99.81 99	99.01 258

eth_miper_zixun_eth		97.23 255	97.25 241	97.17 311	98.00 347	92.77 345	94.71 371	99.18 211	97.27 226	98.56 216	98.74 219	91.89 311	99.69 256	97.06 179	99.81 99	99.05 250

9.14			97.78 205		99.07 208		97.53 234	99.32 158	95.53 306	98.54 220	98.70 226	97.58 125	99.76 222	94.32 312	99.46 235

uanet_test		0.00 383	0.00 386	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.00 414	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

DCPMVS		0.00 383	0.00 386	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.00 414	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

save fliter					99.11 199	97.97 151	96.53 297	99.02 245	98.24 139

ET-MVSNet_ETH3D		94.30 337	93.21 347	97.58 285	98.14 339	94.47 302	94.78 370	93.24 393	94.72 326	89.56 404	95.87 369	78.57 390	99.81 177	96.91 189	97.11 378	98.46 325

UniMVSNet_ETH3D		99.69 2	99.69 4	99.69 3	99.84 17	99.34 15	99.69 4	99.58 54	99.90 2	99.86 18	99.78 8	99.58 6	99.95 22	99.00 60	99.95 31	99.78 32

EIA-MVS		98.00 194	97.74 208	98.80 159	98.72 271	98.09 134	98.05 164	99.60 51	97.39 214	96.63 341	95.55 374	97.68 114	99.80 184	96.73 210	99.27 263	98.52 323

miper_refine_blended		92.87 359	91.99 361	95.51 362	91.37 411	89.27 384	94.07 386	98.14 321	95.42 309	97.25 313	96.44 359	67.86 400	99.24 375	91.28 370	96.08 391	98.02 355

miper_lstm_enhance		97.18 259	97.16 246	97.25 308	98.16 338	92.85 343	95.15 361	99.31 163	97.25 228	98.74 194	98.78 213	90.07 323	99.78 210	97.19 166	99.80 109	99.11 245

ETV-MVS		98.03 190	97.86 202	98.56 200	98.69 283	98.07 140	97.51 238	99.50 87	98.10 154	97.50 298	95.51 375	98.41 62	99.88 82	96.27 246	99.24 268	97.71 372

CS-MVS		99.13 49	99.10 54	99.24 94	99.06 212	99.15 47	99.36 18	99.88 11	99.36 47	98.21 243	98.46 263	98.68 42	99.93 39	99.03 58	99.85 79	98.64 314

D2MVS		97.84 212	97.84 203	97.83 261	99.14 195	94.74 293	96.94 275	98.88 264	95.84 297	98.89 169	98.96 174	94.40 270	99.69 256	97.55 146	99.95 31	99.05 250

DVP-MVS		98.77 92	98.52 116	99.52 38	99.50 107	99.21 28	98.02 169	98.84 275	97.97 159	99.08 132	99.02 151	97.61 123	99.88 82	96.99 183	99.63 185	99.48 136
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									98.17 149	99.08 132	99.02 151	97.89 101	99.88 82	97.07 177	99.71 155	99.70 50

test_0728_SECOND				99.60 11	99.50 107	99.23 26	98.02 169	99.32 158					99.88 82	96.99 183	99.63 185	99.68 53

test0726					99.50 107	99.21 28	98.17 150	99.35 145	97.97 159	99.26 110	99.06 139	97.61 123

SR-MVS		98.71 98	98.43 132	99.57 16	99.18 187	99.35 12	98.36 134	99.29 180	98.29 136	98.88 172	98.85 201	97.53 131	99.87 99	96.14 254	99.31 256	99.48 136

DPM-MVS		96.32 296	95.59 306	98.51 207	98.76 265	97.21 207	94.54 380	98.26 315	91.94 369	96.37 351	97.25 342	93.06 295	99.43 350	91.42 368	98.74 316	98.89 279

GST-MVS		98.61 122	98.30 152	99.52 38	99.51 104	99.20 34	98.26 140	99.25 192	97.44 211	98.67 198	98.39 268	97.68 114	99.85 118	96.00 258	99.51 225	99.52 117

test_yl		96.69 282	96.29 291	97.90 256	98.28 330	95.24 278	97.29 255	97.36 339	98.21 142	98.17 244	97.86 309	86.27 346	99.55 318	94.87 293	98.32 336	98.89 279

thisisatest0530		95.27 323	94.45 332	97.74 272	99.19 180	94.37 304	97.86 192	90.20 403	97.17 239	98.22 242	97.65 321	73.53 397	99.90 63	96.90 194	99.35 250	98.95 269

Anonymous20240529		98.93 70	98.87 70	99.12 109	99.19 180	98.22 124	99.01 65	98.99 251	99.25 57	99.54 55	99.37 78	97.04 161	99.80 184	97.89 127	99.52 223	99.35 192

Anonymous202405211		97.90 199	97.50 227	99.08 117	98.90 240	98.25 118	98.53 110	96.16 365	98.87 101	99.11 127	98.86 198	90.40 322	99.78 210	97.36 158	99.31 256	99.19 232

DCV-MVSNet		96.69 282	96.29 291	97.90 256	98.28 330	95.24 278	97.29 255	97.36 339	98.21 142	98.17 244	97.86 309	86.27 346	99.55 318	94.87 293	98.32 336	98.89 279

tttt0517		95.64 316	94.98 325	97.64 281	99.36 146	93.81 326	98.72 90	90.47 402	98.08 155	98.67 198	98.34 275	73.88 396	99.92 49	97.77 136	99.51 225	99.20 227

our_test_3		97.39 241	97.73 210	96.34 339	98.70 278	89.78 383	94.61 377	98.97 252	96.50 270	99.04 141	98.85 201	95.98 219	99.84 135	97.26 163	99.67 174	99.41 163

thisisatest0515		94.12 341	93.16 348	96.97 320	98.60 297	92.90 342	93.77 392	90.61 401	94.10 342	96.91 327	95.87 369	74.99 395	99.80 184	94.52 302	99.12 288	98.20 346

ppachtmachnet_test		97.50 231	97.74 208	96.78 331	98.70 278	91.23 372	94.55 379	99.05 236	96.36 276	99.21 118	98.79 212	96.39 197	99.78 210	96.74 208	99.82 94	99.34 194

SMA-MVS		98.40 150	98.03 184	99.51 42	99.16 190	99.21 28	98.05 164	99.22 200	94.16 340	98.98 148	99.10 135	97.52 133	99.79 199	96.45 236	99.64 182	99.53 114
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																98.81 291

DPE-MVS		98.59 125	98.26 158	99.57 16	99.27 160	99.15 47	97.01 271	99.39 129	97.67 181	99.44 74	98.99 165	97.53 131	99.89 73	95.40 284	99.68 168	99.66 57
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part2					99.36 146	99.10 60				99.05 139

thres100view900		94.19 338	93.67 342	95.75 356	99.06 212	91.35 366	98.03 167	94.24 386	98.33 130	97.40 306	94.98 387	79.84 381	99.62 293	83.05 399	98.08 351	96.29 392

tfpnnormal		98.90 74	98.90 69	98.91 146	99.67 61	97.82 167	99.00 67	99.44 114	99.45 35	99.51 65	99.24 104	98.20 79	99.86 106	95.92 262	99.69 163	99.04 254

tfpn200view9		94.03 342	93.44 344	95.78 355	98.93 232	91.44 364	97.60 225	94.29 384	97.94 162	97.10 316	94.31 394	79.67 383	99.62 293	83.05 399	98.08 351	96.29 392

c3_l		97.36 242	97.37 235	97.31 303	98.09 342	93.25 336	95.01 365	99.16 218	97.05 244	98.77 189	98.72 222	92.88 298	99.64 287	96.93 188	99.76 135	99.05 250

CHOSEN 280x420		95.51 320	95.47 309	95.65 359	98.25 332	88.27 389	93.25 395	98.88 264	93.53 350	94.65 382	97.15 345	86.17 348	99.93 39	97.41 156	99.93 43	98.73 304

CANet		97.87 204	97.76 206	98.19 239	97.75 358	95.51 269	96.76 286	99.05 236	97.74 177	96.93 324	98.21 285	95.59 234	99.89 73	97.86 132	99.93 43	99.19 232

Fast-Effi-MVS+-dtu		98.27 168	98.09 177	98.81 157	98.43 319	98.11 131	97.61 224	99.50 87	98.64 111	97.39 308	97.52 330	98.12 87	99.95 22	96.90 194	98.71 320	98.38 337

Effi-MVS+-dtu		98.26 170	97.90 197	99.35 69	98.02 345	99.49 5	98.02 169	99.16 218	98.29 136	97.64 285	97.99 301	96.44 196	99.95 22	96.66 217	98.93 308	98.60 317

CANet_DTU		97.26 250	97.06 252	97.84 260	97.57 367	94.65 298	96.19 317	98.79 283	97.23 234	95.14 376	98.24 282	93.22 290	99.84 135	97.34 159	99.84 83	99.04 254

MVS_0304		98.10 183	97.88 200	98.76 169	98.82 257	96.50 239	97.90 185	91.35 400	99.56 26	98.32 237	99.13 129	96.06 210	99.93 39	99.84 7	99.97 19	99.85 18

