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 29	99.63 21	99.78 27	99.67 27	99.48 9	99.81 186	99.30 43	99.97 19	99.77 37
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 91	98.73 90	99.05 129	98.76 270	97.81 173	99.25 40	99.30 176	98.57 128	98.55 226	99.33 95	97.95 104	99.90 67	97.16 175	99.67 179	99.44 161

3Dnovator+	97.89 3	98.69 111	98.51 124	99.24 97	98.81 265	98.40 109	99.02 66	99.19 211	98.99 97	98.07 266	99.28 104	97.11 165	99.84 145	96.84 207	99.32 259	99.47 151

DeepC-MVS	97.60 4	98.97 70	98.93 70	99.10 116	99.35 151	97.98 153	98.01 182	99.46 109	97.56 205	99.54 57	99.50 62	98.97 23	99.84 145	98.06 123	99.92 54	99.49 134
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	98.32 167	98.01 192	99.23 99	98.39 332	98.97 70	95.03 375	99.18 215	96.88 265	99.33 100	98.78 223	98.16 88	99.28 381	96.74 215	99.62 193	99.44 161

DeepC-MVS_fast	96.85 6	98.30 170	98.15 178	98.75 175	98.61 303	97.23 207	97.76 218	99.09 234	97.31 233	98.75 198	98.66 244	97.56 133	99.64 293	96.10 266	99.55 219	99.39 181
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	97.09 270	96.68 281	98.32 233	98.32 335	97.16 215	98.86 86	99.37 141	89.48 399	96.29 363	99.15 138	96.56 196	99.90 67	92.90 354	99.20 281	97.89 371

ACMH	96.65 7	99.25 36	99.24 42	99.26 92	99.72 42	98.38 111	99.07 61	99.55 76	98.30 144	99.65 46	99.45 74	99.22 15	99.76 229	98.44 101	99.77 126	99.64 66
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMH+	96.62 9	99.08 61	99.00 64	99.33 80	99.71 45	98.83 79	98.60 109	99.58 58	99.11 76	99.53 61	99.18 128	98.81 32	99.67 274	96.71 220	99.77 126	99.50 130

COLMAP_ROB	96.50 10	98.99 66	98.85 80	99.41 62	99.58 76	99.10 64	98.74 92	99.56 72	99.09 86	99.33 100	99.19 124	98.40 63	99.72 253	95.98 269	99.76 138	99.42 168
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	96.63 292	95.95 303	98.65 184	98.93 238	98.09 137	96.93 288	99.28 187	83.58 412	98.13 261	97.78 325	96.13 214	99.40 362	93.52 343	99.29 266	98.45 339
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMM	96.08 12	98.91 77	98.73 90	99.48 53	99.55 93	99.14 56	98.07 171	99.37 141	97.62 197	99.04 147	98.96 185	98.84 30	99.79 206	97.43 162	99.65 185	99.49 134
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
HY-MVS	95.94 13	95.90 315	95.35 325	97.55 295	97.95 355	94.79 294	98.81 91	96.94 363	92.28 378	95.17 385	98.57 260	89.90 331	99.75 236	91.20 382	97.33 384	98.10 362

OpenMVS_ROB	95.38 14	95.84 318	95.18 331	97.81 268	98.41 331	97.15 216	97.37 258	98.62 306	83.86 411	98.65 209	98.37 283	94.29 276	99.68 271	88.41 397	98.62 338	96.60 402

ACMP	95.32 15	98.41 154	98.09 183	99.36 66	99.51 105	98.79 82	97.68 226	99.38 137	95.76 311	98.81 191	98.82 216	98.36 65	99.82 172	94.75 305	99.77 126	99.48 144
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PLC	94.65 16	96.51 295	95.73 307	98.85 156	98.75 272	97.91 160	96.42 314	99.06 237	90.94 392	95.59 374	97.38 349	94.41 271	99.59 310	90.93 386	98.04 365	99.05 259
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
PVSNet	93.40 17	95.67 322	95.70 308	95.57 369	98.83 260	88.57 396	92.50 409	97.72 338	92.69 373	96.49 360	96.44 369	93.72 289	99.43 358	93.61 340	99.28 267	98.71 316

PCF-MVS	92.86 18	94.36 344	93.00 361	98.42 223	98.70 283	97.56 189	93.16 407	99.11 231	79.59 416	97.55 303	97.43 346	92.19 310	99.73 246	79.85 416	99.45 242	97.97 370
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
IB-MVS	91.63 19	92.24 378	90.90 382	96.27 350	97.22 392	91.24 378	94.36 394	93.33 403	92.37 376	92.24 411	94.58 403	66.20 417	99.89 78	93.16 351	94.63 409	97.66 384
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	97.86 210	97.94 200	97.65 283	99.71 45	97.94 159	98.52 118	98.68 301	98.99 97	97.52 306	99.35 89	97.41 147	98.18 410	91.59 375	99.67 179	96.82 399
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PVSNet_0	89.98 21	91.15 383	90.30 386	93.70 392	97.72 364	84.34 416	90.24 413	97.42 345	90.20 396	93.79 403	93.09 411	90.90 324	98.89 401	86.57 405	72.76 420	97.87 373

MVE	83.40 22	92.50 373	91.92 375	94.25 384	98.83 260	91.64 368	92.71 408	83.52 422	95.92 307	86.46 420	95.46 389	95.20 249	95.40 418	80.51 415	98.64 335	95.73 411
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CMPMVS	75.91 23	96.29 303	95.44 320	98.84 157	96.25 412	98.69 90	97.02 281	99.12 229	88.90 402	97.83 284	98.86 207	89.51 333	98.90 400	91.92 368	99.51 230	98.92 285
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
BP-MVS1		97.40 247	96.97 260	98.71 181	99.07 213	96.81 231	98.34 144	97.18 353	98.58 127	98.17 254	98.61 255	84.01 373	99.94 36	98.97 66	99.78 120	99.37 190

reproduce_monomvs		95.00 338	95.25 327	94.22 385	97.51 384	83.34 417	97.86 204	98.44 314	98.51 133	99.29 109	99.30 101	67.68 412	99.56 321	98.89 72	99.81 99	99.77 37

mmtdpeth		99.30 29	99.42 20	98.92 149	99.58 76	96.89 229	99.48 10	99.92 7	99.92 2	98.26 251	99.80 9	98.33 70	99.91 61	99.56 29	99.95 30	99.97 4

reproduce_model		99.15 48	98.97 68	99.67 4	99.33 154	99.44 10	98.15 159	99.47 106	99.12 75	99.52 63	99.32 99	98.31 71	99.90 67	97.78 142	99.73 145	99.66 60

reproduce-ours		99.09 57	98.90 73	99.67 4	99.27 164	99.49 6	98.00 183	99.42 126	99.05 91	99.48 70	99.27 106	98.29 73	99.89 78	97.61 152	99.71 158	99.62 70

our_new_method		99.09 57	98.90 73	99.67 4	99.27 164	99.49 6	98.00 183	99.42 126	99.05 91	99.48 70	99.27 106	98.29 73	99.89 78	97.61 152	99.71 158	99.62 70

mmdepth		0.00 394	0.00 397	0.00 407	0.00 430	0.00 432	0.00 418	0.00 431	0.00 425	0.00 426	0.00 425	0.00 430	0.00 426	0.00 425	0.00 424	0.00 422

monomultidepth		0.00 394	0.00 397	0.00 407	0.00 430	0.00 432	0.00 418	0.00 431	0.00 425	0.00 426	0.00 425	0.00 430	0.00 426	0.00 425	0.00 424	0.00 422

mvs5depth		99.30 29	99.59 9	98.44 221	99.65 63	95.35 278	99.82 3	99.94 2	99.83 4	99.42 83	99.94 2	98.13 91	99.96 12	99.63 24	99.96 23	100.00 1

MVStest1		95.86 316	95.60 312	96.63 340	95.87 416	91.70 367	97.93 192	98.94 256	98.03 167	99.56 53	99.66 29	71.83 405	98.26 409	99.35 40	99.24 273	99.91 12

ttmdpeth		97.91 202	98.02 191	97.58 290	98.69 288	94.10 316	98.13 161	98.90 265	97.95 173	97.32 321	99.58 43	95.95 228	98.75 403	96.41 246	99.22 277	99.87 18

WBMVS		95.18 333	94.78 339	96.37 346	97.68 372	89.74 393	95.80 351	98.73 298	97.54 208	98.30 245	98.44 276	70.06 406	99.82 172	96.62 225	99.87 76	99.54 113

dongtai		76.24 387	75.95 390	77.12 403	92.39 421	67.91 427	90.16 414	59.44 428	82.04 414	89.42 416	94.67 402	49.68 426	81.74 421	48.06 421	77.66 419	81.72 417

kuosan		69.30 388	68.95 391	70.34 404	87.68 425	65.00 428	91.11 412	59.90 427	69.02 417	74.46 422	88.89 419	48.58 427	68.03 423	28.61 422	72.33 421	77.99 418

MVSMamba_PlusPlus		98.83 87	98.98 67	98.36 230	99.32 155	96.58 243	98.90 80	99.41 130	99.75 8	98.72 201	99.50 62	96.17 212	99.94 36	99.27 45	99.78 120	98.57 332

MGCFI-Net		98.34 163	98.28 160	98.51 211	98.47 321	97.59 188	98.96 74	99.48 98	99.18 71	97.40 316	95.50 386	98.66 43	99.50 342	98.18 114	98.71 328	98.44 342

testing91		93.32 362	92.27 366	96.47 344	97.54 377	91.25 377	96.17 331	96.76 367	97.18 249	93.65 405	93.50 409	65.11 419	99.63 296	93.04 352	97.45 375	98.53 333

testing11		93.08 367	92.02 371	96.26 351	97.56 375	90.83 385	96.32 320	95.70 384	96.47 285	92.66 409	93.73 406	64.36 420	99.59 310	93.77 338	97.57 371	98.37 351

testing99		93.04 368	91.98 374	96.23 353	97.53 379	90.70 387	96.35 318	95.94 380	96.87 266	93.41 406	93.43 410	63.84 421	99.59 310	93.24 350	97.19 385	98.40 347

UBG		93.25 364	92.32 365	96.04 360	97.72 364	90.16 390	95.92 345	95.91 381	96.03 302	93.95 402	93.04 412	69.60 408	99.52 336	90.72 390	97.98 366	98.45 339

UWE-MVS		92.38 375	91.76 378	94.21 386	97.16 393	84.65 412	95.42 365	88.45 417	95.96 305	96.17 364	95.84 381	66.36 415	99.71 254	91.87 370	98.64 335	98.28 354

ETVMVS		92.60 372	91.08 381	97.18 315	97.70 369	93.65 338	96.54 306	95.70 384	96.51 281	94.68 391	92.39 415	61.80 422	99.50 342	86.97 402	97.41 378	98.40 347

sasdasda		98.34 163	98.26 164	98.58 197	98.46 323	97.82 170	98.96 74	99.46 109	99.19 69	97.46 311	95.46 389	98.59 50	99.46 353	98.08 121	98.71 328	98.46 336

testing222		91.96 380	90.37 384	96.72 339	97.47 386	92.59 353	96.11 333	94.76 390	96.83 268	92.90 408	92.87 413	57.92 423	99.55 325	86.93 403	97.52 372	98.00 369

WB-MVSnew		95.73 321	95.57 315	96.23 353	96.70 403	90.70 387	96.07 335	93.86 400	95.60 315	97.04 330	95.45 392	96.00 220	99.55 325	91.04 384	98.31 347	98.43 344

fmvsm_l_conf0.5_n_a		99.19 43	99.27 38	98.94 144	99.65 63	97.05 218	97.80 211	99.76 31	98.70 117	99.78 27	99.11 144	98.79 34	99.95 24	99.85 5	99.96 23	99.83 24

fmvsm_l_conf0.5_n		99.21 41	99.28 37	99.02 134	99.64 69	97.28 204	97.82 208	99.76 31	98.73 114	99.82 21	99.09 150	98.81 32	99.95 24	99.86 4	99.96 23	99.83 24

fmvsm_s_conf0.1_n_a		99.17 44	99.30 35	98.80 163	99.75 33	96.59 241	97.97 191	99.86 15	98.22 152	99.88 17	99.71 19	98.59 50	99.84 145	99.73 18	99.98 12	99.98 3

fmvsm_s_conf0.1_n		99.16 47	99.33 29	98.64 185	99.71 45	96.10 252	97.87 203	99.85 17	98.56 131	99.90 12	99.68 22	98.69 41	99.85 127	99.72 20	99.98 12	99.97 4

fmvsm_s_conf0.5_n_a		99.10 56	99.20 44	98.78 169	99.55 93	96.59 241	97.79 212	99.82 24	98.21 153	99.81 24	99.53 58	98.46 60	99.84 145	99.70 21	99.97 19	99.90 13

fmvsm_s_conf0.5_n		99.09 57	99.26 40	98.61 193	99.55 93	96.09 255	97.74 220	99.81 25	98.55 132	99.85 19	99.55 52	98.60 49	99.84 145	99.69 23	99.98 12	99.89 14

MM		98.22 180	97.99 194	98.91 150	98.66 298	96.97 222	97.89 199	94.44 393	99.54 30	98.95 162	99.14 141	93.50 290	99.92 52	99.80 11	99.96 23	99.85 22

WAC-MVS						90.90 383								91.37 379

Syy-MVS		96.04 310	95.56 316	97.49 301	97.10 395	94.48 305	96.18 329	96.58 370	95.65 313	94.77 389	92.29 416	91.27 320	99.36 367	98.17 116	98.05 363	98.63 326

test_fmvsmconf0.1_n		99.49 12	99.54 11	99.34 75	99.78 23	98.11 134	97.77 215	99.90 11	99.33 51	99.97 3	99.66 29	99.71 3	99.96 12	99.79 12	99.99 5	99.96 7

test_fmvsmconf0.01_n		99.57 7	99.63 7	99.36 66	99.87 12	98.13 133	98.08 169	99.95 1	99.45 37	99.98 2	99.75 13	99.80 1	99.97 5	99.82 7	99.99 5	99.99 2

myMVS_eth3d		91.92 381	90.45 383	96.30 348	97.10 395	90.90 383	96.18 329	96.58 370	95.65 313	94.77 389	92.29 416	53.88 424	99.36 367	89.59 395	98.05 363	98.63 326

testing3		93.51 359	92.09 369	97.75 275	98.60 305	94.40 307	97.32 262	95.26 388	97.56 205	96.79 347	95.50 386	53.57 425	99.77 223	95.26 295	98.97 312	99.08 255

SSC-MVS		98.71 104	98.74 88	98.62 190	99.72 42	96.08 257	98.74 92	98.64 305	99.74 10	99.67 42	99.24 115	94.57 268	99.95 24	99.11 55	99.24 273	99.82 27

test_fmvsmconf_n		99.44 15	99.48 15	99.31 85	99.64 69	98.10 136	97.68 226	99.84 20	99.29 56	99.92 8	99.57 45	99.60 5	99.96 12	99.74 17	99.98 12	99.89 14

WB-MVS		98.52 145	98.55 119	98.43 222	99.65 63	95.59 267	98.52 118	98.77 291	99.65 18	99.52 63	99.00 175	94.34 274	99.93 43	98.65 89	98.83 320	99.76 42

test_fmvsmvis_n_1920		99.26 35	99.49 13	98.54 208	99.66 62	96.97 222	98.00 183	99.85 17	99.24 60	99.92 8	99.50 62	99.39 11	99.95 24	99.89 3	99.98 12	98.71 316

dmvs_re		95.98 313	95.39 323	97.74 277	98.86 254	97.45 195	98.37 140	95.69 386	97.95 173	96.56 354	95.95 376	90.70 325	97.68 413	88.32 398	96.13 400	98.11 361

SDMVSNet		99.23 40	99.32 31	98.96 141	99.68 56	97.35 200	98.84 89	99.48 98	99.69 13	99.63 49	99.68 22	99.03 21	99.96 12	97.97 130	99.92 54	99.57 96

dmvs_testset		92.94 369	92.21 368	95.13 377	98.59 308	90.99 382	97.65 232	92.09 408	96.95 261	94.00 400	93.55 408	92.34 309	96.97 416	72.20 419	92.52 414	97.43 391

sd_testset		99.28 32	99.31 33	99.19 103	99.68 56	98.06 146	99.41 14	99.30 176	99.69 13	99.63 49	99.68 22	99.25 14	99.96 12	97.25 171	99.92 54	99.57 96

test_fmvsm_n_1920		99.33 27	99.45 19	98.99 137	99.57 81	97.73 180	97.93 192	99.83 22	99.22 61	99.93 6	99.30 101	99.42 10	99.96 12	99.85 5	99.99 5	99.29 219

test_cas_vis1_n_1920		98.33 166	98.68 101	97.27 312	99.69 54	92.29 361	98.03 177	99.85 17	97.62 197	99.96 4	99.62 36	93.98 283	99.74 241	99.52 33	99.86 80	99.79 32

test_vis1_n_1920		98.40 156	98.92 71	96.81 335	99.74 35	90.76 386	98.15 159	99.91 9	98.33 141	99.89 15	99.55 52	95.07 253	99.88 90	99.76 15	99.93 43	99.79 32

test_vis1_n		98.31 169	98.50 126	97.73 279	99.76 29	94.17 314	98.68 102	99.91 9	96.31 291	99.79 26	99.57 45	92.85 302	99.42 360	99.79 12	99.84 85	99.60 79

test_fmvs1_n		98.09 191	98.28 160	97.52 298	99.68 56	93.47 340	98.63 105	99.93 5	95.41 324	99.68 40	99.64 34	91.88 315	99.48 348	99.82 7	99.87 76	99.62 70

mvsany_test1		97.60 230	97.54 228	97.77 271	97.72 364	95.35 278	95.36 367	97.13 356	94.13 352	99.71 34	99.33 95	97.93 105	99.30 377	97.60 154	98.94 315	98.67 324

APD_test1		98.83 87	98.66 104	99.34 75	99.78 23	99.47 9	98.42 136	99.45 113	98.28 149	98.98 154	99.19 124	97.76 116	99.58 316	96.57 230	99.55 219	98.97 276

test_vis1_rt		97.75 220	97.72 216	97.83 266	98.81 265	96.35 247	97.30 264	99.69 39	94.61 339	97.87 280	98.05 310	96.26 210	98.32 408	98.74 82	98.18 352	98.82 298

test_vis3_rt		99.14 49	99.17 46	99.07 122	99.78 23	98.38 111	98.92 79	99.94 2	97.80 186	99.91 11	99.67 27	97.15 162	98.91 399	99.76 15	99.56 216	99.92 11

test_fmvs2		98.70 108	98.97 68	97.89 263	99.54 98	94.05 317	98.55 114	99.92 7	96.78 271	99.72 32	99.78 10	96.60 195	99.67 274	99.91 2	99.90 67	99.94 9

test_fmvs1		97.72 222	97.94 200	97.07 322	98.66 298	92.39 358	97.68 226	99.81 25	95.20 328	99.54 57	99.44 75	91.56 318	99.41 361	99.78 14	99.77 126	99.40 180

test_fmvs3		99.12 54	99.41 21	98.25 239	99.76 29	95.07 290	99.05 64	99.94 2	97.78 188	99.82 21	99.84 3	98.56 54	99.71 254	99.96 1	99.96 23	99.97 4

mvsany_test3		98.87 82	98.92 71	98.74 179	99.38 140	96.94 226	98.58 111	99.10 232	96.49 283	99.96 4	99.81 6	98.18 84	99.45 355	98.97 66	99.79 115	99.83 24

testf1		99.25 36	99.16 48	99.51 46	99.89 6	99.63 4	98.71 99	99.69 39	98.90 106	99.43 80	99.35 89	98.86 28	99.67 274	97.81 139	99.81 99	99.24 229

APD_test2		99.25 36	99.16 48	99.51 46	99.89 6	99.63 4	98.71 99	99.69 39	98.90 106	99.43 80	99.35 89	98.86 28	99.67 274	97.81 139	99.81 99	99.24 229

test_f		98.67 119	98.87 76	98.05 256	99.72 42	95.59 267	98.51 123	99.81 25	96.30 293	99.78 27	99.82 5	96.14 213	98.63 405	99.82 7	99.93 43	99.95 8

FE-MVS		95.66 323	94.95 336	97.77 271	98.53 317	95.28 281	99.40 16	96.09 377	93.11 367	97.96 274	99.26 110	79.10 394	99.77 223	92.40 366	98.71 328	98.27 355

FA-MVS(test-final)		96.99 279	96.82 272	97.50 300	98.70 283	94.78 295	99.34 20	96.99 359	95.07 329	98.48 233	99.33 95	88.41 344	99.65 290	96.13 265	98.92 317	98.07 364

balanced_conf03		98.63 125	98.72 92	98.38 227	98.66 298	96.68 240	98.90 80	99.42 126	98.99 97	98.97 158	99.19 124	95.81 233	99.85 127	98.77 80	99.77 126	98.60 328

MonoMVSNet		96.25 305	96.53 292	95.39 374	96.57 405	91.01 381	98.82 90	97.68 341	98.57 128	98.03 271	99.37 84	90.92 323	97.78 412	94.99 299	93.88 412	97.38 392

patch_mono-2		98.51 146	98.63 108	98.17 245	99.38 140	94.78 295	97.36 259	99.69 39	98.16 163	98.49 232	99.29 103	97.06 166	99.97 5	98.29 109	99.91 61	99.76 42

EGC-MVSNET		85.24 384	80.54 387	99.34 75	99.77 26	99.20 38	99.08 58	99.29 184	12.08 422	20.84 423	99.42 77	97.55 134	99.85 127	97.08 183	99.72 153	98.96 278

test2506		92.39 374	91.89 376	93.89 390	99.38 140	82.28 420	99.32 23	66.03 426	99.08 88	98.77 195	99.57 45	66.26 416	99.84 145	98.71 85	99.95 30	99.54 113

test1111		96.49 298	96.82 272	95.52 370	99.42 135	87.08 404	99.22 42	87.14 418	99.11 76	99.46 75	99.58 43	88.69 338	99.86 115	98.80 76	99.95 30	99.62 70

ECVR-MVS		96.42 300	96.61 286	95.85 362	99.38 140	88.18 400	99.22 42	86.00 420	99.08 88	99.36 95	99.57 45	88.47 343	99.82 172	98.52 98	99.95 30	99.54 113

test_blank		0.00 394	0.00 397	0.00 407	0.00 430	0.00 432	0.00 418	0.00 431	0.00 425	0.00 426	0.00 425	0.00 430	0.00 426	0.00 425	0.00 424	0.00 422

tt0805		98.69 111	98.62 110	98.90 153	99.75 33	99.30 21	99.15 53	96.97 360	98.86 109	98.87 182	97.62 336	98.63 46	98.96 396	99.41 38	98.29 348	98.45 339

DVP-MVS++		98.90 79	98.70 98	99.51 46	98.43 327	99.15 51	99.43 12	99.32 163	98.17 160	99.26 116	99.02 163	98.18 84	99.88 90	97.07 184	99.45 242	99.49 134

FOURS1					99.73 36	99.67 3	99.43 12	99.54 80	99.43 41	99.26 116

MSC_two_6792asdad				99.32 82	98.43 327	98.37 113		98.86 276					99.89 78	97.14 178	99.60 200	99.71 49

PC_three_1452									93.27 364	99.40 88	98.54 262	98.22 80	97.00 415	95.17 296	99.45 242	99.49 134