MP-MVS-pluss		98.57 126	98.23 162	99.60 11	99.69 55	99.35 12	97.16 266	99.38 131	94.87 324	98.97 152	98.99 165	98.01 93	99.88 82	97.29 161	99.70 160	99.58 85
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MSP-MVS		98.40 150	98.00 187	99.61 9	99.57 80	99.25 24	98.57 105	99.35 145	97.55 197	99.31 103	97.71 317	94.61 265	99.88 82	96.14 254	99.19 277	99.70 50
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												84.74 360				98.81 291

sam_mvs												84.29 366

IterMVS-SCA-FT		97.85 210	98.18 167	96.87 325	99.27 160	91.16 373	95.53 346	99.25 192	99.10 79	99.41 79	99.35 82	93.10 293	99.96 11	98.65 82	99.94 39	99.49 126

TSAR-MVS + MP.		98.63 119	98.49 123	99.06 125	99.64 69	97.90 158	98.51 116	98.94 253	96.96 248	99.24 115	98.89 193	97.83 104	99.81 177	96.88 196	99.49 233	99.48 136
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		97.86 205	98.17 168	96.92 322	98.98 225	93.91 321	96.45 300	99.17 215	97.85 170	98.41 231	97.14 346	98.47 57	99.92 49	98.02 119	99.05 291	96.92 385

OPM-MVS		98.56 127	98.32 151	99.25 92	99.41 136	98.73 84	97.13 268	99.18 211	97.10 243	98.75 192	98.92 183	98.18 80	99.65 284	96.68 215	99.56 211	99.37 182
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMMP_NAP		98.75 94	98.48 124	99.57 16	99.58 76	99.29 19	97.82 195	99.25 192	96.94 250	98.78 186	99.12 131	98.02 92	99.84 135	97.13 173	99.67 174	99.59 79

ambc				98.24 236	98.82 257	95.97 255	98.62 100	99.00 250		99.27 106	99.21 109	96.99 166	99.50 334	96.55 229	99.50 232	99.26 216

MTGPA								99.20 203

CS-MVS-test		99.13 49	99.09 55	99.26 89	99.13 197	98.97 66	99.31 26	99.88 11	99.44 37	98.16 246	98.51 255	98.64 44	99.93 39	98.91 64	99.85 79	98.88 282

Effi-MVS+		98.02 191	97.82 204	98.62 186	98.53 309	97.19 209	97.33 251	99.68 41	97.30 223	96.68 339	97.46 334	98.56 54	99.80 184	96.63 218	98.20 342	98.86 284

xiu_mvs_v2_base		97.16 261	97.49 228	96.17 348	98.54 307	92.46 350	95.45 351	98.84 275	97.25 228	97.48 300	96.49 356	98.31 70	99.90 63	96.34 242	98.68 325	96.15 396

xiu_mvs_v1_base		97.86 205	98.17 168	96.92 322	98.98 225	93.91 321	96.45 300	99.17 215	97.85 170	98.41 231	97.14 346	98.47 57	99.92 49	98.02 119	99.05 291	96.92 385

new-patchmatchnet		98.35 156	98.74 82	97.18 309	99.24 166	92.23 357	96.42 303	99.48 96	98.30 133	99.69 37	99.53 53	97.44 140	99.82 162	98.84 69	99.77 124	99.49 126

pmmvs6		99.67 3	99.70 3	99.60 11	99.90 4	99.27 22	99.53 7	99.76 28	99.64 15	99.84 20	99.83 3	99.50 8	99.87 99	99.36 37	99.92 54	99.64 62

pmmvs5		97.64 224	97.49 228	98.08 247	99.14 195	95.12 284	96.70 290	99.05 236	93.77 347	98.62 205	98.83 204	93.23 289	99.75 230	98.33 101	99.76 135	99.36 188

test_post1							97.59 227				20.48 413	83.07 372	99.66 279	94.16 313

test_post											21.25 412	83.86 368	99.70 252

Fast-Effi-MVS+		97.67 222	97.38 234	98.57 196	98.71 274	97.43 194	97.23 259	99.45 110	94.82 325	96.13 355	96.51 355	98.52 56	99.91 58	96.19 250	98.83 312	98.37 339

patchmatchnet-post											98.77 215	84.37 363	99.85 118

Anonymous20231211		99.27 30	99.27 35	99.26 89	99.29 157	98.18 125	99.49 8	99.51 84	99.70 8	99.80 24	99.68 20	96.84 172	99.83 152	99.21 47	99.91 61	99.77 34

pmmvs-eth3d		98.47 142	98.34 147	98.86 151	99.30 156	97.76 173	97.16 266	99.28 183	95.54 305	99.42 78	99.19 112	97.27 149	99.63 290	97.89 127	99.97 19	99.20 227

GG-mvs-BLEND				94.76 370	94.54 408	92.13 358	99.31 26	80.47 413		88.73 407	91.01 407	67.59 402	98.16 401	82.30 403	94.53 400	93.98 403

xiu_mvs_v1_base_debi		97.86 205	98.17 168	96.92 322	98.98 225	93.91 321	96.45 300	99.17 215	97.85 170	98.41 231	97.14 346	98.47 57	99.92 49	98.02 119	99.05 291	96.92 385

Anonymous20231206		98.21 176	98.21 163	98.20 238	99.51 104	95.43 273	98.13 152	99.32 158	96.16 284	98.93 164	98.82 207	96.00 214	99.83 152	97.32 160	99.73 143	99.36 188

MTAPA		98.88 76	98.64 100	99.61 9	99.67 61	99.36 11	98.43 127	99.20 203	98.83 106	98.89 169	98.90 187	96.98 167	99.92 49	97.16 168	99.70 160	99.56 96

MTMP							97.93 180	91.91 398

gm-plane-assit					94.83 407	81.97 410			88.07 394		94.99 386		99.60 300	91.76 361

test9_res														93.28 339	99.15 282	99.38 180

MVP-Stereo		98.08 188	97.92 195	98.57 196	98.96 228	96.79 228	97.90 185	99.18 211	96.41 275	98.46 226	98.95 179	95.93 222	99.60 300	96.51 232	98.98 303	99.31 205
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST9					98.71 274	98.08 138	95.96 329	99.03 241	91.40 375	95.85 361	97.53 328	96.52 192	99.76 222

train_agg		97.10 263	96.45 287	99.07 119	98.71 274	98.08 138	95.96 329	99.03 241	91.64 370	95.85 361	97.53 328	96.47 194	99.76 222	93.67 329	99.16 280	99.36 188

gg-mvs-nofinetune		92.37 365	91.20 369	95.85 353	95.80 406	92.38 353	99.31 26	81.84 412	99.75 5	91.83 401	99.74 13	68.29 399	99.02 385	87.15 390	97.12 377	96.16 395

SCA		96.41 295	96.66 278	95.67 357	98.24 333	88.35 388	95.85 337	96.88 355	96.11 285	97.67 284	98.67 231	93.10 293	99.85 118	94.16 313	99.22 271	98.81 291

Patchmatch-test		96.55 288	96.34 289	97.17 311	98.35 325	93.06 338	98.40 130	97.79 329	97.33 219	98.41 231	98.67 231	83.68 369	99.69 256	95.16 288	99.31 256	98.77 299

test_8					98.67 286	98.01 146	95.91 334	99.02 245	91.64 370	95.79 363	97.50 331	96.47 194	99.76 222

MS-PatchMatch		97.68 221	97.75 207	97.45 298	98.23 335	93.78 327	97.29 255	98.84 275	96.10 286	98.64 202	98.65 236	96.04 211	99.36 359	96.84 200	99.14 283	99.20 227

Patchmatch-RL test		97.26 250	97.02 254	97.99 255	99.52 102	95.53 268	96.13 321	99.71 33	97.47 203	99.27 106	99.16 121	84.30 365	99.62 293	97.89 127	99.77 124	98.81 291

cdsmvs_eth3d_5k		24.66 378	32.88 381	0.00 396	0.00 419	0.00 421	0.00 407	99.10 228	0.00 414	0.00 415	97.58 325	99.21 16	0.00 415	0.00 414	0.00 413	0.00 411

pcd_1.5k_mvsjas		8.17 381	10.90 384	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.00 414	98.07 88	0.00 415	0.00 414	0.00 413	0.00 411

agg_prior2														92.50 355	99.16 280	99.37 182

agg_prior					98.68 285	97.99 147		99.01 248		95.59 364			99.77 216

tmp_tt		78.77 375	78.73 378	78.90 391	58.45 416	74.76 415	94.20 385	78.26 414	39.16 409	86.71 408	92.82 403	80.50 379	75.19 411	86.16 395	92.29 404	86.74 405

canonicalmvs		98.34 157	98.26 158	98.58 193	98.46 315	97.82 167	98.96 71	99.46 106	99.19 67	97.46 301	95.46 379	98.59 50	99.46 345	98.08 115	98.71 320	98.46 325

anonymousdsp		99.51 11	99.47 16	99.62 6	99.88 9	99.08 63	99.34 19	99.69 36	98.93 97	99.65 45	99.72 16	98.93 26	99.95 22	99.11 51	100.00 1	99.82 24

alignmvs		97.35 243	96.88 261	98.78 165	98.54 307	98.09 134	97.71 210	97.69 333	99.20 63	97.59 289	95.90 368	88.12 340	99.55 318	98.18 108	98.96 305	98.70 308

nrg030		99.40 21	99.35 23	99.54 26	99.58 76	99.13 55	98.98 70	99.48 96	99.68 11	99.46 70	99.26 99	98.62 47	99.73 240	99.17 50	99.92 54	99.76 38

v144192		98.54 133	98.57 111	98.45 214	99.21 173	95.98 254	97.63 221	99.36 140	97.15 242	99.32 101	99.18 115	95.84 226	99.84 135	99.50 32	99.91 61	99.54 107

FIs		99.14 46	99.09 55	99.29 83	99.70 53	98.28 116	99.13 54	99.52 83	99.48 31	99.24 115	99.41 75	96.79 178	99.82 162	98.69 80	99.88 72	99.76 38

v1921920		98.54 133	98.60 108	98.38 221	99.20 177	95.76 263	97.56 231	99.36 140	97.23 234	99.38 86	99.17 119	96.02 212	99.84 135	99.57 27	99.90 67	99.54 107

UA-Net		99.47 13	99.40 20	99.70 2	99.49 114	99.29 19	99.80 3	99.72 32	99.82 3	99.04 141	99.81 5	98.05 91	99.96 11	98.85 68	99.99 5	99.86 17

v1192		98.60 123	98.66 97	98.41 218	99.27 160	95.88 257	97.52 236	99.36 140	97.41 212	99.33 95	99.20 111	96.37 200	99.82 162	99.57 27	99.92 54	99.55 103

FC-MVSNet-test		99.27 30	99.25 38	99.34 72	99.77 27	98.37 110	99.30 31	99.57 61	99.61 22	99.40 82	99.50 58	97.12 157	99.85 118	99.02 59	99.94 39	99.80 28

v1144		98.60 123	98.66 97	98.41 218	99.36 146	95.90 256	97.58 228	99.34 151	97.51 199	99.27 106	99.15 125	96.34 202	99.80 184	99.47 34	99.93 43	99.51 119

sosnet-low-res		0.00 383	0.00 386	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.00 414	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

HFP-MVS		98.71 98	98.44 131	99.51 42	99.49 114	99.16 43	98.52 111	99.31 163	97.47 203	98.58 213	98.50 259	97.97 98	99.85 118	96.57 222	99.59 199	99.53 114

v148		98.45 145	98.60 108	98.00 254	99.44 128	94.98 287	97.44 245	99.06 233	98.30 133	99.32 101	98.97 171	96.65 187	99.62 293	98.37 97	99.85 79	99.39 173

sosnet		0.00 383	0.00 386	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.00 414	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

uncertanet		0.00 383	0.00 386	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.00 414	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

AllTest		98.44 146	98.20 164	99.16 104	99.50 107	98.55 96	98.25 141	99.58 54	96.80 257	98.88 172	99.06 139	97.65 117	99.57 312	94.45 305	99.61 193	99.37 182

TestCases				99.16 104	99.50 107	98.55 96		99.58 54	96.80 257	98.88 172	99.06 139	97.65 117	99.57 312	94.45 305	99.61 193	99.37 182

v7n		99.53 9	99.57 9	99.41 59	99.88 9	98.54 99	99.45 9	99.61 50	99.66 13	99.68 39	99.66 27	98.44 61	99.95 22	99.73 19	99.96 24	99.75 42

region2R		98.69 105	98.40 136	99.54 26	99.53 100	99.17 39	98.52 111	99.31 163	97.46 208	98.44 228	98.51 255	97.83 104	99.88 82	96.46 235	99.58 204	99.58 85

iter_conf05		98.46 143	98.38 141	98.70 177	99.27 160	97.15 213	97.51 238	99.51 84	97.57 191	98.95 155	98.89 193	95.48 240	99.82 162	98.30 102	99.96 24	99.14 242

mamv4		98.09 186	98.01 185	98.31 228	98.02 345	96.58 238	97.53 234	99.41 124	97.57 191	97.89 267	98.96 174	95.45 242	99.80 184	97.48 153	99.78 119	98.57 320

PS-MVSNAJss		99.46 14	99.49 12	99.35 69	99.90 4	98.15 127	99.20 44	99.65 45	99.48 31	99.92 8	99.71 17	98.07 88	99.96 11	99.53 30	100.00 1	99.93 8

PS-MVSNAJ		97.08 265	97.39 233	96.16 350	98.56 305	92.46 350	95.24 358	98.85 274	97.25 228	97.49 299	95.99 365	98.07 88	99.90 63	96.37 239	98.67 326	96.12 397

jajsoiax		99.58 6	99.61 8	99.48 50	99.87 12	98.61 91	99.28 36	99.66 44	99.09 82	99.89 15	99.68 20	99.53 7	99.97 4	99.50 32	99.99 5	99.87 15

mvs_tets		99.63 5	99.67 5	99.49 47	99.88 9	98.61 91	99.34 19	99.71 33	99.27 56	99.90 12	99.74 13	99.68 4	99.97 4	99.55 29	99.99 5	99.88 14

EI-MVSNet-UG-set		98.69 105	98.71 88	98.62 186	99.10 201	96.37 242	97.23 259	98.87 266	99.20 63	99.19 120	98.99 165	97.30 146	99.85 118	98.77 74	99.79 114	99.65 61

EI-MVSNet-Vis-set		98.68 110	98.70 91	98.63 185	99.09 204	96.40 241	97.23 259	98.86 271	99.20 63	99.18 124	98.97 171	97.29 148	99.85 118	98.72 77	99.78 119	99.64 62

HPM-MVS++		98.10 183	97.64 219	99.48 50	99.09 204	99.13 55	97.52 236	98.75 290	97.46 208	96.90 330	97.83 312	96.01 213	99.84 135	95.82 270	99.35 250	99.46 145

test_prior4						97.97 151	95.86 335

XVS		98.72 97	98.45 129	99.53 33	99.46 124	99.21 28	98.65 96	99.34 151	98.62 115	97.54 294	98.63 241	97.50 135	99.83 152	96.79 202	99.53 220	99.56 96

v1240		98.55 131	98.62 103	98.32 225	99.22 171	95.58 266	97.51 238	99.45 110	97.16 240	99.45 73	99.24 104	96.12 208	99.85 118	99.60 25	99.88 72	99.55 103

pm-mvs1		99.44 15	99.48 14	99.33 77	99.80 21	98.63 88	99.29 32	99.63 46	99.30 53	99.65 45	99.60 38	99.16 20	99.82 162	99.07 54	99.83 91	99.56 96

test_prior2							95.74 340		96.48 272	96.11 356	97.63 323	95.92 223		94.16 313	99.20 274

X-MVStestdata		94.32 335	92.59 353	99.53 33	99.46 124	99.21 28	98.65 96	99.34 151	98.62 115	97.54 294	45.85 409	97.50 135	99.83 152	96.79 202	99.53 220	99.56 96

test_prior				98.95 140	98.69 283	97.95 155		99.03 241					99.59 304			99.30 208

旧先验2							95.76 339		88.56 393	97.52 296			99.66 279	94.48 303

新几何2							95.93 332

新几何1				98.91 146	98.94 230	97.76 173		98.76 287	87.58 395	96.75 338	98.10 293	94.80 261	99.78 210	92.73 351	99.00 300	99.20 227

旧先验1					98.82 257	97.45 192		98.76 287			98.34 275	95.50 239			99.01 299	99.23 222

无先验							95.74 340	98.74 292	89.38 389				99.73 240	92.38 357		99.22 226

原ACMM2							95.53 346

原ACMM1				98.35 223	98.90 240	96.25 246		98.83 279	92.48 364	96.07 358	98.10 293	95.39 244	99.71 248	92.61 354	98.99 301	99.08 246

test222					98.92 236	96.93 225	95.54 345	98.78 285	85.72 398	96.86 333	98.11 292	94.43 268			99.10 290	99.23 222

testdata2													99.79 199	92.80 349

segment_acmp												97.02 164

testdata				98.09 244	98.93 232	95.40 274		98.80 282	90.08 386	97.45 303	98.37 271	95.26 246	99.70 252	93.58 332	98.95 306	99.17 238

testdata1							95.44 352		96.32 278

v8		99.01 59	99.16 45	98.57 196	99.47 123	96.31 245	98.90 77	99.47 104	99.03 88	99.52 61	99.57 41	96.93 168	99.81 177	99.60 25	99.98 12	99.60 73

1314		95.74 312	95.60 305	96.17 348	97.53 372	92.75 346	98.07 161	98.31 314	91.22 377	94.25 385	96.68 353	95.53 236	99.03 384	91.64 364	97.18 376	96.74 389

LFMVS		97.20 257	96.72 272	98.64 181	98.72 271	96.95 223	98.93 75	94.14 388	99.74 6	98.78 186	99.01 160	84.45 362	99.73 240	97.44 154	99.27 263	99.25 217

VDD-MVS		98.56 127	98.39 139	99.07 119	99.13 197	98.07 140	98.59 103	97.01 348	99.59 23	99.11 127	99.27 97	94.82 258	99.79 199	98.34 99	99.63 185	99.34 194

VDDNet		98.21 176	97.95 191	99.01 132	99.58 76	97.74 175	99.01 65	97.29 343	99.67 12	98.97 152	99.50 58	90.45 321	99.80 184	97.88 130	99.20 274	99.48 136

v10		98.97 65	99.11 52	98.55 201	99.44 128	96.21 247	98.90 77	99.55 72	98.73 107	99.48 67	99.60 38	96.63 188	99.83 152	99.70 22	99.99 5	99.61 72