No_MVS				99.32 82	98.43 327	98.37 113		98.86 276					99.89 78	97.14 178	99.60 200	99.71 49

test_one_0601					99.39 139	99.20 38		99.31 168	98.49 134	98.66 208	99.02 163	97.64 126

eth-test2					0.00 430

eth-test					0.00 430

GeoE		99.05 62	98.99 66	99.25 95	99.44 129	98.35 117	98.73 96	99.56 72	98.42 137	98.91 172	98.81 218	98.94 25	99.91 61	98.35 105	99.73 145	99.49 134

test_method		79.78 385	79.50 388	80.62 401	80.21 426	45.76 429	70.82 417	98.41 318	31.08 421	80.89 421	97.71 329	84.85 364	97.37 414	91.51 377	80.03 418	98.75 313

Anonymous20240521		98.69 111	98.87 76	98.16 247	99.77 26	95.11 289	99.08 58	99.44 117	99.34 50	99.33 100	99.55 52	94.10 282	99.94 36	99.25 48	99.96 23	99.42 168

h-mvs33		97.77 219	97.33 243	99.10 116	99.21 178	97.84 166	98.35 142	98.57 308	99.11 76	98.58 221	99.02 163	88.65 341	99.96 12	98.11 118	96.34 396	99.49 134

hse-mvs2		97.46 240	97.07 255	98.64 185	98.73 274	97.33 201	97.45 254	97.64 344	99.11 76	98.58 221	97.98 314	88.65 341	99.79 206	98.11 118	97.39 379	98.81 302

CL-MVSNet_self_test		97.44 243	97.22 248	98.08 252	98.57 312	95.78 265	94.30 395	98.79 288	96.58 280	98.60 217	98.19 299	94.74 266	99.64 293	96.41 246	98.84 319	98.82 298

KD-MVS_2432*1600		92.87 370	91.99 372	95.51 371	91.37 422	89.27 394	94.07 397	98.14 328	95.42 321	97.25 323	96.44 369	67.86 410	99.24 383	91.28 380	96.08 401	98.02 366

KD-MVS_self_test		99.25 36	99.18 45	99.44 59	99.63 73	99.06 68	98.69 101	99.54 80	99.31 53	99.62 52	99.53 58	97.36 150	99.86 115	99.24 50	99.71 158	99.39 181

AUN-MVS		96.24 307	95.45 319	98.60 195	98.70 283	97.22 209	97.38 257	97.65 342	95.95 306	95.53 381	97.96 318	82.11 384	99.79 206	96.31 252	97.44 376	98.80 307

ZD-MVS					99.01 226	98.84 78		99.07 236	94.10 353	98.05 269	98.12 303	96.36 207	99.86 115	92.70 362	99.19 284

SR-MVS-dyc-post		98.81 91	98.55 119	99.57 20	99.20 182	99.38 12	98.48 129	99.30 176	98.64 118	98.95 162	98.96 185	97.49 144	99.86 115	96.56 234	99.39 249	99.45 157

RE-MVS-def			98.58 117		99.20 182	99.38 12	98.48 129	99.30 176	98.64 118	98.95 162	98.96 185	97.75 117		96.56 234	99.39 249	99.45 157

SED-MVS		98.91 77	98.72 92	99.49 51	99.49 115	99.17 43	98.10 167	99.31 168	98.03 167	99.66 43	99.02 163	98.36 65	99.88 90	96.91 196	99.62 193	99.41 171

IU-MVS					99.49 115	99.15 51		98.87 271	92.97 368	99.41 85				96.76 213	99.62 193	99.66 60

OPU-MVS				98.82 159	98.59 308	98.30 118	98.10 167				98.52 265	98.18 84	98.75 403	94.62 309	99.48 239	99.41 171

test_241102_TWO								99.30 176	98.03 167	99.26 116	99.02 163	97.51 140	99.88 90	96.91 196	99.60 200	99.66 60

test_241102_ONE					99.49 115	99.17 43		99.31 168	97.98 170	99.66 43	98.90 197	98.36 65	99.48 348

SF-MVS		98.53 142	98.27 163	99.32 82	99.31 156	98.75 83	98.19 154	99.41 130	96.77 272	98.83 186	98.90 197	97.80 114	99.82 172	95.68 285	99.52 228	99.38 188

cl22		95.79 319	95.39 323	96.98 325	96.77 402	92.79 350	94.40 393	98.53 310	94.59 340	97.89 278	98.17 300	82.82 381	99.24 383	96.37 248	99.03 302	98.92 285

miper_ehance_all_eth		97.06 272	97.03 257	97.16 319	97.83 360	93.06 344	94.66 385	99.09 234	95.99 304	98.69 203	98.45 275	92.73 305	99.61 305	96.79 209	99.03 302	98.82 298

miper_enhance_ethall		96.01 311	95.74 306	96.81 335	96.41 410	92.27 362	93.69 404	98.89 268	91.14 390	98.30 245	97.35 352	90.58 326	99.58 316	96.31 252	99.03 302	98.60 328

ZNCC-MVS		98.68 116	98.40 143	99.54 30	99.57 81	99.21 32	98.46 131	99.29 184	97.28 236	98.11 263	98.39 280	98.00 99	99.87 107	96.86 206	99.64 187	99.55 109

dcpmvs_2		98.78 95	99.11 54	97.78 270	99.56 89	93.67 336	99.06 62	99.86 15	99.50 32	99.66 43	99.26 110	97.21 160	99.99 2	98.00 128	99.91 61	99.68 56

cl____		97.02 275	96.83 271	97.58 290	97.82 361	94.04 319	94.66 385	99.16 222	97.04 256	98.63 211	98.71 233	88.68 340	99.69 262	97.00 188	99.81 99	99.00 271

DIV-MVS_self_test		97.02 275	96.84 270	97.58 290	97.82 361	94.03 320	94.66 385	99.16 222	97.04 256	98.63 211	98.71 233	88.69 338	99.69 262	97.00 188	99.81 99	99.01 267

eth_miper_zixun_eth		97.23 261	97.25 246	97.17 317	98.00 354	92.77 351	94.71 382	99.18 215	97.27 237	98.56 224	98.74 229	91.89 314	99.69 262	97.06 186	99.81 99	99.05 259

9.14			97.78 210		99.07 213		97.53 246	99.32 163	95.53 318	98.54 228	98.70 236	97.58 131	99.76 229	94.32 322	99.46 240

uanet_test		0.00 394	0.00 397	0.00 407	0.00 430	0.00 432	0.00 418	0.00 431	0.00 425	0.00 426	0.00 425	0.00 430	0.00 426	0.00 425	0.00 424	0.00 422

DCPMVS		0.00 394	0.00 397	0.00 407	0.00 430	0.00 432	0.00 418	0.00 431	0.00 425	0.00 426	0.00 425	0.00 430	0.00 426	0.00 425	0.00 424	0.00 422

save fliter					99.11 204	97.97 154	96.53 308	99.02 248	98.24 150

ET-MVSNet_ETH3D		94.30 347	93.21 357	97.58 290	98.14 347	94.47 306	94.78 381	93.24 404	94.72 337	89.56 415	95.87 379	78.57 397	99.81 186	96.91 196	97.11 388	98.46 336

UniMVSNet_ETH3D		99.69 2	99.69 4	99.69 3	99.84 17	99.34 19	99.69 5	99.58 58	99.90 3	99.86 18	99.78 10	99.58 6	99.95 24	99.00 64	99.95 30	99.78 35

EIA-MVS		98.00 197	97.74 213	98.80 163	98.72 276	98.09 137	98.05 174	99.60 55	97.39 225	96.63 351	95.55 384	97.68 120	99.80 193	96.73 217	99.27 268	98.52 334

miper_refine_blended		92.87 370	91.99 372	95.51 371	91.37 422	89.27 394	94.07 397	98.14 328	95.42 321	97.25 323	96.44 369	67.86 410	99.24 383	91.28 380	96.08 401	98.02 366

miper_lstm_enhance		97.18 265	97.16 251	97.25 314	98.16 345	92.85 349	95.15 373	99.31 168	97.25 239	98.74 200	98.78 223	90.07 329	99.78 217	97.19 173	99.80 110	99.11 254

ETV-MVS		98.03 194	97.86 207	98.56 204	98.69 288	98.07 143	97.51 249	99.50 89	98.10 165	97.50 308	95.51 385	98.41 62	99.88 90	96.27 255	99.24 273	97.71 383

CS-MVS		99.13 52	99.10 56	99.24 97	99.06 218	99.15 51	99.36 19	99.88 13	99.36 49	98.21 253	98.46 274	98.68 42	99.93 43	99.03 62	99.85 81	98.64 325

D2MVS		97.84 216	97.84 208	97.83 266	99.14 200	94.74 297	96.94 286	98.88 269	95.84 309	98.89 175	98.96 185	94.40 272	99.69 262	97.55 155	99.95 30	99.05 259

DVP-MVS		98.77 98	98.52 123	99.52 42	99.50 108	99.21 32	98.02 179	98.84 280	97.97 171	99.08 138	99.02 163	97.61 129	99.88 90	96.99 190	99.63 190	99.48 144
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									98.17 160	99.08 138	99.02 163	97.89 106	99.88 90	97.07 184	99.71 158	99.70 54

test_0728_SECOND				99.60 14	99.50 108	99.23 30	98.02 179	99.32 163					99.88 90	96.99 190	99.63 190	99.68 56

test0726					99.50 108	99.21 32	98.17 158	99.35 150	97.97 171	99.26 116	99.06 151	97.61 129

SR-MVS		98.71 104	98.43 139	99.57 20	99.18 192	99.35 16	98.36 141	99.29 184	98.29 147	98.88 178	98.85 210	97.53 137	99.87 107	96.14 263	99.31 261	99.48 144

DPM-MVS		96.32 302	95.59 314	98.51 211	98.76 270	97.21 210	94.54 391	98.26 322	91.94 380	96.37 361	97.25 353	93.06 297	99.43 358	91.42 378	98.74 324	98.89 290

GST-MVS		98.61 129	98.30 158	99.52 42	99.51 105	99.20 38	98.26 148	99.25 196	97.44 222	98.67 206	98.39 280	97.68 120	99.85 127	96.00 267	99.51 230	99.52 124

test_yl		96.69 288	96.29 298	97.90 261	98.28 337	95.24 282	97.29 265	97.36 347	98.21 153	98.17 254	97.86 321	86.27 352	99.55 325	94.87 303	98.32 345	98.89 290

thisisatest0530		95.27 331	94.45 342	97.74 277	99.19 185	94.37 308	97.86 204	90.20 414	97.17 250	98.22 252	97.65 333	73.53 404	99.90 67	96.90 201	99.35 255	98.95 279

Anonymous20240529		98.93 75	98.87 76	99.12 112	99.19 185	98.22 127	99.01 67	98.99 254	99.25 59	99.54 57	99.37 84	97.04 167	99.80 193	97.89 133	99.52 228	99.35 201

Anonymous202405211		97.90 203	97.50 231	99.08 120	98.90 246	98.25 121	98.53 117	96.16 375	98.87 108	99.11 133	98.86 207	90.40 328	99.78 217	97.36 165	99.31 261	99.19 241

DCV-MVSNet		96.69 288	96.29 298	97.90 261	98.28 337	95.24 282	97.29 265	97.36 347	98.21 153	98.17 254	97.86 321	86.27 352	99.55 325	94.87 303	98.32 345	98.89 290

tttt0517		95.64 324	94.98 334	97.64 285	99.36 147	93.81 331	98.72 97	90.47 413	98.08 166	98.67 206	98.34 287	73.88 403	99.92 52	97.77 143	99.51 230	99.20 236

our_test_3		97.39 248	97.73 215	96.34 347	98.70 283	89.78 392	94.61 388	98.97 255	96.50 282	99.04 147	98.85 210	95.98 225	99.84 145	97.26 170	99.67 179	99.41 171

thisisatest0515		94.12 351	93.16 358	96.97 326	98.60 305	92.90 348	93.77 403	90.61 412	94.10 353	96.91 337	95.87 379	74.99 402	99.80 193	94.52 312	99.12 295	98.20 357

ppachtmachnet_test		97.50 236	97.74 213	96.78 337	98.70 283	91.23 379	94.55 390	99.05 240	96.36 288	99.21 124	98.79 221	96.39 203	99.78 217	96.74 215	99.82 95	99.34 203