VPNet		98.87 77	98.83 75	99.01 132	99.70 53	97.62 184	98.43 127	99.35 145	99.47 33	99.28 104	99.05 146	96.72 184	99.82 162	98.09 114	99.36 248	99.59 79

MVS		93.19 354	92.09 358	96.50 336	96.91 390	94.03 315	98.07 161	98.06 325	68.01 407	94.56 384	96.48 357	95.96 221	99.30 369	83.84 398	96.89 381	96.17 394

v2v482		98.56 127	98.62 103	98.37 222	99.42 134	95.81 261	97.58 228	99.16 218	97.90 166	99.28 104	99.01 160	95.98 219	99.79 199	99.33 38	99.90 67	99.51 119

V42		98.78 89	98.78 80	98.76 169	99.44 128	97.04 217	98.27 139	99.19 207	97.87 168	99.25 114	99.16 121	96.84 172	99.78 210	99.21 47	99.84 83	99.46 145

SD-MVS		98.40 150	98.68 94	97.54 290	98.96 228	97.99 147	97.88 188	99.36 140	98.20 146	99.63 48	99.04 148	98.76 35	95.33 408	96.56 226	99.74 139	99.31 205
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		95.86 309	95.32 318	97.49 295	98.60 297	94.15 311	93.83 391	97.93 327	95.49 307	96.68 339	97.42 336	83.21 370	99.30 369	96.22 248	98.55 333	99.01 258

MSLP-MVS++		98.02 191	98.14 174	97.64 281	98.58 302	95.19 281	97.48 241	99.23 199	97.47 203	97.90 266	98.62 243	97.04 161	98.81 394	97.55 146	99.41 242	98.94 273

APDe-MVS		98.99 61	98.79 79	99.60 11	99.21 173	99.15 47	98.87 79	99.48 96	97.57 191	99.35 92	99.24 104	97.83 104	99.89 73	97.88 130	99.70 160	99.75 42
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
APD-MVS_3200maxsize		98.84 81	98.61 107	99.53 33	99.19 180	99.27 22	98.49 119	99.33 156	98.64 111	99.03 144	98.98 169	97.89 101	99.85 118	96.54 230	99.42 241	99.46 145

ADS-MVSNet2		95.43 321	94.98 325	96.76 332	98.14 339	91.74 360	97.92 182	97.76 330	90.23 382	96.51 347	98.91 184	85.61 353	99.85 118	92.88 345	96.90 379	98.69 309

EI-MVSNet		98.40 150	98.51 117	98.04 252	99.10 201	94.73 294	97.20 263	98.87 266	98.97 93	99.06 134	99.02 151	96.00 214	99.80 184	98.58 85	99.82 94	99.60 73

Regformer		0.00 383	0.00 386	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.00 414	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

CVMVSNet		96.25 299	97.21 244	93.38 385	99.10 201	80.56 412	97.20 263	98.19 320	96.94 250	99.00 146	99.02 151	89.50 328	99.80 184	96.36 241	99.59 199	99.78 32

pmmvs4		97.58 229	97.28 240	98.51 207	98.84 252	96.93 225	95.40 354	98.52 305	93.60 349	98.61 207	98.65 236	95.10 250	99.60 300	96.97 186	99.79 114	98.99 262

EU-MVSNet		97.66 223	98.50 119	95.13 367	99.63 73	85.84 397	98.35 135	98.21 317	98.23 140	99.54 55	99.46 65	95.02 252	99.68 265	98.24 104	99.87 75	99.87 15

VNet		98.42 147	98.30 152	98.79 162	98.79 264	97.29 200	98.23 142	98.66 296	99.31 51	98.85 177	98.80 210	94.80 261	99.78 210	98.13 111	99.13 285	99.31 205

test-LLR		93.90 344	93.85 338	94.04 376	96.53 397	84.62 403	94.05 388	92.39 395	96.17 282	94.12 387	95.07 383	82.30 375	99.67 268	95.87 266	98.18 343	97.82 363

TESTMET0.1,1		92.19 368	91.77 366	93.46 383	96.48 399	82.80 408	94.05 388	91.52 399	94.45 334	94.00 390	94.88 389	66.65 403	99.56 315	95.78 271	98.11 349	98.02 355

test-mter		92.33 366	91.76 367	94.04 376	96.53 397	84.62 403	94.05 388	92.39 395	94.00 345	94.12 387	95.07 383	65.63 407	99.67 268	95.87 266	98.18 343	97.82 363

VPA-MVSNet		99.30 28	99.30 32	99.28 84	99.49 114	98.36 113	99.00 67	99.45 110	99.63 17	99.52 61	99.44 70	98.25 71	99.88 82	99.09 53	99.84 83	99.62 66

ACMMPR		98.70 102	98.42 134	99.54 26	99.52 102	99.14 52	98.52 111	99.31 163	97.47 203	98.56 216	98.54 251	97.75 111	99.88 82	96.57 222	99.59 199	99.58 85

testgi		98.32 161	98.39 139	98.13 243	99.57 80	95.54 267	97.78 200	99.49 94	97.37 216	99.19 120	97.65 321	98.96 24	99.49 337	96.50 233	98.99 301	99.34 194

test20.03		98.78 89	98.77 81	98.78 165	99.46 124	97.20 208	97.78 200	99.24 197	99.04 87	99.41 79	98.90 187	97.65 117	99.76 222	97.70 142	99.79 114	99.39 173

thres600view7		94.45 333	93.83 339	96.29 341	99.06 212	91.53 362	97.99 175	94.24 386	98.34 129	97.44 304	95.01 385	79.84 381	99.67 268	84.33 397	98.23 340	97.66 373

ADS-MVSNet		95.24 324	94.93 328	96.18 347	98.14 339	90.10 382	97.92 182	97.32 342	90.23 382	96.51 347	98.91 184	85.61 353	99.74 235	92.88 345	96.90 379	98.69 309

MP-MVS		98.46 143	98.09 177	99.54 26	99.57 80	99.22 27	98.50 118	99.19 207	97.61 188	97.58 290	98.66 234	97.40 142	99.88 82	94.72 298	99.60 195	99.54 107
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		17.12 379	20.53 382	6.87 395	12.05 417	4.20 420	93.62 394	6.73 418	4.62 413	10.41 413	24.33 410	8.28 418	3.56 414	9.69 413	15.07 411	12.86 410

thres400		94.14 340	93.44 344	96.24 344	98.93 232	91.44 364	97.60 225	94.29 384	97.94 162	97.10 316	94.31 394	79.67 383	99.62 293	83.05 399	98.08 351	97.66 373

test123		17.04 380	20.11 383	7.82 394	10.25 418	4.91 419	94.80 369	4.47 419	4.93 412	10.00 414	24.28 411	9.69 417	3.64 413	10.14 412	12.43 412	14.92 409

thres200		93.72 347	93.14 349	95.46 364	98.66 291	91.29 368	96.61 294	94.63 381	97.39 214	96.83 334	93.71 397	79.88 380	99.56 315	82.40 402	98.13 348	95.54 401

test0.0.03 1		94.51 332	93.69 341	96.99 318	96.05 403	93.61 333	94.97 366	93.49 390	96.17 282	97.57 292	94.88 389	82.30 375	99.01 387	93.60 331	94.17 401	98.37 339

pmmvs3		95.03 327	94.40 333	96.93 321	97.70 363	92.53 349	95.08 362	97.71 332	88.57 392	97.71 281	98.08 296	79.39 385	99.82 162	96.19 250	99.11 289	98.43 332

EMVS		93.83 345	94.02 337	93.23 386	96.83 393	84.96 400	89.77 405	96.32 364	97.92 164	97.43 305	96.36 362	86.17 348	98.93 390	87.68 389	97.73 359	95.81 399

E-PMN		94.17 339	94.37 334	93.58 382	96.86 391	85.71 399	90.11 404	97.07 347	98.17 149	97.82 276	97.19 343	84.62 361	98.94 389	89.77 382	97.68 360	96.09 398

PGM-MVS		98.66 114	98.37 143	99.55 23	99.53 100	99.18 38	98.23 142	99.49 94	97.01 247	98.69 196	98.88 195	98.00 94	99.89 73	95.87 266	99.59 199	99.58 85

LCM-MVSNet-Re		98.64 117	98.48 124	99.11 111	98.85 251	98.51 101	98.49 119	99.83 20	98.37 127	99.69 37	99.46 65	98.21 78	99.92 49	94.13 317	99.30 259	98.91 278

LCM-MVSNet		99.93 1	99.92 1	99.94 1	99.99 1	99.97 1	99.90 1	99.89 10	99.98 1	99.99 1	99.96 1	99.77 2	100.00 1	99.81 11	100.00 1	99.85 18

MCST-MVS		98.00 194	97.63 220	99.10 113	99.24 166	98.17 126	96.89 280	98.73 293	95.66 300	97.92 264	97.70 319	97.17 155	99.66 279	96.18 252	99.23 270	99.47 143

mvs_anonymous		97.83 214	98.16 171	96.87 325	98.18 337	91.89 359	97.31 253	98.90 261	97.37 216	98.83 180	99.46 65	96.28 203	99.79 199	98.90 65	98.16 346	98.95 269