SMA-MVS		98.40 156	98.03 190	99.51 46	99.16 195	99.21 32	98.05 174	99.22 204	94.16 351	98.98 154	99.10 147	97.52 139	99.79 206	96.45 244	99.64 187	99.53 121
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																98.81 302

DPE-MVS		98.59 132	98.26 164	99.57 20	99.27 164	99.15 51	97.01 282	99.39 135	97.67 193	99.44 79	98.99 176	97.53 137	99.89 78	95.40 293	99.68 173	99.66 60
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part2					99.36 147	99.10 64				99.05 145

thres100view900		94.19 348	93.67 352	95.75 365	99.06 218	91.35 373	98.03 177	94.24 397	98.33 141	97.40 316	94.98 397	79.84 388	99.62 299	83.05 410	98.08 360	96.29 403

tfpnnormal		98.90 79	98.90 73	98.91 150	99.67 60	97.82 170	99.00 69	99.44 117	99.45 37	99.51 68	99.24 115	98.20 83	99.86 115	95.92 271	99.69 168	99.04 263

tfpn200view9		94.03 352	93.44 354	95.78 364	98.93 238	91.44 371	97.60 238	94.29 395	97.94 175	97.10 326	94.31 404	79.67 390	99.62 299	83.05 410	98.08 360	96.29 403

c3_l		97.36 249	97.37 239	97.31 309	98.09 350	93.25 342	95.01 376	99.16 222	97.05 255	98.77 195	98.72 232	92.88 300	99.64 293	96.93 195	99.76 138	99.05 259

CHOSEN 280x420		95.51 328	95.47 317	95.65 368	98.25 339	88.27 399	93.25 406	98.88 269	93.53 361	94.65 392	97.15 356	86.17 354	99.93 43	97.41 163	99.93 43	98.73 315

CANet		97.87 209	97.76 211	98.19 244	97.75 363	95.51 272	96.76 297	99.05 240	97.74 189	96.93 334	98.21 297	95.59 239	99.89 78	97.86 138	99.93 43	99.19 241

Fast-Effi-MVS+-dtu		98.27 174	98.09 183	98.81 161	98.43 327	98.11 134	97.61 237	99.50 89	98.64 118	97.39 318	97.52 341	98.12 92	99.95 24	96.90 201	98.71 328	98.38 349

Effi-MVS+-dtu		98.26 176	97.90 204	99.35 72	98.02 353	99.49 6	98.02 179	99.16 222	98.29 147	97.64 295	97.99 313	96.44 202	99.95 24	96.66 223	98.93 316	98.60 328

CANet_DTU		97.26 257	97.06 256	97.84 265	97.57 374	94.65 302	96.19 328	98.79 288	97.23 245	95.14 386	98.24 294	93.22 292	99.84 145	97.34 166	99.84 85	99.04 263

MVS_0304		97.44 243	97.01 259	98.72 180	96.42 409	96.74 236	97.20 273	91.97 409	98.46 136	98.30 245	98.79 221	92.74 304	99.91 61	99.30 43	99.94 38	99.52 124

MP-MVS-pluss		98.57 133	98.23 168	99.60 14	99.69 54	99.35 16	97.16 277	99.38 137	94.87 335	98.97 158	98.99 176	98.01 98	99.88 90	97.29 168	99.70 165	99.58 91
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MSP-MVS		98.40 156	98.00 193	99.61 12	99.57 81	99.25 28	98.57 112	99.35 150	97.55 207	99.31 108	97.71 329	94.61 267	99.88 90	96.14 263	99.19 284	99.70 54
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												84.74 366				98.81 302

sam_mvs												84.29 372

IterMVS-SCA-FT		97.85 215	98.18 173	96.87 331	99.27 164	91.16 380	95.53 359	99.25 196	99.10 83	99.41 85	99.35 89	93.10 295	99.96 12	98.65 89	99.94 38	99.49 134

TSAR-MVS + MP.		98.63 125	98.49 130	99.06 128	99.64 69	97.90 161	98.51 123	98.94 256	96.96 260	99.24 121	98.89 203	97.83 109	99.81 186	96.88 203	99.49 238	99.48 144
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		97.86 210	98.17 174	96.92 328	98.98 231	93.91 326	96.45 311	99.17 219	97.85 183	98.41 239	97.14 357	98.47 57	99.92 52	98.02 125	99.05 298	96.92 396

OPM-MVS		98.56 134	98.32 157	99.25 95	99.41 137	98.73 87	97.13 279	99.18 215	97.10 254	98.75 198	98.92 193	98.18 84	99.65 290	96.68 222	99.56 216	99.37 190
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMMP_NAP		98.75 100	98.48 131	99.57 20	99.58 76	99.29 23	97.82 208	99.25 196	96.94 262	98.78 192	99.12 143	98.02 97	99.84 145	97.13 180	99.67 179	99.59 85

ambc				98.24 241	98.82 263	95.97 259	98.62 107	99.00 253		99.27 112	99.21 121	96.99 172	99.50 342	96.55 237	99.50 237	99.26 225

MTGPA								99.20 207

SPE-MVS-test		99.13 52	99.09 57	99.26 92	99.13 202	98.97 70	99.31 27	99.88 13	99.44 39	98.16 257	98.51 266	98.64 44	99.93 43	98.91 69	99.85 81	98.88 293

Effi-MVS+		98.02 195	97.82 209	98.62 190	98.53 317	97.19 212	97.33 261	99.68 44	97.30 234	96.68 349	97.46 345	98.56 54	99.80 193	96.63 224	98.20 351	98.86 295

xiu_mvs_v2_base		97.16 267	97.49 232	96.17 356	98.54 315	92.46 356	95.45 363	98.84 280	97.25 239	97.48 310	96.49 366	98.31 71	99.90 67	96.34 251	98.68 333	96.15 407

xiu_mvs_v1_base		97.86 210	98.17 174	96.92 328	98.98 231	93.91 326	96.45 311	99.17 219	97.85 183	98.41 239	97.14 357	98.47 57	99.92 52	98.02 125	99.05 298	96.92 396

new-patchmatchnet		98.35 162	98.74 88	97.18 315	99.24 171	92.23 363	96.42 314	99.48 98	98.30 144	99.69 38	99.53 58	97.44 146	99.82 172	98.84 75	99.77 126	99.49 134

pmmvs6		99.67 3	99.70 3	99.60 14	99.90 4	99.27 26	99.53 8	99.76 31	99.64 19	99.84 20	99.83 4	99.50 8	99.87 107	99.36 39	99.92 54	99.64 66

pmmvs5		97.64 228	97.49 232	98.08 252	99.14 200	95.12 288	96.70 301	99.05 240	93.77 358	98.62 213	98.83 213	93.23 291	99.75 236	98.33 108	99.76 138	99.36 197

test_post1							97.59 240				20.48 424	83.07 379	99.66 285	94.16 323

test_post											21.25 423	83.86 375	99.70 258

Fast-Effi-MVS+		97.67 226	97.38 238	98.57 200	98.71 279	97.43 197	97.23 269	99.45 113	94.82 336	96.13 365	96.51 365	98.52 56	99.91 61	96.19 259	98.83 320	98.37 351

patchmatchnet-post											98.77 225	84.37 369	99.85 127

Anonymous20231211		99.27 33	99.27 38	99.26 92	99.29 161	98.18 128	99.49 9	99.51 87	99.70 12	99.80 25	99.68 22	96.84 178	99.83 162	99.21 51	99.91 61	99.77 37

pmmvs-eth3d		98.47 149	98.34 153	98.86 155	99.30 159	97.76 176	97.16 277	99.28 187	95.54 317	99.42 83	99.19 124	97.27 155	99.63 296	97.89 133	99.97 19	99.20 236

GG-mvs-BLEND				94.76 380	94.54 419	92.13 364	99.31 27	80.47 424		88.73 418	91.01 418	67.59 413	98.16 411	82.30 414	94.53 410	93.98 414

xiu_mvs_v1_base_debi		97.86 210	98.17 174	96.92 328	98.98 231	93.91 326	96.45 311	99.17 219	97.85 183	98.41 239	97.14 357	98.47 57	99.92 52	98.02 125	99.05 298	96.92 396

Anonymous20231206		98.21 182	98.21 169	98.20 243	99.51 105	95.43 276	98.13 161	99.32 163	96.16 296	98.93 170	98.82 216	96.00 220	99.83 162	97.32 167	99.73 145	99.36 197

MTAPA		98.88 81	98.64 107	99.61 12	99.67 60	99.36 15	98.43 134	99.20 207	98.83 113	98.89 175	98.90 197	96.98 173	99.92 52	97.16 175	99.70 165	99.56 102

MTMP							97.93 192	91.91 410

gm-plane-assit					94.83 418	81.97 421			88.07 405		94.99 396		99.60 306	91.76 371

test9_res														93.28 349	99.15 289	99.38 188

MVP-Stereo		98.08 192	97.92 202	98.57 200	98.96 234	96.79 232	97.90 198	99.18 215	96.41 287	98.46 234	98.95 189	95.93 229	99.60 306	96.51 240	98.98 311	99.31 214
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST9					98.71 279	98.08 141	95.96 340	99.03 245	91.40 386	95.85 371	97.53 339	96.52 198	99.76 229

train_agg		97.10 269	96.45 294	99.07 122	98.71 279	98.08 141	95.96 340	99.03 245	91.64 381	95.85 371	97.53 339	96.47 200	99.76 229	93.67 339	99.16 287	99.36 197

gg-mvs-nofinetune		92.37 376	91.20 380	95.85 362	95.80 417	92.38 359	99.31 27	81.84 423	99.75 8	91.83 412	99.74 15	68.29 409	99.02 393	87.15 401	97.12 387	96.16 406

SCA		96.41 301	96.66 284	95.67 366	98.24 340	88.35 398	95.85 349	96.88 365	96.11 297	97.67 294	98.67 241	93.10 295	99.85 127	94.16 323	99.22 277	98.81 302

Patchmatch-test		96.55 294	96.34 296	97.17 317	98.35 333	93.06 344	98.40 137	97.79 336	97.33 230	98.41 239	98.67 241	83.68 376	99.69 262	95.16 297	99.31 261	98.77 310

test_8					98.67 293	98.01 149	95.91 346	99.02 248	91.64 381	95.79 373	97.50 342	96.47 200	99.76 229

MS-PatchMatch		97.68 225	97.75 212	97.45 304	98.23 342	93.78 332	97.29 265	98.84 280	96.10 298	98.64 210	98.65 246	96.04 217	99.36 367	96.84 207	99.14 290	99.20 236

Patchmatch-RL test		97.26 257	97.02 258	97.99 260	99.52 103	95.53 271	96.13 332	99.71 36	97.47 214	99.27 112	99.16 134	84.30 371	99.62 299	97.89 133	99.77 126	98.81 302

cdsmvs_eth3d_5k		24.66 389	32.88 392	0.00 407	0.00 430	0.00 432	0.00 418	99.10 232	0.00 425	0.00 426	97.58 337	99.21 16	0.00 426	0.00 425	0.00 424	0.00 422

pcd_1.5k_mvsjas		8.17 392	10.90 395	0.00 407	0.00 430	0.00 432	0.00 418	0.00 431	0.00 425	0.00 426	0.00 425	98.07 93	0.00 426	0.00 425	0.00 424	0.00 422

agg_prior2														92.50 365	99.16 287	99.37 190

agg_prior					98.68 292	97.99 150		99.01 251		95.59 374			99.77 223

tmp_tt		78.77 386	78.73 389	78.90 402	58.45 427	74.76 426	94.20 396	78.26 425	39.16 420	86.71 419	92.82 414	80.50 386	75.19 422	86.16 406	92.29 415	86.74 416

canonicalmvs		98.34 163	98.26 164	98.58 197	98.46 323	97.82 170	98.96 74	99.46 109	99.19 69	97.46 311	95.46 389	98.59 50	99.46 353	98.08 121	98.71 328	98.46 336

anonymousdsp		99.51 11	99.47 17	99.62 9	99.88 9	99.08 67	99.34 20	99.69 39	98.93 104	99.65 46	99.72 18	98.93 26	99.95 24	99.11 55	100.00 1	99.82 27

alignmvs		97.35 250	96.88 267	98.78 169	98.54 315	98.09 137	97.71 223	97.69 340	99.20 65	97.59 299	95.90 378	88.12 346	99.55 325	98.18 114	98.96 313	98.70 319

nrg030		99.40 22	99.35 26	99.54 30	99.58 76	99.13 59	98.98 72	99.48 98	99.68 15	99.46 75	99.26 110	98.62 47	99.73 246	99.17 54	99.92 54	99.76 42

v144192		98.54 140	98.57 118	98.45 219	99.21 178	95.98 258	97.63 234	99.36 145	97.15 253	99.32 106	99.18 128	95.84 232	99.84 145	99.50 34	99.91 61	99.54 113