MVS_Test		98.18 179	98.36 144	97.67 277	98.48 312	94.73 294	98.18 147	99.02 245	97.69 180	98.04 259	99.11 132	97.22 153	99.56 315	98.57 87	98.90 310	98.71 305

MDA-MVSNet-bldmvs		97.94 198	97.91 196	98.06 249	99.44 128	94.96 288	96.63 293	99.15 223	98.35 128	98.83 180	99.11 132	94.31 273	99.85 118	96.60 219	98.72 318	99.37 182

CDPH-MVS		97.26 250	96.66 278	99.07 119	99.00 221	98.15 127	96.03 325	99.01 248	91.21 378	97.79 277	97.85 311	96.89 170	99.69 256	92.75 350	99.38 247	99.39 173

test12				98.93 143	98.58 302	97.83 164		98.66 296		96.53 345		95.51 238	99.69 256		99.13 285	99.27 213

casdiffmvs		98.95 68	99.00 62	98.81 157	99.38 139	97.33 198	97.82 195	99.57 61	99.17 70	99.35 92	99.17 119	98.35 68	99.69 256	98.46 93	99.73 143	99.41 163
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		98.22 174	98.24 161	98.17 240	99.00 221	95.44 272	96.38 305	99.58 54	97.79 174	98.53 221	98.50 259	96.76 181	99.74 235	97.95 126	99.64 182	99.34 194
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		93.73 346	92.83 352	96.42 338	97.70 363	91.28 369	96.84 282	89.77 404	93.96 346	92.44 399	95.93 367	79.14 386	99.77 216	92.94 343	96.76 383	98.21 345

baseline1		95.96 307	95.44 312	97.52 292	98.51 311	93.99 318	98.39 131	96.09 367	98.21 142	98.40 235	97.76 315	86.88 342	99.63 290	95.42 283	89.27 406	98.95 269

YYNet1		97.60 226	97.67 214	97.39 302	99.04 216	93.04 341	95.27 356	98.38 312	97.25 228	98.92 165	98.95 179	95.48 240	99.73 240	96.99 183	98.74 316	99.41 163

PMMVS2		98.07 189	98.08 180	98.04 252	99.41 136	94.59 300	94.59 378	99.40 127	97.50 200	98.82 183	98.83 204	96.83 174	99.84 135	97.50 152	99.81 99	99.71 45

MDA-MVSNet_test_wron		97.60 226	97.66 217	97.41 301	99.04 216	93.09 337	95.27 356	98.42 309	97.26 227	98.88 172	98.95 179	95.43 243	99.73 240	97.02 180	98.72 318	99.41 163

tpmvs		95.02 328	95.25 319	94.33 373	96.39 401	85.87 396	98.08 159	96.83 356	95.46 308	95.51 372	98.69 227	85.91 351	99.53 325	94.16 313	96.23 388	97.58 376

PM-MVS		98.82 83	98.72 86	99.12 109	99.64 69	98.54 99	97.98 176	99.68 41	97.62 185	99.34 94	99.18 115	97.54 129	99.77 216	97.79 135	99.74 139	99.04 254

HQP_MVS		97.99 197	97.67 214	98.93 143	99.19 180	97.65 181	97.77 202	99.27 186	98.20 146	97.79 277	97.98 302	94.90 254	99.70 252	94.42 307	99.51 225	99.45 149

plane_prior7					99.19 180	97.87 160

plane_prior6					98.99 224	97.70 179						94.90 254

plane_prior5								99.27 186					99.70 252	94.42 307	99.51 225	99.45 149

plane_prior4											97.98 302

plane_prior3						97.78 172			97.41 212	97.79 277

plane_prior2							97.77 202		98.20 146

plane_prior1					99.05 215

plane_prior						97.65 181	97.07 269		96.72 262						99.36 248

PS-CasMVS		99.40 21	99.33 26	99.62 6	99.71 46	99.10 60	99.29 32	99.53 80	99.53 29	99.46 70	99.41 75	98.23 73	99.95 22	98.89 67	99.95 31	99.81 27

UniMVSNet_NR-MVSNet		98.86 80	98.68 94	99.40 61	99.17 188	98.74 81	97.68 213	99.40 127	99.14 71	99.06 134	98.59 247	96.71 185	99.93 39	98.57 87	99.77 124	99.53 114

PEN-MVS		99.41 20	99.34 25	99.62 6	99.73 37	99.14 52	99.29 32	99.54 77	99.62 20	99.56 52	99.42 72	98.16 84	99.96 11	98.78 71	99.93 43	99.77 34

TransMVSNet (Re)		99.44 15	99.47 16	99.36 63	99.80 21	98.58 94	99.27 38	99.57 61	99.39 42	99.75 30	99.62 33	99.17 18	99.83 152	99.06 55	99.62 188	99.66 57

DTE-MVSNet		99.43 18	99.35 23	99.66 4	99.71 46	99.30 17	99.31 26	99.51 84	99.64 15	99.56 52	99.46 65	98.23 73	99.97 4	98.78 71	99.93 43	99.72 44

DU-MVS		98.82 83	98.63 101	99.39 62	99.16 190	98.74 81	97.54 233	99.25 192	98.84 105	99.06 134	98.76 217	96.76 181	99.93 39	98.57 87	99.77 124	99.50 122

UniMVSNet (Re)		98.87 77	98.71 88	99.35 69	99.24 166	98.73 84	97.73 209	99.38 131	98.93 97	99.12 126	98.73 220	96.77 179	99.86 106	98.63 84	99.80 109	99.46 145

CP-MVSNet		99.21 39	99.09 55	99.56 21	99.65 64	98.96 70	99.13 54	99.34 151	99.42 40	99.33 95	99.26 99	97.01 165	99.94 34	98.74 75	99.93 43	99.79 29

WR-MVS_H		99.33 26	99.22 40	99.65 5	99.71 46	99.24 25	99.32 22	99.55 72	99.46 34	99.50 66	99.34 86	97.30 146	99.93 39	98.90 65	99.93 43	99.77 34

WR-MVS		98.40 150	98.19 166	99.03 129	99.00 221	97.65 181	96.85 281	98.94 253	98.57 120	98.89 169	98.50 259	95.60 233	99.85 118	97.54 148	99.85 79	99.59 79

NR-MVSNet		98.95 68	98.82 76	99.36 63	99.16 190	98.72 86	99.22 41	99.20 203	99.10 79	99.72 31	98.76 217	96.38 199	99.86 106	98.00 122	99.82 94	99.50 122

Baseline_NR-MVSNet		98.98 64	98.86 73	99.36 63	99.82 20	98.55 96	97.47 243	99.57 61	99.37 44	99.21 118	99.61 36	96.76 181	99.83 152	98.06 117	99.83 91	99.71 45

TranMVSNet+NR-MVSNet		99.17 42	99.07 58	99.46 55	99.37 145	98.87 73	98.39 131	99.42 123	99.42 40	99.36 90	99.06 139	98.38 64	99.95 22	98.34 99	99.90 67	99.57 90

TSAR-MVS + GP.		98.18 179	97.98 189	98.77 168	98.71 274	97.88 159	96.32 309	98.66 296	96.33 277	99.23 117	98.51 255	97.48 139	99.40 354	97.16 168	99.46 235	99.02 257

n2								0.00 420

nn								0.00 420

mPP-MVS		98.64 117	98.34 147	99.54 26	99.54 97	99.17 39	98.63 98	99.24 197	97.47 203	98.09 254	98.68 229	97.62 122	99.89 73	96.22 248	99.62 188	99.57 90

door-mid								99.57 61

XVG-OURS-SEG-HR		98.49 140	98.28 154	99.14 107	99.49 114	98.83 76	96.54 295	99.48 96	97.32 221	99.11 127	98.61 245	99.33 13	99.30 369	96.23 247	98.38 335	99.28 212

mvsmamba		99.24 37	99.15 50	99.49 47	99.83 18	98.85 74	99.41 12	99.55 72	99.54 27	99.40 82	99.52 56	95.86 225	99.91 58	99.32 39	99.95 31	99.70 50

MVSFormer		98.26 170	98.43 132	97.77 266	98.88 246	93.89 324	99.39 16	99.56 68	99.11 72	98.16 246	98.13 289	93.81 284	99.97 4	99.26 42	99.57 208	99.43 157

jason		97.45 237	97.35 237	97.76 269	99.24 166	93.93 320	95.86 335	98.42 309	94.24 338	98.50 223	98.13 289	94.82 258	99.91 58	97.22 165	99.73 143	99.43 157
jason: jason.
lupinMVS		97.06 266	96.86 262	97.65 279	98.88 246	93.89 324	95.48 350	97.97 326	93.53 350	98.16 246	97.58 325	93.81 284	99.91 58	96.77 205	99.57 208	99.17 238

test_djsdf		99.52 10	99.51 11	99.53 33	99.86 14	98.74 81	99.39 16	99.56 68	99.11 72	99.70 35	99.73 15	99.00 22	99.97 4	99.26 42	99.98 12	99.89 11

HPM-MVS_fast		99.01 59	98.82 76	99.57 16	99.71 46	99.35 12	99.00 67	99.50 87	97.33 219	98.94 163	98.86 198	98.75 36	99.82 162	97.53 149	99.71 155	99.56 96

K. test v3		98.00 194	97.66 217	99.03 129	99.79 23	97.56 186	99.19 48	92.47 394	99.62 20	99.52 61	99.66 27	89.61 326	99.96 11	99.25 44	99.81 99	99.56 96

lessismore_v0				98.97 137	99.73 37	97.53 188		86.71 408		99.37 88	99.52 56	89.93 324	99.92 49	98.99 61	99.72 150	99.44 153

SixPastTwentyTwo		98.75 94	98.62 103	99.16 104	99.83 18	97.96 154	99.28 36	98.20 318	99.37 44	99.70 35	99.65 30	92.65 303	99.93 39	99.04 57	99.84 83	99.60 73

OurMVSNet-221017-0		99.37 24	99.31 30	99.53 33	99.91 3	98.98 65	99.63 6	99.58 54	99.44 37	99.78 26	99.76 10	96.39 197	99.92 49	99.44 35	99.92 54	99.68 53

HPM-MVS		98.79 87	98.53 115	99.59 15	99.65 64	99.29 19	99.16 50	99.43 120	96.74 261	98.61 207	98.38 270	98.62 47	99.87 99	96.47 234	99.67 174	99.59 79
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
XVG-OURS		98.53 135	98.34 147	99.11 111	99.50 107	98.82 78	95.97 327	99.50 87	97.30 223	99.05 139	98.98 169	99.35 12	99.32 366	95.72 273	99.68 168	99.18 234

XVG-ACMP-BASELINE		98.56 127	98.34 147	99.22 97	99.54 97	98.59 93	97.71 210	99.46 106	97.25 228	98.98 148	98.99 165	97.54 129	99.84 135	95.88 263	99.74 139	99.23 222

casdiffmvs_mvg		99.12 51	99.16 45	98.99 134	99.43 133	97.73 177	98.00 173	99.62 47	99.22 59	99.55 54	99.22 108	98.93 26	99.75 230	98.66 81	99.81 99	99.50 122
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 98	98.46 128	99.47 53	99.57 80	98.97 66	98.23 142	99.48 96	96.60 266	99.10 130	99.06 139	98.71 39	99.83 152	95.58 280	99.78 119	99.62 66

LGP-MVS_train				99.47 53	99.57 80	98.97 66		99.48 96	96.60 266	99.10 130	99.06 139	98.71 39	99.83 152	95.58 280	99.78 119	99.62 66

baseline		98.96 67	99.02 60	98.76 169	99.38 139	97.26 203	98.49 119	99.50 87	98.86 102	99.19 120	99.06 139	98.23 73	99.69 256	98.71 78	99.76 135	99.33 199

test11								98.87 266

door								99.41 124

EPNet_dtu		94.93 329	94.78 330	95.38 365	93.58 409	87.68 392	96.78 284	95.69 375	97.35 218	89.14 406	98.09 295	88.15 339	99.49 337	94.95 292	99.30 259	98.98 263
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x2688		97.49 233	97.14 249	98.54 204	99.68 57	96.09 251	96.50 298	99.62 47	91.58 372	98.84 179	98.97 171	92.36 305	99.88 82	96.76 206	99.95 31	99.67 56

EPNet		96.14 301	95.44 312	98.25 234	90.76 413	95.50 270	97.92 182	94.65 380	98.97 93	92.98 396	98.85 201	89.12 330	99.87 99	95.99 259	99.68 168	99.39 173
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS						96.79 228

HQP-NCC					98.67 286		96.29 311		96.05 288	95.55 367

ACMP_Plane					98.67 286		96.29 311		96.05 288	95.55 367

APD-MVS		98.10 183	97.67 214	99.42 57	99.11 199	98.93 71	97.76 205	99.28 183	94.97 321	98.72 195	98.77 215	97.04 161	99.85 118	93.79 327	99.54 216	99.49 126
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS														92.82 347

HQP4-MVS										95.56 366			99.54 323			99.32 201

HQP3-MVS								99.04 239							99.26 266

HQP2-MVS												93.84 282

CNVR-MVS		98.17 181	97.87 201	99.07 119	98.67 286	98.24 119	97.01 271	98.93 255	97.25 228	97.62 286	98.34 275	97.27 149	99.57 312	96.42 237	99.33 253	99.39 173

NCCC		97.86 205	97.47 231	99.05 126	98.61 295	98.07 140	96.98 273	98.90 261	97.63 184	97.04 320	97.93 307	95.99 218	99.66 279	95.31 285	98.82 314	99.43 157

114514_t		96.50 291	95.77 298	98.69 178	99.48 121	97.43 194	97.84 194	99.55 72	81.42 404	96.51 347	98.58 248	95.53 236	99.67 268	93.41 337	99.58 204	98.98 263

CP-MVS		98.70 102	98.42 134	99.52 38	99.36 146	99.12 57	98.72 90	99.36 140	97.54 198	98.30 238	98.40 267	97.86 103	99.89 73	96.53 231	99.72 150	99.56 96

DSMNet-mixed		97.42 239	97.60 222	96.87 325	99.15 194	91.46 363	98.54 109	99.12 225	92.87 360	97.58 290	99.63 32	96.21 205	99.90 63	95.74 272	99.54 216	99.27 213

tpm2		93.09 355	92.58 354	94.62 371	97.56 368	86.53 395	97.66 217	95.79 372	86.15 397	94.07 389	98.23 284	75.95 393	99.53 325	90.91 377	96.86 382	97.81 365

NP-MVS					98.84 252	97.39 196					96.84 350

EG-PatchMatch MVS		98.99 61	99.01 61	98.94 141	99.50 107	97.47 190	98.04 166	99.59 52	98.15 153	99.40 82	99.36 81	98.58 53	99.76 222	98.78 71	99.68 168	99.59 79

tpm cat1		93.29 353	93.13 350	93.75 380	97.39 380	84.74 401	97.39 246	97.65 334	83.39 402	94.16 386	98.41 266	82.86 373	99.39 356	91.56 366	95.35 396	97.14 384

SteuartSystems-ACMMP		98.79 87	98.54 114	99.54 26	99.73 37	99.16 43	98.23 142	99.31 163	97.92 164	98.90 167	98.90 187	98.00 94	99.88 82	96.15 253	99.72 150	99.58 85
Skip Steuart: Steuart Systems R&D Blog.
CostFormer		93.97 343	93.78 340	94.51 372	97.53 372	85.83 398	97.98 176	95.96 369	89.29 390	94.99 378	98.63 241	78.63 389	99.62 293	94.54 301	96.50 384	98.09 352

CR-MVSNet		96.28 298	95.95 296	97.28 305	97.71 361	94.22 306	98.11 155	98.92 258	92.31 366	96.91 327	99.37 78	85.44 356	99.81 177	97.39 157	97.36 372	97.81 365

JIA-IIPM		95.52 319	95.03 324	97.00 317	96.85 392	94.03 315	96.93 277	95.82 371	99.20 63	94.63 383	99.71 17	83.09 371	99.60 300	94.42 307	94.64 398	97.36 382

Patchmtry		97.35 243	96.97 255	98.50 210	97.31 382	96.47 240	98.18 147	98.92 258	98.95 96	98.78 186	99.37 78	85.44 356	99.85 118	95.96 261	99.83 91	99.17 238

PatchT		96.65 285	96.35 288	97.54 290	97.40 379	95.32 276	97.98 176	96.64 359	99.33 49	96.89 331	99.42 72	84.32 364	99.81 177	97.69 144	97.49 363	97.48 378

tpmrst		95.07 326	95.46 310	93.91 378	97.11 386	84.36 405	97.62 222	96.96 351	94.98 320	96.35 352	98.80 210	85.46 355	99.59 304	95.60 278	96.23 388	97.79 368

BH-w/o		95.13 325	94.89 329	95.86 352	98.20 336	91.31 367	95.65 342	97.37 338	93.64 348	96.52 346	95.70 372	93.04 296	99.02 385	88.10 388	95.82 393	97.24 383

tpm		94.67 331	94.34 335	95.66 358	97.68 366	88.42 387	97.88 188	94.90 378	94.46 332	96.03 360	98.56 250	78.66 388	99.79 199	95.88 263	95.01 397	98.78 298

DELS-MVS		98.27 168	98.20 164	98.48 211	98.86 248	96.70 233	95.60 344	99.20 203	97.73 178	98.45 227	98.71 223	97.50 135	99.82 162	98.21 106	99.59 199	98.93 274
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		96.83 278	96.75 271	97.08 314	98.74 268	93.33 335	96.71 289	98.26 315	96.72 262	98.44 228	97.37 339	95.20 247	99.47 343	91.89 359	97.43 367	98.44 330

RPMNet		97.02 269	96.93 256	97.30 304	97.71 361	94.22 306	98.11 155	99.30 172	99.37 44	96.91 327	99.34 86	86.72 343	99.87 99	97.53 149	97.36 372	97.81 365

MVSTER		96.86 277	96.55 284	97.79 264	97.91 352	94.21 308	97.56 231	98.87 266	97.49 202	99.06 134	99.05 146	80.72 378	99.80 184	98.44 94	99.82 94	99.37 182

CPTT-MVS		97.84 212	97.36 236	99.27 87	99.31 153	98.46 104	98.29 137	99.27 186	94.90 323	97.83 274	98.37 271	94.90 254	99.84 135	93.85 326	99.54 216	99.51 119