FIs		99.14 49	99.09 57	99.29 86	99.70 52	98.28 119	99.13 55	99.52 86	99.48 33	99.24 121	99.41 81	96.79 184	99.82 172	98.69 87	99.88 73	99.76 42

v1921920		98.54 140	98.60 115	98.38 227	99.20 182	95.76 266	97.56 243	99.36 145	97.23 245	99.38 91	99.17 132	96.02 218	99.84 145	99.57 27	99.90 67	99.54 113

UA-Net		99.47 13	99.40 22	99.70 2	99.49 115	99.29 23	99.80 4	99.72 35	99.82 5	99.04 147	99.81 6	98.05 96	99.96 12	98.85 74	99.99 5	99.86 21

v1192		98.60 130	98.66 104	98.41 224	99.27 164	95.88 261	97.52 247	99.36 145	97.41 223	99.33 100	99.20 123	96.37 206	99.82 172	99.57 27	99.92 54	99.55 109

FC-MVSNet-test		99.27 33	99.25 41	99.34 75	99.77 26	98.37 113	99.30 32	99.57 65	99.61 26	99.40 88	99.50 62	97.12 163	99.85 127	99.02 63	99.94 38	99.80 31

v1144		98.60 130	98.66 104	98.41 224	99.36 147	95.90 260	97.58 241	99.34 156	97.51 210	99.27 112	99.15 138	96.34 208	99.80 193	99.47 36	99.93 43	99.51 127

sosnet-low-res		0.00 394	0.00 397	0.00 407	0.00 430	0.00 432	0.00 418	0.00 431	0.00 425	0.00 426	0.00 425	0.00 430	0.00 426	0.00 425	0.00 424	0.00 422

HFP-MVS		98.71 104	98.44 138	99.51 46	99.49 115	99.16 47	98.52 118	99.31 168	97.47 214	98.58 221	98.50 270	97.97 103	99.85 127	96.57 230	99.59 204	99.53 121

v148		98.45 151	98.60 115	98.00 259	99.44 129	94.98 291	97.44 255	99.06 237	98.30 144	99.32 106	98.97 182	96.65 193	99.62 299	98.37 104	99.85 81	99.39 181

sosnet		0.00 394	0.00 397	0.00 407	0.00 430	0.00 432	0.00 418	0.00 431	0.00 425	0.00 426	0.00 425	0.00 430	0.00 426	0.00 425	0.00 424	0.00 422

uncertanet		0.00 394	0.00 397	0.00 407	0.00 430	0.00 432	0.00 418	0.00 431	0.00 425	0.00 426	0.00 425	0.00 430	0.00 426	0.00 425	0.00 424	0.00 422

AllTest		98.44 152	98.20 170	99.16 107	99.50 108	98.55 99	98.25 149	99.58 58	96.80 269	98.88 178	99.06 151	97.65 123	99.57 318	94.45 315	99.61 198	99.37 190

TestCases				99.16 107	99.50 108	98.55 99		99.58 58	96.80 269	98.88 178	99.06 151	97.65 123	99.57 318	94.45 315	99.61 198	99.37 190

v7n		99.53 9	99.57 10	99.41 62	99.88 9	98.54 102	99.45 11	99.61 54	99.66 17	99.68 40	99.66 29	98.44 61	99.95 24	99.73 18	99.96 23	99.75 46

region2R		98.69 111	98.40 143	99.54 30	99.53 101	99.17 43	98.52 118	99.31 168	97.46 219	98.44 236	98.51 266	97.83 109	99.88 90	96.46 243	99.58 209	99.58 91

RRT-MVS		97.88 207	97.98 195	97.61 287	98.15 346	93.77 333	98.97 73	99.64 49	99.16 73	98.69 203	99.42 77	91.60 316	99.89 78	97.63 151	98.52 342	99.16 250

mamv4		99.44 15	99.39 23	99.58 19	99.30 159	99.74 2	99.04 65	99.81 25	99.77 7	99.82 21	99.57 45	97.82 112	99.98 4	99.53 31	99.89 71	99.01 267

PS-MVSNAJss		99.46 14	99.49 13	99.35 72	99.90 4	98.15 130	99.20 45	99.65 48	99.48 33	99.92 8	99.71 19	98.07 93	99.96 12	99.53 31	100.00 1	99.93 10

PS-MVSNAJ		97.08 271	97.39 237	96.16 358	98.56 313	92.46 356	95.24 370	98.85 279	97.25 239	97.49 309	95.99 375	98.07 93	99.90 67	96.37 248	98.67 334	96.12 408

jajsoiax		99.58 6	99.61 8	99.48 53	99.87 12	98.61 94	99.28 37	99.66 47	99.09 86	99.89 15	99.68 22	99.53 7	99.97 5	99.50 34	99.99 5	99.87 18

mvs_tets		99.63 5	99.67 5	99.49 51	99.88 9	98.61 94	99.34 20	99.71 36	99.27 58	99.90 12	99.74 15	99.68 4	99.97 5	99.55 30	99.99 5	99.88 17

EI-MVSNet-UG-set		98.69 111	98.71 95	98.62 190	99.10 206	96.37 246	97.23 269	98.87 271	99.20 65	99.19 126	98.99 176	97.30 152	99.85 127	98.77 80	99.79 115	99.65 65

EI-MVSNet-Vis-set		98.68 116	98.70 98	98.63 189	99.09 209	96.40 245	97.23 269	98.86 276	99.20 65	99.18 130	98.97 182	97.29 154	99.85 127	98.72 84	99.78 120	99.64 66

HPM-MVS++		98.10 189	97.64 223	99.48 53	99.09 209	99.13 59	97.52 247	98.75 295	97.46 219	96.90 340	97.83 324	96.01 219	99.84 145	95.82 279	99.35 255	99.46 153

test_prior4						97.97 154	95.86 347

XVS		98.72 103	98.45 136	99.53 37	99.46 125	99.21 32	98.65 103	99.34 156	98.62 122	97.54 304	98.63 251	97.50 141	99.83 162	96.79 209	99.53 225	99.56 102

v1240		98.55 138	98.62 110	98.32 233	99.22 176	95.58 269	97.51 249	99.45 113	97.16 251	99.45 78	99.24 115	96.12 215	99.85 127	99.60 25	99.88 73	99.55 109

pm-mvs1		99.44 15	99.48 15	99.33 80	99.80 20	98.63 91	99.29 33	99.63 50	99.30 55	99.65 46	99.60 41	99.16 20	99.82 172	99.07 58	99.83 92	99.56 102

test_prior2							95.74 353		96.48 284	96.11 366	97.63 335	95.92 230		94.16 323	99.20 281

X-MVStestdata		94.32 345	92.59 363	99.53 37	99.46 125	99.21 32	98.65 103	99.34 156	98.62 122	97.54 304	45.85 420	97.50 141	99.83 162	96.79 209	99.53 225	99.56 102

test_prior				98.95 143	98.69 288	97.95 158		99.03 245					99.59 310			99.30 217

旧先验2							95.76 352		88.56 404	97.52 306			99.66 285	94.48 313

新几何2							95.93 343

新几何1				98.91 150	98.94 236	97.76 176		98.76 292	87.58 406	96.75 348	98.10 305	94.80 263	99.78 217	92.73 361	99.00 307	99.20 236

旧先验1					98.82 263	97.45 195		98.76 292			98.34 287	95.50 243			99.01 306	99.23 231

无先验							95.74 353	98.74 297	89.38 400				99.73 246	92.38 367		99.22 235

原ACMM2							95.53 359

原ACMM1				98.35 231	98.90 246	96.25 250		98.83 284	92.48 375	96.07 368	98.10 305	95.39 246	99.71 254	92.61 364	98.99 309	99.08 255

test222					98.92 242	96.93 227	95.54 358	98.78 290	85.72 409	96.86 343	98.11 304	94.43 270			99.10 297	99.23 231

testdata2													99.79 206	92.80 359

segment_acmp												97.02 170

testdata				98.09 249	98.93 238	95.40 277		98.80 287	90.08 397	97.45 313	98.37 283	95.26 248	99.70 258	93.58 342	98.95 314	99.17 247

testdata1							95.44 364		96.32 290

v8		99.01 64	99.16 48	98.57 200	99.47 124	96.31 249	98.90 80	99.47 106	99.03 94	99.52 63	99.57 45	96.93 174	99.81 186	99.60 25	99.98 12	99.60 79

1314		95.74 320	95.60 312	96.17 356	97.53 379	92.75 352	98.07 171	98.31 321	91.22 388	94.25 395	96.68 363	95.53 240	99.03 392	91.64 374	97.18 386	96.74 400

LFMVS		97.20 263	96.72 278	98.64 185	98.72 276	96.95 225	98.93 78	94.14 399	99.74 10	98.78 192	99.01 172	84.45 368	99.73 246	97.44 161	99.27 268	99.25 226

VDD-MVS		98.56 134	98.39 146	99.07 122	99.13 202	98.07 143	98.59 110	97.01 358	99.59 27	99.11 133	99.27 106	94.82 260	99.79 206	98.34 106	99.63 190	99.34 203

VDDNet		98.21 182	97.95 198	99.01 135	99.58 76	97.74 178	99.01 67	97.29 351	99.67 16	98.97 158	99.50 62	90.45 327	99.80 193	97.88 136	99.20 281	99.48 144

v10		98.97 70	99.11 54	98.55 205	99.44 129	96.21 251	98.90 80	99.55 76	98.73 114	99.48 70	99.60 41	96.63 194	99.83 162	99.70 21	99.99 5	99.61 78

VPNet		98.87 82	98.83 81	99.01 135	99.70 52	97.62 187	98.43 134	99.35 150	99.47 35	99.28 110	99.05 158	96.72 190	99.82 172	98.09 120	99.36 253	99.59 85

MVS		93.19 365	92.09 369	96.50 343	96.91 398	94.03 320	98.07 171	98.06 332	68.01 418	94.56 394	96.48 367	95.96 227	99.30 377	83.84 409	96.89 391	96.17 405

v2v482		98.56 134	98.62 110	98.37 229	99.42 135	95.81 264	97.58 241	99.16 222	97.90 179	99.28 110	99.01 172	95.98 225	99.79 206	99.33 41	99.90 67	99.51 127

V42		98.78 95	98.78 86	98.76 173	99.44 129	97.04 219	98.27 147	99.19 211	97.87 181	99.25 120	99.16 134	96.84 178	99.78 217	99.21 51	99.84 85	99.46 153

SD-MVS		98.40 156	98.68 101	97.54 296	98.96 234	97.99 150	97.88 200	99.36 145	98.20 157	99.63 49	99.04 160	98.76 35	95.33 419	96.56 234	99.74 142	99.31 214
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		95.86 316	95.32 326	97.49 301	98.60 305	94.15 315	93.83 402	97.93 334	95.49 319	96.68 349	97.42 347	83.21 377	99.30 377	96.22 257	98.55 341	99.01 267

MSLP-MVS++		98.02 195	98.14 180	97.64 285	98.58 310	95.19 285	97.48 251	99.23 203	97.47 214	97.90 277	98.62 253	97.04 167	98.81 402	97.55 155	99.41 247	98.94 283