GBi-Net		98.65 115	98.47 126	99.17 101	98.90 240	98.24 119	99.20 44	99.44 114	98.59 117	98.95 155	99.55 47	94.14 276	99.86 106	97.77 136	99.69 163	99.41 163

PVSNet_Blended_VisFu		98.17 181	98.15 172	98.22 237	99.73 37	95.15 282	97.36 249	99.68 41	94.45 334	98.99 147	99.27 97	96.87 171	99.94 34	97.13 173	99.91 61	99.57 90

PVSNet_BlendedMVS		97.55 230	97.53 225	97.60 283	98.92 236	93.77 328	96.64 292	99.43 120	94.49 330	97.62 286	99.18 115	96.82 175	99.67 268	94.73 296	99.93 43	99.36 188

UnsupCasMVSNet_eth		97.89 201	97.60 222	98.75 172	99.31 153	97.17 211	97.62 222	99.35 145	98.72 109	98.76 191	98.68 229	92.57 304	99.74 235	97.76 140	95.60 394	99.34 194

UnsupCasMVSNet_bld		97.30 247	96.92 258	98.45 214	99.28 158	96.78 231	96.20 316	99.27 186	95.42 309	98.28 240	98.30 279	93.16 291	99.71 248	94.99 290	97.37 370	98.87 283

PVSNet_Blended		96.88 276	96.68 275	97.47 297	98.92 236	93.77 328	94.71 371	99.43 120	90.98 380	97.62 286	97.36 340	96.82 175	99.67 268	94.73 296	99.56 211	98.98 263

FMVSNet5		96.01 304	95.20 321	98.41 218	97.53 372	96.10 248	98.74 86	99.50 87	97.22 237	98.03 260	99.04 148	69.80 398	99.88 82	97.27 162	99.71 155	99.25 217

test1		98.65 115	98.47 126	99.17 101	98.90 240	98.24 119	99.20 44	99.44 114	98.59 117	98.95 155	99.55 47	94.14 276	99.86 106	97.77 136	99.69 163	99.41 163

new_pmnet		96.99 273	96.76 270	97.67 277	98.72 271	94.89 289	95.95 331	98.20 318	92.62 363	98.55 218	98.54 251	94.88 257	99.52 329	93.96 321	99.44 240	98.59 319

FMVSNet3		97.50 231	97.24 242	98.29 231	98.08 343	95.83 260	97.86 192	98.91 260	97.89 167	98.95 155	98.95 179	87.06 341	99.81 177	97.77 136	99.69 163	99.23 222

dp		93.47 350	93.59 343	93.13 387	96.64 396	81.62 411	97.66 217	96.42 363	92.80 361	96.11 356	98.64 239	78.55 391	99.59 304	93.31 338	92.18 405	98.16 348

FMVSNet2		98.49 140	98.40 136	98.75 172	98.90 240	97.14 215	98.61 101	99.13 224	98.59 117	99.19 120	99.28 95	94.14 276	99.82 162	97.97 124	99.80 109	99.29 210

FMVSNet1		99.17 42	99.17 43	99.17 101	99.55 92	98.24 119	99.20 44	99.44 114	99.21 61	99.43 75	99.55 47	97.82 107	99.86 106	98.42 96	99.89 71	99.41 163

N_pmnet		97.63 225	97.17 245	98.99 134	99.27 160	97.86 161	95.98 326	93.41 391	95.25 315	99.47 69	98.90 187	95.63 232	99.85 118	96.91 189	99.73 143	99.27 213

cascas		94.79 330	94.33 336	96.15 351	96.02 405	92.36 354	92.34 400	99.26 191	85.34 399	95.08 377	94.96 388	92.96 297	98.53 397	94.41 310	98.59 331	97.56 377

BH-RMVSNet		96.83 278	96.58 283	97.58 285	98.47 313	94.05 312	96.67 291	97.36 339	96.70 264	97.87 269	97.98 302	95.14 249	99.44 349	90.47 380	98.58 332	99.25 217

UGNet		98.53 135	98.45 129	98.79 162	97.94 350	96.96 222	99.08 57	98.54 303	99.10 79	96.82 335	99.47 64	96.55 191	99.84 135	98.56 90	99.94 39	99.55 103
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		96.67 284	96.27 293	97.87 259	98.81 260	94.61 299	96.77 285	97.92 328	94.94 322	97.12 315	97.74 316	91.11 317	99.82 162	93.89 323	98.15 347	99.18 234

XXY-MVS		99.14 46	99.15 50	99.10 113	99.76 30	97.74 175	98.85 82	99.62 47	98.48 125	99.37 88	99.49 62	98.75 36	99.86 106	98.20 107	99.80 109	99.71 45

EC-MVSNet		99.09 54	99.05 59	99.20 98	99.28 158	98.93 71	99.24 40	99.84 18	99.08 84	98.12 251	98.37 271	98.72 38	99.90 63	99.05 56	99.77 124	98.77 299

sss		97.21 256	96.93 256	98.06 249	98.83 254	95.22 280	96.75 287	98.48 307	94.49 330	97.27 312	97.90 308	92.77 301	99.80 184	96.57 222	99.32 254	99.16 241

Test_1112_low_res		96.99 273	96.55 284	98.31 228	99.35 150	95.47 271	95.84 338	99.53 80	91.51 374	96.80 336	98.48 262	91.36 315	99.83 152	96.58 220	99.53 220	99.62 66

1112_ss		97.29 249	96.86 262	98.58 193	99.34 152	96.32 244	96.75 287	99.58 54	93.14 355	96.89 331	97.48 332	92.11 309	99.86 106	96.91 189	99.54 216	99.57 90

ab-mvs-re		8.12 382	10.83 385	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	97.48 332	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

ab-mvs		98.41 148	98.36 144	98.59 192	99.19 180	97.23 204	99.32 22	98.81 280	97.66 182	98.62 205	99.40 77	96.82 175	99.80 184	95.88 263	99.51 225	98.75 302

TR-MVS		95.55 318	95.12 323	96.86 328	97.54 370	93.94 319	96.49 299	96.53 362	94.36 337	97.03 322	96.61 354	94.26 275	99.16 381	86.91 393	96.31 387	97.47 379

MDTV_nov1_ep13_2view						74.92 414	97.69 212		90.06 387	97.75 280		85.78 352		93.52 333		98.69 309

MDTV_nov1_ep13			95.22 320		97.06 389	83.20 407	97.74 207	96.16 365	94.37 336	96.99 323	98.83 204	83.95 367	99.53 325	93.90 322	97.95 357

MIMVSNet1		99.38 23	99.32 28	99.55 23	99.86 14	99.19 37	99.41 12	99.59 52	99.59 23	99.71 33	99.57 41	97.12 157	99.90 63	99.21 47	99.87 75	99.54 107

MIMVSNet		96.62 287	96.25 294	97.71 275	99.04 216	94.66 297	99.16 50	96.92 354	97.23 234	97.87 269	99.10 135	86.11 350	99.65 284	91.65 363	99.21 273	98.82 287

IterMVS-LS		98.55 131	98.70 91	98.09 244	99.48 121	94.73 294	97.22 262	99.39 129	98.97 93	99.38 86	99.31 92	96.00 214	99.93 39	98.58 85	99.97 19	99.60 73
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet		97.69 220	97.35 237	98.69 178	98.73 269	97.02 219	96.92 279	98.75 290	95.89 296	98.59 211	98.67 231	92.08 310	99.74 235	96.72 211	99.81 99	99.32 201
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref															99.77 124

IterMVS		97.73 217	98.11 176	96.57 334	99.24 166	90.28 381	95.52 349	99.21 201	98.86 102	99.33 95	99.33 88	93.11 292	99.94 34	98.49 92	99.94 39	99.48 136
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon		97.33 245	96.92 258	98.57 196	99.09 204	97.99 147	96.79 283	99.35 145	93.18 354	97.71 281	98.07 297	95.00 253	99.31 367	93.97 320	99.13 285	98.42 334

MVS_111021_LR		98.30 164	98.12 175	98.83 154	99.16 190	98.03 145	96.09 323	99.30 172	97.58 190	98.10 253	98.24 282	98.25 71	99.34 363	96.69 214	99.65 180	99.12 244

DP-MVS		98.93 70	98.81 78	99.28 84	99.21 173	98.45 105	98.46 124	99.33 156	99.63 17	99.48 67	99.15 125	97.23 152	99.75 230	97.17 167	99.66 179	99.63 65

ACMMP++															99.68 168

HQP-MVS		97.00 272	96.49 286	98.55 201	98.67 286	96.79 228	96.29 311	99.04 239	96.05 288	95.55 367	96.84 350	93.84 282	99.54 323	92.82 347	99.26 266	99.32 201

QAPM		97.31 246	96.81 268	98.82 155	98.80 263	97.49 189	99.06 61	99.19 207	90.22 384	97.69 283	99.16 121	96.91 169	99.90 63	90.89 378	99.41 242	99.07 248

Vis-MVSNet		99.34 25	99.36 22	99.27 87	99.73 37	98.26 117	99.17 49	99.78 26	99.11 72	99.27 106	99.48 63	98.82 31	99.95 22	98.94 63	99.93 43	99.59 79
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet		94.32 335	95.62 304	90.42 389	98.46 315	75.36 413	96.29 311	89.13 405	95.25 315	95.38 373	99.75 11	92.88 298	99.19 379	94.07 319	99.39 244	96.72 390

IS-MVSNet		98.19 178	97.90 197	99.08 117	99.57 80	97.97 151	99.31 26	98.32 313	99.01 90	98.98 148	99.03 150	91.59 313	99.79 199	95.49 282	99.80 109	99.48 136

HyFIR lowres test		97.19 258	96.60 282	98.96 138	99.62 75	97.28 201	95.17 359	99.50 87	94.21 339	99.01 145	98.32 278	86.61 344	99.99 2	97.10 175	99.84 83	99.60 73

EPMVS		93.72 347	93.27 346	95.09 369	96.04 404	87.76 391	98.13 152	85.01 410	94.69 327	96.92 325	98.64 239	78.47 392	99.31 367	95.04 289	96.46 385	98.20 346

PAPM_NR		96.82 280	96.32 290	98.30 230	99.07 208	96.69 234	97.48 241	98.76 287	95.81 298	96.61 343	96.47 358	94.12 279	99.17 380	90.82 379	97.78 358	99.06 249

TAMVS		98.24 173	98.05 182	98.80 159	99.07 208	97.18 210	97.88 188	98.81 280	96.66 265	99.17 125	99.21 109	94.81 260	99.77 216	96.96 187	99.88 72	99.44 153

PAPR		95.29 322	94.47 331	97.75 270	97.50 377	95.14 283	94.89 368	98.71 294	91.39 376	95.35 374	95.48 378	94.57 266	99.14 383	84.95 396	97.37 370	98.97 266

RPSCF		98.62 121	98.36 144	99.42 57	99.65 64	99.42 7	98.55 107	99.57 61	97.72 179	98.90 167	99.26 99	96.12 208	99.52 329	95.72 273	99.71 155	99.32 201

Vis-MVSNet (Re-imp)		97.46 235	97.16 246	98.34 224	99.55 92	96.10 248	98.94 74	98.44 308	98.32 132	98.16 246	98.62 243	88.76 331	99.73 240	93.88 324	99.79 114	99.18 234

test_0402		98.76 93	98.71 88	98.93 143	99.56 88	98.14 129	98.45 126	99.34 151	99.28 55	98.95 155	98.91 184	98.34 69	99.79 199	95.63 277	99.91 61	98.86 284

MVS_111021_HR		98.25 172	98.08 180	98.75 172	99.09 204	97.46 191	95.97 327	99.27 186	97.60 189	97.99 261	98.25 281	98.15 86	99.38 358	96.87 197	99.57 208	99.42 160

CSCG		98.68 110	98.50 119	99.20 98	99.45 127	98.63 88	98.56 106	99.57 61	97.87 168	98.85 177	98.04 299	97.66 116	99.84 135	96.72 211	99.81 99	99.13 243

PatchMatch-RL		97.24 254	96.78 269	98.61 189	99.03 219	97.83 164	96.36 306	99.06 233	93.49 352	97.36 311	97.78 313	95.75 228	99.49 337	93.44 336	98.77 315	98.52 323

API-MVS		97.04 268	96.91 260	97.42 300	97.88 354	98.23 123	98.18 147	98.50 306	97.57 191	97.39 308	96.75 352	96.77 179	99.15 382	90.16 381	99.02 298	94.88 402

Test By Simon												96.52 192

TDRefinement		99.42 19	99.38 21	99.55 23	99.76 30	99.33 16	99.68 5	99.71 33	99.38 43	99.53 59	99.61 36	98.64 44	99.80 184	98.24 104	99.84 83	99.52 117

USDC		97.41 240	97.40 232	97.44 299	98.94 230	93.67 330	95.17 359	99.53 80	94.03 344	98.97 152	99.10 135	95.29 245	99.34 363	95.84 269	99.73 143	99.30 208

EPP-MVSNet		98.30 164	98.04 183	99.07 119	99.56 88	97.83 164	99.29 32	98.07 324	99.03 88	98.59 211	99.13 129	92.16 308	99.90 63	96.87 197	99.68 168	99.49 126

PMMVS		96.51 289	95.98 295	98.09 244	97.53 372	95.84 259	94.92 367	98.84 275	91.58 372	96.05 359	95.58 373	95.68 231	99.66 279	95.59 279	98.09 350	98.76 301

PAPM		91.88 371	90.34 374	96.51 335	98.06 344	92.56 348	92.44 399	97.17 344	86.35 396	90.38 403	96.01 364	86.61 344	99.21 378	70.65 409	95.43 395	97.75 369

ACMMP		98.75 94	98.50 119	99.52 38	99.56 88	99.16 43	98.87 79	99.37 136	97.16 240	98.82 183	99.01 160	97.71 113	99.87 99	96.29 245	99.69 163	99.54 107
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		97.17 260	96.71 273	98.55 201	98.56 305	98.05 144	96.33 308	98.93 255	96.91 252	97.06 319	97.39 337	94.38 271	99.45 347	91.66 362	99.18 279	98.14 349

PatchmatchNet		95.58 317	95.67 303	95.30 366	97.34 381	87.32 393	97.65 219	96.65 358	95.30 314	97.07 318	98.69 227	84.77 359	99.75 230	94.97 291	98.64 327	98.83 286
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS		98.29 167	97.95 191	99.34 72	98.44 318	99.16 43	98.12 154	99.38 131	96.01 291	98.06 256	98.43 265	97.80 108	99.67 268	95.69 275	99.58 204	99.20 227

F-COLMAP		97.30 247	96.68 275	99.14 107	99.19 180	98.39 107	97.27 258	99.30 172	92.93 358	96.62 342	98.00 300	95.73 229	99.68 265	92.62 353	98.46 334	99.35 192

ANet_high		99.57 7	99.67 5	99.28 84	99.89 6	98.09 134	99.14 53	99.93 4	99.82 3	99.93 6	99.81 5	99.17 18	99.94 34	99.31 40	100.00 1	99.82 24

wuyk23d		96.06 302	97.62 221	91.38 388	98.65 294	98.57 95	98.85 82	96.95 352	96.86 255	99.90 12	99.16 121	99.18 17	98.40 398	89.23 385	99.77 124	77.18 408

OMC-MVS		97.88 203	97.49 228	99.04 128	98.89 245	98.63 88	96.94 275	99.25 192	95.02 319	98.53 221	98.51 255	97.27 149	99.47 343	93.50 335	99.51 225	99.01 258

MG-MVS		96.77 281	96.61 280	97.26 307	98.31 328	93.06 338	95.93 332	98.12 323	96.45 274	97.92 264	98.73 220	93.77 286	99.39 356	91.19 373	99.04 294	99.33 199

AdaColmap		97.14 262	96.71 273	98.46 213	98.34 326	97.80 171	96.95 274	98.93 255	95.58 304	96.92 325	97.66 320	95.87 224	99.53 325	90.97 375	99.14 283	98.04 354

uanet		0.00 383	0.00 386	0.00 396	0.00 419	0.00 421	0.00 407	0.00 420	0.00 414	0.00 415	0.00 414	0.00 419	0.00 415	0.00 414	0.00 413	0.00 411

ITE_SJBPF				98.87 150	99.22 171	98.48 103		99.35 145	97.50 200	98.28 240	98.60 246	97.64 120	99.35 362	93.86 325	99.27 263	98.79 297

DeepMVS_CX				93.44 384	98.24 333	94.21 308		94.34 383	64.28 408	91.34 402	94.87 391	89.45 329	92.77 409	77.54 407	93.14 402	93.35 404

TinyColmap		97.89 201	97.98 189	97.60 283	98.86 248	94.35 305	96.21 315	99.44 114	97.45 210	99.06 134	98.88 195	97.99 97	99.28 373	94.38 311	99.58 204	99.18 234

MAR-MVS		96.47 293	95.70 301	98.79 162	97.92 351	99.12 57	98.28 138	98.60 301	92.16 368	95.54 370	96.17 363	94.77 263	99.52 329	89.62 383	98.23 340	97.72 371
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		97.90 199	97.69 213	98.52 206	99.17 188	97.66 180	97.19 265	99.47 104	96.31 279	97.85 272	98.20 286	96.71 185	99.52 329	94.62 299	99.72 150	98.38 337

MSDG		97.71 219	97.52 226	98.28 232	98.91 239	96.82 227	94.42 381	99.37 136	97.65 183	98.37 236	98.29 280	97.40 142	99.33 365	94.09 318	99.22 271	98.68 312

LS3D		98.63 119	98.38 141	99.36 63	97.25 383	99.38 8	99.12 56	99.32 158	99.21 61	98.44 228	98.88 195	97.31 145	99.80 184	96.58 220	99.34 252	98.92 275

CLD-MVS		97.49 233	97.16 246	98.48 211	99.07 208	97.03 218	94.71 371	99.21 201	94.46 332	98.06 256	97.16 344	97.57 126	99.48 340	94.46 304	99.78 119	98.95 269
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS		93.44 351	92.23 356	97.08 314	99.25 165	97.86 161	95.61 343	97.16 345	92.90 359	93.76 393	98.65 236	75.94 394	95.66 406	79.30 406	97.49 363	97.73 370

Gipuma		99.03 58	99.16 45	98.64 181	99.94 2	98.51 101	99.32 22	99.75 31	99.58 25	98.60 209	99.62 33	98.22 76	99.51 333	97.70 142	99.73 143	97.89 360
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015

High-resolution multi-view benchmark