APDe-MVS		98.99 66	98.79 85	99.60 14	99.21 178	99.15 51	98.87 84	99.48 98	97.57 203	99.35 97	99.24 115	97.83 109	99.89 78	97.88 136	99.70 165	99.75 46
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
APD-MVS_3200maxsize		98.84 86	98.61 114	99.53 37	99.19 185	99.27 26	98.49 126	99.33 161	98.64 118	99.03 150	98.98 180	97.89 106	99.85 127	96.54 238	99.42 246	99.46 153

ADS-MVSNet2		95.43 329	94.98 334	96.76 338	98.14 347	91.74 366	97.92 195	97.76 337	90.23 393	96.51 357	98.91 194	85.61 359	99.85 127	92.88 355	96.90 389	98.69 320

EI-MVSNet		98.40 156	98.51 124	98.04 257	99.10 206	94.73 298	97.20 273	98.87 271	98.97 100	99.06 140	99.02 163	96.00 220	99.80 193	98.58 92	99.82 95	99.60 79

Regformer		0.00 394	0.00 397	0.00 407	0.00 430	0.00 432	0.00 418	0.00 431	0.00 425	0.00 426	0.00 425	0.00 430	0.00 426	0.00 425	0.00 424	0.00 422

CVMVSNet		96.25 305	97.21 249	93.38 396	99.10 206	80.56 423	97.20 273	98.19 327	96.94 262	99.00 152	99.02 163	89.50 334	99.80 193	96.36 250	99.59 204	99.78 35

pmmvs4		97.58 233	97.28 244	98.51 211	98.84 258	96.93 227	95.40 366	98.52 311	93.60 360	98.61 215	98.65 246	95.10 252	99.60 306	96.97 193	99.79 115	98.99 272

EU-MVSNet		97.66 227	98.50 126	95.13 377	99.63 73	85.84 407	98.35 142	98.21 324	98.23 151	99.54 57	99.46 70	95.02 254	99.68 271	98.24 110	99.87 76	99.87 18

VNet		98.42 153	98.30 158	98.79 166	98.79 269	97.29 203	98.23 150	98.66 302	99.31 53	98.85 183	98.80 219	94.80 263	99.78 217	98.13 117	99.13 292	99.31 214

test-LLR		93.90 354	93.85 348	94.04 387	96.53 406	84.62 413	94.05 399	92.39 406	96.17 294	94.12 397	95.07 393	82.30 382	99.67 274	95.87 275	98.18 352	97.82 374

TESTMET0.1,1		92.19 379	91.77 377	93.46 394	96.48 408	82.80 419	94.05 399	91.52 411	94.45 345	94.00 400	94.88 399	66.65 414	99.56 321	95.78 280	98.11 358	98.02 366

test-mter		92.33 377	91.76 378	94.04 387	96.53 406	84.62 413	94.05 399	92.39 406	94.00 356	94.12 397	95.07 393	65.63 418	99.67 274	95.87 275	98.18 352	97.82 374

VPA-MVSNet		99.30 29	99.30 35	99.28 87	99.49 115	98.36 116	99.00 69	99.45 113	99.63 21	99.52 63	99.44 75	98.25 75	99.88 90	99.09 57	99.84 85	99.62 70

ACMMPR		98.70 108	98.42 141	99.54 30	99.52 103	99.14 56	98.52 118	99.31 168	97.47 214	98.56 224	98.54 262	97.75 117	99.88 90	96.57 230	99.59 204	99.58 91

testgi		98.32 167	98.39 146	98.13 248	99.57 81	95.54 270	97.78 213	99.49 96	97.37 227	99.19 126	97.65 333	98.96 24	99.49 345	96.50 241	98.99 309	99.34 203

test20.03		98.78 95	98.77 87	98.78 169	99.46 125	97.20 211	97.78 213	99.24 201	99.04 93	99.41 85	98.90 197	97.65 123	99.76 229	97.70 148	99.79 115	99.39 181

thres600view7		94.45 343	93.83 349	96.29 349	99.06 218	91.53 369	97.99 187	94.24 397	98.34 140	97.44 314	95.01 395	79.84 388	99.67 274	84.33 408	98.23 349	97.66 384

ADS-MVSNet		95.24 332	94.93 337	96.18 355	98.14 347	90.10 391	97.92 195	97.32 350	90.23 393	96.51 357	98.91 194	85.61 359	99.74 241	92.88 355	96.90 389	98.69 320

MP-MVS		98.46 150	98.09 183	99.54 30	99.57 81	99.22 31	98.50 125	99.19 211	97.61 200	97.58 300	98.66 244	97.40 148	99.88 90	94.72 308	99.60 200	99.54 113
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		17.12 390	20.53 393	6.87 406	12.05 428	4.20 431	93.62 405	6.73 429	4.62 424	10.41 424	24.33 421	8.28 429	3.56 425	9.69 424	15.07 422	12.86 421

thres400		94.14 350	93.44 354	96.24 352	98.93 238	91.44 371	97.60 238	94.29 395	97.94 175	97.10 326	94.31 404	79.67 390	99.62 299	83.05 410	98.08 360	97.66 384

test123		17.04 391	20.11 394	7.82 405	10.25 429	4.91 430	94.80 380	4.47 430	4.93 423	10.00 425	24.28 422	9.69 428	3.64 424	10.14 423	12.43 423	14.92 420

thres200		93.72 357	93.14 359	95.46 373	98.66 298	91.29 375	96.61 305	94.63 392	97.39 225	96.83 344	93.71 407	79.88 387	99.56 321	82.40 413	98.13 357	95.54 412

test0.0.03 1		94.51 342	93.69 351	96.99 324	96.05 413	93.61 339	94.97 377	93.49 401	96.17 294	97.57 302	94.88 399	82.30 382	99.01 395	93.60 341	94.17 411	98.37 351

pmmvs3		95.03 336	94.40 343	96.93 327	97.70 369	92.53 355	95.08 374	97.71 339	88.57 403	97.71 291	98.08 308	79.39 392	99.82 172	96.19 259	99.11 296	98.43 344

EMVS		93.83 355	94.02 347	93.23 397	96.83 401	84.96 410	89.77 416	96.32 374	97.92 177	97.43 315	96.36 372	86.17 354	98.93 398	87.68 400	97.73 369	95.81 410

E-PMN		94.17 349	94.37 344	93.58 393	96.86 399	85.71 409	90.11 415	97.07 357	98.17 160	97.82 286	97.19 354	84.62 367	98.94 397	89.77 393	97.68 370	96.09 409

PGM-MVS		98.66 120	98.37 149	99.55 27	99.53 101	99.18 42	98.23 150	99.49 96	97.01 259	98.69 203	98.88 204	98.00 99	99.89 78	95.87 275	99.59 204	99.58 91

LCM-MVSNet-Re		98.64 123	98.48 131	99.11 114	98.85 257	98.51 104	98.49 126	99.83 22	98.37 138	99.69 38	99.46 70	98.21 82	99.92 52	94.13 327	99.30 264	98.91 288

LCM-MVSNet		99.93 1	99.92 1	99.94 1	99.99 1	99.97 1	99.90 1	99.89 12	99.98 1	99.99 1	99.96 1	99.77 2	100.00 1	99.81 10	100.00 1	99.85 22

MCST-MVS		98.00 197	97.63 224	99.10 116	99.24 171	98.17 129	96.89 291	98.73 298	95.66 312	97.92 275	97.70 331	97.17 161	99.66 285	96.18 261	99.23 276	99.47 151

mvs_anonymous		97.83 218	98.16 177	96.87 331	98.18 344	91.89 365	97.31 263	98.90 265	97.37 227	98.83 186	99.46 70	96.28 209	99.79 206	98.90 70	98.16 355	98.95 279

MVS_Test		98.18 185	98.36 150	97.67 281	98.48 320	94.73 298	98.18 155	99.02 248	97.69 192	98.04 270	99.11 144	97.22 159	99.56 321	98.57 94	98.90 318	98.71 316

MDA-MVSNet-bldmvs		97.94 201	97.91 203	98.06 254	99.44 129	94.96 292	96.63 304	99.15 227	98.35 139	98.83 186	99.11 144	94.31 275	99.85 127	96.60 227	98.72 326	99.37 190

CDPH-MVS		97.26 257	96.66 284	99.07 122	99.00 227	98.15 130	96.03 336	99.01 251	91.21 389	97.79 287	97.85 323	96.89 176	99.69 262	92.75 360	99.38 252	99.39 181

test12				98.93 146	98.58 310	97.83 167		98.66 302		96.53 355		95.51 242	99.69 262		99.13 292	99.27 222

casdiffmvs		98.95 73	99.00 64	98.81 161	99.38 140	97.33 201	97.82 208	99.57 65	99.17 72	99.35 97	99.17 132	98.35 68	99.69 262	98.46 100	99.73 145	99.41 171
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		98.22 180	98.24 167	98.17 245	99.00 227	95.44 275	96.38 316	99.58 58	97.79 187	98.53 229	98.50 270	96.76 187	99.74 241	97.95 132	99.64 187	99.34 203
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		93.73 356	92.83 362	96.42 345	97.70 369	91.28 376	96.84 293	89.77 415	93.96 357	92.44 410	95.93 377	79.14 393	99.77 223	92.94 353	96.76 393	98.21 356

baseline1		95.96 314	95.44 320	97.52 298	98.51 319	93.99 323	98.39 138	96.09 377	98.21 153	98.40 243	97.76 327	86.88 348	99.63 296	95.42 292	89.27 417	98.95 279

YYNet1		97.60 230	97.67 218	97.39 308	99.04 222	93.04 347	95.27 368	98.38 319	97.25 239	98.92 171	98.95 189	95.48 244	99.73 246	96.99 190	98.74 324	99.41 171

PMMVS2		98.07 193	98.08 186	98.04 257	99.41 137	94.59 304	94.59 389	99.40 133	97.50 211	98.82 189	98.83 213	96.83 180	99.84 145	97.50 160	99.81 99	99.71 49

MDA-MVSNet_test_wron		97.60 230	97.66 221	97.41 307	99.04 222	93.09 343	95.27 368	98.42 316	97.26 238	98.88 178	98.95 189	95.43 245	99.73 246	97.02 187	98.72 326	99.41 171

tpmvs		95.02 337	95.25 327	94.33 383	96.39 411	85.87 406	98.08 169	96.83 366	95.46 320	95.51 382	98.69 237	85.91 357	99.53 332	94.16 323	96.23 398	97.58 387

PM-MVS		98.82 89	98.72 92	99.12 112	99.64 69	98.54 102	97.98 188	99.68 44	97.62 197	99.34 99	99.18 128	97.54 135	99.77 223	97.79 141	99.74 142	99.04 263

HQP_MVS		97.99 200	97.67 218	98.93 146	99.19 185	97.65 184	97.77 215	99.27 190	98.20 157	97.79 287	97.98 314	94.90 256	99.70 258	94.42 317	99.51 230	99.45 157

plane_prior7					99.19 185	97.87 163

plane_prior6					98.99 230	97.70 182						94.90 256

plane_prior5								99.27 190					99.70 258	94.42 317	99.51 230	99.45 157

plane_prior4											97.98 314

plane_prior3						97.78 175			97.41 223	97.79 287

plane_prior2							97.77 215		98.20 157

plane_prior1					99.05 221

plane_prior						97.65 184	97.07 280		96.72 274						99.36 253

PS-CasMVS		99.40 22	99.33 29	99.62 9	99.71 45	99.10 64	99.29 33	99.53 83	99.53 31	99.46 75	99.41 81	98.23 77	99.95 24	98.89 72	99.95 30	99.81 30

UniMVSNet_NR-MVSNet		98.86 85	98.68 101	99.40 64	99.17 193	98.74 84	97.68 226	99.40 133	99.14 74	99.06 140	98.59 258	96.71 191	99.93 43	98.57 94	99.77 126	99.53 121

PEN-MVS		99.41 21	99.34 28	99.62 9	99.73 36	99.14 56	99.29 33	99.54 80	99.62 24	99.56 53	99.42 77	98.16 88	99.96 12	98.78 77	99.93 43	99.77 37

TransMVSNet (Re)		99.44 15	99.47 17	99.36 66	99.80 20	98.58 97	99.27 39	99.57 65	99.39 44	99.75 31	99.62 36	99.17 18	99.83 162	99.06 59	99.62 193	99.66 60

DTE-MVSNet		99.43 19	99.35 26	99.66 7	99.71 45	99.30 21	99.31 27	99.51 87	99.64 19	99.56 53	99.46 70	98.23 77	99.97 5	98.78 77	99.93 43	99.72 48

DU-MVS		98.82 89	98.63 108	99.39 65	99.16 195	98.74 84	97.54 245	99.25 196	98.84 112	99.06 140	98.76 227	96.76 187	99.93 43	98.57 94	99.77 126	99.50 130

UniMVSNet (Re)		98.87 82	98.71 95	99.35 72	99.24 171	98.73 87	97.73 222	99.38 137	98.93 104	99.12 132	98.73 230	96.77 185	99.86 115	98.63 91	99.80 110	99.46 153

CP-MVSNet		99.21 41	99.09 57	99.56 25	99.65 63	98.96 74	99.13 55	99.34 156	99.42 42	99.33 100	99.26 110	97.01 171	99.94 36	98.74 82	99.93 43	99.79 32

WR-MVS_H		99.33 27	99.22 43	99.65 8	99.71 45	99.24 29	99.32 23	99.55 76	99.46 36	99.50 69	99.34 93	97.30 152	99.93 43	98.90 70	99.93 43	99.77 37

WR-MVS		98.40 156	98.19 172	99.03 132	99.00 227	97.65 184	96.85 292	98.94 256	98.57 128	98.89 175	98.50 270	95.60 238	99.85 127	97.54 157	99.85 81	99.59 85

NR-MVSNet		98.95 73	98.82 82	99.36 66	99.16 195	98.72 89	99.22 42	99.20 207	99.10 83	99.72 32	98.76 227	96.38 205	99.86 115	98.00 128	99.82 95	99.50 130

Baseline_NR-MVSNet		98.98 69	98.86 79	99.36 66	99.82 19	98.55 99	97.47 253	99.57 65	99.37 46	99.21 124	99.61 39	96.76 187	99.83 162	98.06 123	99.83 92	99.71 49

TranMVSNet+NR-MVSNet		99.17 44	99.07 60	99.46 58	99.37 146	98.87 77	98.39 138	99.42 126	99.42 42	99.36 95	99.06 151	98.38 64	99.95 24	98.34 106	99.90 67	99.57 96

TSAR-MVS + GP.		98.18 185	97.98 195	98.77 172	98.71 279	97.88 162	96.32 320	98.66 302	96.33 289	99.23 123	98.51 266	97.48 145	99.40 362	97.16 175	99.46 240	99.02 266

n2								0.00 431

nn								0.00 431

mPP-MVS		98.64 123	98.34 153	99.54 30	99.54 98	99.17 43	98.63 105	99.24 201	97.47 214	98.09 265	98.68 239	97.62 128	99.89 78	96.22 257	99.62 193	99.57 96

door-mid								99.57 65

XVG-OURS-SEG-HR		98.49 147	98.28 160	99.14 110	99.49 115	98.83 79	96.54 306	99.48 98	97.32 232	99.11 133	98.61 255	99.33 13	99.30 377	96.23 256	98.38 344	99.28 221

mvsmamba		97.57 234	97.26 245	98.51 211	98.69 288	96.73 237	98.74 92	97.25 352	97.03 258	97.88 279	99.23 119	90.95 322	99.87 107	96.61 226	99.00 307	98.91 288

MVSFormer		98.26 176	98.43 139	97.77 271	98.88 252	93.89 329	99.39 17	99.56 72	99.11 76	98.16 257	98.13 301	93.81 286	99.97 5	99.26 46	99.57 213	99.43 165

jason		97.45 242	97.35 241	97.76 274	99.24 171	93.93 325	95.86 347	98.42 316	94.24 349	98.50 231	98.13 301	94.82 260	99.91 61	97.22 172	99.73 145	99.43 165
jason: jason.
lupinMVS		97.06 272	96.86 268	97.65 283	98.88 252	93.89 329	95.48 362	97.97 333	93.53 361	98.16 257	97.58 337	93.81 286	99.91 61	96.77 212	99.57 213	99.17 247

test_djsdf		99.52 10	99.51 12	99.53 37	99.86 14	98.74 84	99.39 17	99.56 72	99.11 76	99.70 36	99.73 17	99.00 22	99.97 5	99.26 46	99.98 12	99.89 14

HPM-MVS_fast		99.01 64	98.82 82	99.57 20	99.71 45	99.35 16	99.00 69	99.50 89	97.33 230	98.94 169	98.86 207	98.75 36	99.82 172	97.53 158	99.71 158	99.56 102

K. test v3		98.00 197	97.66 221	99.03 132	99.79 22	97.56 189	99.19 49	92.47 405	99.62 24	99.52 63	99.66 29	89.61 332	99.96 12	99.25 48	99.81 99	99.56 102

lessismore_v0				98.97 140	99.73 36	97.53 191		86.71 419		99.37 93	99.52 61	89.93 330	99.92 52	98.99 65	99.72 153	99.44 161

SixPastTwentyTwo		98.75 100	98.62 110	99.16 107	99.83 18	97.96 157	99.28 37	98.20 325	99.37 46	99.70 36	99.65 33	92.65 306	99.93 43	99.04 61	99.84 85	99.60 79

OurMVSNet-221017-0		99.37 25	99.31 33	99.53 37	99.91 3	98.98 69	99.63 7	99.58 58	99.44 39	99.78 27	99.76 12	96.39 203	99.92 52	99.44 37	99.92 54	99.68 56

HPM-MVS		98.79 93	98.53 122	99.59 18	99.65 63	99.29 23	99.16 51	99.43 123	96.74 273	98.61 215	98.38 282	98.62 47	99.87 107	96.47 242	99.67 179	99.59 85
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
XVG-OURS		98.53 142	98.34 153	99.11 114	99.50 108	98.82 81	95.97 338	99.50 89	97.30 234	99.05 145	98.98 180	99.35 12	99.32 374	95.72 282	99.68 173	99.18 243

XVG-ACMP-BASELINE		98.56 134	98.34 153	99.22 100	99.54 98	98.59 96	97.71 223	99.46 109	97.25 239	98.98 154	98.99 176	97.54 135	99.84 145	95.88 272	99.74 142	99.23 231

casdiffmvs_mvg		99.12 54	99.16 48	98.99 137	99.43 134	97.73 180	98.00 183	99.62 51	99.22 61	99.55 56	99.22 120	98.93 26	99.75 236	98.66 88	99.81 99	99.50 130
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
LPG-MVS_test		98.71 104	98.46 135	99.47 56	99.57 81	98.97 70	98.23 150	99.48 98	96.60 278	99.10 136	99.06 151	98.71 39	99.83 162	95.58 289	99.78 120	99.62 70

LGP-MVS_train				99.47 56	99.57 81	98.97 70		99.48 98	96.60 278	99.10 136	99.06 151	98.71 39	99.83 162	95.58 289	99.78 120	99.62 70

baseline		98.96 72	99.02 62	98.76 173	99.38 140	97.26 206	98.49 126	99.50 89	98.86 109	99.19 126	99.06 151	98.23 77	99.69 262	98.71 85	99.76 138	99.33 208

test11								98.87 271

door								99.41 130

EPNet_dtu		94.93 339	94.78 339	95.38 375	93.58 420	87.68 402	96.78 295	95.69 386	97.35 229	89.14 417	98.09 307	88.15 345	99.49 345	94.95 302	99.30 264	98.98 273
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x2688		97.49 238	97.14 254	98.54 208	99.68 56	96.09 255	96.50 309	99.62 51	91.58 383	98.84 185	98.97 182	92.36 308	99.88 90	96.76 213	99.95 30	99.67 59

EPNet		96.14 308	95.44 320	98.25 239	90.76 424	95.50 273	97.92 195	94.65 391	98.97 100	92.98 407	98.85 210	89.12 336	99.87 107	95.99 268	99.68 173	99.39 181
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS						96.79 232

HQP-NCC					98.67 293		96.29 322		96.05 299	95.55 377

ACMP_Plane					98.67 293		96.29 322		96.05 299	95.55 377

APD-MVS		98.10 189	97.67 218	99.42 60	99.11 204	98.93 75	97.76 218	99.28 187	94.97 332	98.72 201	98.77 225	97.04 167	99.85 127	93.79 337	99.54 221	99.49 134
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS														92.82 357

HQP4-MVS										95.56 376			99.54 330			99.32 210

HQP3-MVS								99.04 243							99.26 271

HQP2-MVS												93.84 284

CNVR-MVS		98.17 187	97.87 206	99.07 122	98.67 293	98.24 122	97.01 282	98.93 259	97.25 239	97.62 296	98.34 287	97.27 155	99.57 318	96.42 245	99.33 258	99.39 181

NCCC		97.86 210	97.47 235	99.05 129	98.61 303	98.07 143	96.98 284	98.90 265	97.63 196	97.04 330	97.93 319	95.99 224	99.66 285	95.31 294	98.82 322	99.43 165

114514_t		96.50 297	95.77 305	98.69 182	99.48 122	97.43 197	97.84 207	99.55 76	81.42 415	96.51 357	98.58 259	95.53 240	99.67 274	93.41 347	99.58 209	98.98 273

CP-MVS		98.70 108	98.42 141	99.52 42	99.36 147	99.12 61	98.72 97	99.36 145	97.54 208	98.30 245	98.40 279	97.86 108	99.89 78	96.53 239	99.72 153	99.56 102

DSMNet-mixed		97.42 245	97.60 226	96.87 331	99.15 199	91.46 370	98.54 116	99.12 229	92.87 371	97.58 300	99.63 35	96.21 211	99.90 67	95.74 281	99.54 221	99.27 222

tpm2		93.09 366	92.58 364	94.62 381	97.56 375	86.53 405	97.66 230	95.79 383	86.15 408	94.07 399	98.23 296	75.95 400	99.53 332	90.91 387	96.86 392	97.81 376

NP-MVS					98.84 258	97.39 199					96.84 360

EG-PatchMatch MVS		98.99 66	99.01 63	98.94 144	99.50 108	97.47 193	98.04 176	99.59 56	98.15 164	99.40 88	99.36 88	98.58 53	99.76 229	98.78 77	99.68 173	99.59 85

tpm cat1		93.29 363	93.13 360	93.75 391	97.39 388	84.74 411	97.39 256	97.65 342	83.39 413	94.16 396	98.41 278	82.86 380	99.39 364	91.56 376	95.35 406	97.14 395

SteuartSystems-ACMMP		98.79 93	98.54 121	99.54 30	99.73 36	99.16 47	98.23 150	99.31 168	97.92 177	98.90 173	98.90 197	98.00 99	99.88 90	96.15 262	99.72 153	99.58 91
Skip Steuart: Steuart Systems R&D Blog.
CostFormer		93.97 353	93.78 350	94.51 382	97.53 379	85.83 408	97.98 188	95.96 379	89.29 401	94.99 388	98.63 251	78.63 396	99.62 299	94.54 311	96.50 394	98.09 363

CR-MVSNet		96.28 304	95.95 303	97.28 311	97.71 367	94.22 310	98.11 165	98.92 262	92.31 377	96.91 337	99.37 84	85.44 362	99.81 186	97.39 164	97.36 382	97.81 376

JIA-IIPM		95.52 327	95.03 333	97.00 323	96.85 400	94.03 320	96.93 288	95.82 382	99.20 65	94.63 393	99.71 19	83.09 378	99.60 306	94.42 317	94.64 408	97.36 393

Patchmtry		97.35 250	96.97 260	98.50 215	97.31 390	96.47 244	98.18 155	98.92 262	98.95 103	98.78 192	99.37 84	85.44 362	99.85 127	95.96 270	99.83 92	99.17 247

PatchT		96.65 291	96.35 295	97.54 296	97.40 387	95.32 280	97.98 188	96.64 369	99.33 51	96.89 341	99.42 77	84.32 370	99.81 186	97.69 150	97.49 373	97.48 389

tpmrst		95.07 335	95.46 318	93.91 389	97.11 394	84.36 415	97.62 235	96.96 361	94.98 331	96.35 362	98.80 219	85.46 361	99.59 310	95.60 287	96.23 398	97.79 379

BH-w/o		95.13 334	94.89 338	95.86 361	98.20 343	91.31 374	95.65 355	97.37 346	93.64 359	96.52 356	95.70 382	93.04 298	99.02 393	88.10 399	95.82 403	97.24 394

tpm		94.67 341	94.34 345	95.66 367	97.68 372	88.42 397	97.88 200	94.90 389	94.46 343	96.03 370	98.56 261	78.66 395	99.79 206	95.88 272	95.01 407	98.78 309

DELS-MVS		98.27 174	98.20 170	98.48 216	98.86 254	96.70 238	95.60 357	99.20 207	97.73 190	98.45 235	98.71 233	97.50 141	99.82 172	98.21 112	99.59 204	98.93 284
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		96.83 284	96.75 277	97.08 320	98.74 273	93.33 341	96.71 300	98.26 322	96.72 274	98.44 236	97.37 350	95.20 249	99.47 351	91.89 369	97.43 377	98.44 342

RPMNet		97.02 275	96.93 262	97.30 310	97.71 367	94.22 310	98.11 165	99.30 176	99.37 46	96.91 337	99.34 93	86.72 349	99.87 107	97.53 158	97.36 382	97.81 376

MVSTER		96.86 283	96.55 290	97.79 269	97.91 358	94.21 312	97.56 243	98.87 271	97.49 213	99.06 140	99.05 158	80.72 385	99.80 193	98.44 101	99.82 95	99.37 190

CPTT-MVS		97.84 216	97.36 240	99.27 90	99.31 156	98.46 107	98.29 145	99.27 190	94.90 334	97.83 284	98.37 283	94.90 256	99.84 145	93.85 336	99.54 221	99.51 127

GBi-Net		98.65 121	98.47 133	99.17 104	98.90 246	98.24 122	99.20 45	99.44 117	98.59 124	98.95 162	99.55 52	94.14 278	99.86 115	97.77 143	99.69 168	99.41 171

PVSNet_Blended_VisFu		98.17 187	98.15 178	98.22 242	99.73 36	95.15 286	97.36 259	99.68 44	94.45 345	98.99 153	99.27 106	96.87 177	99.94 36	97.13 180	99.91 61	99.57 96

PVSNet_BlendedMVS		97.55 235	97.53 229	97.60 288	98.92 242	93.77 333	96.64 303	99.43 123	94.49 341	97.62 296	99.18 128	96.82 181	99.67 274	94.73 306	99.93 43	99.36 197

UnsupCasMVSNet_eth		97.89 205	97.60 226	98.75 175	99.31 156	97.17 214	97.62 235	99.35 150	98.72 116	98.76 197	98.68 239	92.57 307	99.74 241	97.76 147	95.60 404	99.34 203

UnsupCasMVSNet_bld		97.30 254	96.92 264	98.45 219	99.28 162	96.78 235	96.20 327	99.27 190	95.42 321	98.28 249	98.30 291	93.16 293	99.71 254	94.99 299	97.37 380	98.87 294

PVSNet_Blended		96.88 282	96.68 281	97.47 303	98.92 242	93.77 333	94.71 382	99.43 123	90.98 391	97.62 296	97.36 351	96.82 181	99.67 274	94.73 306	99.56 216	98.98 273

FMVSNet5		96.01 311	95.20 330	98.41 224	97.53 379	96.10 252	98.74 92	99.50 89	97.22 248	98.03 271	99.04 160	69.80 407	99.88 90	97.27 169	99.71 158	99.25 226

test1		98.65 121	98.47 133	99.17 104	98.90 246	98.24 122	99.20 45	99.44 117	98.59 124	98.95 162	99.55 52	94.14 278	99.86 115	97.77 143	99.69 168	99.41 171

new_pmnet		96.99 279	96.76 276	97.67 281	98.72 276	94.89 293	95.95 342	98.20 325	92.62 374	98.55 226	98.54 262	94.88 259	99.52 336	93.96 331	99.44 245	98.59 331

FMVSNet3		97.50 236	97.24 247	98.29 237	98.08 351	95.83 263	97.86 204	98.91 264	97.89 180	98.95 162	98.95 189	87.06 347	99.81 186	97.77 143	99.69 168	99.23 231

dp		93.47 360	93.59 353	93.13 398	96.64 404	81.62 422	97.66 230	96.42 373	92.80 372	96.11 366	98.64 249	78.55 398	99.59 310	93.31 348	92.18 416	98.16 359

FMVSNet2		98.49 147	98.40 143	98.75 175	98.90 246	97.14 217	98.61 108	99.13 228	98.59 124	99.19 126	99.28 104	94.14 278	99.82 172	97.97 130	99.80 110	99.29 219

FMVSNet1		99.17 44	99.17 46	99.17 104	99.55 93	98.24 122	99.20 45	99.44 117	99.21 63	99.43 80	99.55 52	97.82 112	99.86 115	98.42 103	99.89 71	99.41 171

N_pmnet		97.63 229	97.17 250	98.99 137	99.27 164	97.86 164	95.98 337	93.41 402	95.25 326	99.47 74	98.90 197	95.63 237	99.85 127	96.91 196	99.73 145	99.27 222

cascas		94.79 340	94.33 346	96.15 359	96.02 415	92.36 360	92.34 411	99.26 195	85.34 410	95.08 387	94.96 398	92.96 299	98.53 406	94.41 320	98.59 339	97.56 388

BH-RMVSNet		96.83 284	96.58 289	97.58 290	98.47 321	94.05 317	96.67 302	97.36 347	96.70 276	97.87 280	97.98 314	95.14 251	99.44 357	90.47 391	98.58 340	99.25 226

UGNet		98.53 142	98.45 136	98.79 166	97.94 356	96.96 224	99.08 58	98.54 309	99.10 83	96.82 345	99.47 69	96.55 197	99.84 145	98.56 97	99.94 38	99.55 109
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		96.67 290	96.27 300	97.87 264	98.81 265	94.61 303	96.77 296	97.92 335	94.94 333	97.12 325	97.74 328	91.11 321	99.82 172	93.89 333	98.15 356	99.18 243

XXY-MVS		99.14 49	99.15 53	99.10 116	99.76 29	97.74 178	98.85 87	99.62 51	98.48 135	99.37 93	99.49 67	98.75 36	99.86 115	98.20 113	99.80 110	99.71 49

EC-MVSNet		99.09 57	99.05 61	99.20 101	99.28 162	98.93 75	99.24 41	99.84 20	99.08 88	98.12 262	98.37 283	98.72 38	99.90 67	99.05 60	99.77 126	98.77 310

sss		97.21 262	96.93 262	98.06 254	98.83 260	95.22 284	96.75 298	98.48 313	94.49 341	97.27 322	97.90 320	92.77 303	99.80 193	96.57 230	99.32 259	99.16 250

Test_1112_low_res		96.99 279	96.55 290	98.31 235	99.35 151	95.47 274	95.84 350	99.53 83	91.51 385	96.80 346	98.48 273	91.36 319	99.83 162	96.58 228	99.53 225	99.62 70

1112_ss		97.29 256	96.86 268	98.58 197	99.34 153	96.32 248	96.75 298	99.58 58	93.14 366	96.89 341	97.48 343	92.11 312	99.86 115	96.91 196	99.54 221	99.57 96

ab-mvs-re		8.12 393	10.83 396	0.00 407	0.00 430	0.00 432	0.00 418	0.00 431	0.00 425	0.00 426	97.48 343	0.00 430	0.00 426	0.00 425	0.00 424	0.00 422

ab-mvs		98.41 154	98.36 150	98.59 196	99.19 185	97.23 207	99.32 23	98.81 285	97.66 194	98.62 213	99.40 83	96.82 181	99.80 193	95.88 272	99.51 230	98.75 313

TR-MVS		95.55 326	95.12 332	96.86 334	97.54 377	93.94 324	96.49 310	96.53 372	94.36 348	97.03 332	96.61 364	94.26 277	99.16 389	86.91 404	96.31 397	97.47 390

MDTV_nov1_ep13_2view						74.92 425	97.69 225		90.06 398	97.75 290		85.78 358		93.52 343		98.69 320

MDTV_nov1_ep13			95.22 329		97.06 397	83.20 418	97.74 220	96.16 375	94.37 347	96.99 333	98.83 213	83.95 374	99.53 332	93.90 332	97.95 367

MIMVSNet1		99.38 24	99.32 31	99.55 27	99.86 14	99.19 41	99.41 14	99.59 56	99.59 27	99.71 34	99.57 45	97.12 163	99.90 67	99.21 51	99.87 76	99.54 113

MIMVSNet		96.62 293	96.25 301	97.71 280	99.04 222	94.66 301	99.16 51	96.92 364	97.23 245	97.87 280	99.10 147	86.11 356	99.65 290	91.65 373	99.21 280	98.82 298

IterMVS-LS		98.55 138	98.70 98	98.09 249	99.48 122	94.73 298	97.22 272	99.39 135	98.97 100	99.38 91	99.31 100	96.00 220	99.93 43	98.58 92	99.97 19	99.60 79
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet		97.69 224	97.35 241	98.69 182	98.73 274	97.02 221	96.92 290	98.75 295	95.89 308	98.59 219	98.67 241	92.08 313	99.74 241	96.72 218	99.81 99	99.32 210
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref															99.77 126

IterMVS		97.73 221	98.11 182	96.57 341	99.24 171	90.28 389	95.52 361	99.21 205	98.86 109	99.33 100	99.33 95	93.11 294	99.94 36	98.49 99	99.94 38	99.48 144
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon		97.33 252	96.92 264	98.57 200	99.09 209	97.99 150	96.79 294	99.35 150	93.18 365	97.71 291	98.07 309	95.00 255	99.31 375	93.97 330	99.13 292	98.42 346

MVS_111021_LR		98.30 170	98.12 181	98.83 158	99.16 195	98.03 148	96.09 334	99.30 176	97.58 202	98.10 264	98.24 294	98.25 75	99.34 371	96.69 221	99.65 185	99.12 253

DP-MVS		98.93 75	98.81 84	99.28 87	99.21 178	98.45 108	98.46 131	99.33 161	99.63 21	99.48 70	99.15 138	97.23 158	99.75 236	97.17 174	99.66 184	99.63 69

ACMMP++															99.68 173

HQP-MVS		97.00 278	96.49 293	98.55 205	98.67 293	96.79 232	96.29 322	99.04 243	96.05 299	95.55 377	96.84 360	93.84 284	99.54 330	92.82 357	99.26 271	99.32 210

QAPM		97.31 253	96.81 274	98.82 159	98.80 268	97.49 192	99.06 62	99.19 211	90.22 395	97.69 293	99.16 134	96.91 175	99.90 67	90.89 388	99.41 247	99.07 257

Vis-MVSNet		99.34 26	99.36 25	99.27 90	99.73 36	98.26 120	99.17 50	99.78 29	99.11 76	99.27 112	99.48 68	98.82 31	99.95 24	98.94 68	99.93 43	99.59 85
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet		94.32 345	95.62 311	90.42 400	98.46 323	75.36 424	96.29 322	89.13 416	95.25 326	95.38 383	99.75 13	92.88 300	99.19 387	94.07 329	99.39 249	96.72 401

IS-MVSNet		98.19 184	97.90 204	99.08 120	99.57 81	97.97 154	99.31 27	98.32 320	99.01 96	98.98 154	99.03 162	91.59 317	99.79 206	95.49 291	99.80 110	99.48 144

HyFIR lowres test		97.19 264	96.60 288	98.96 141	99.62 75	97.28 204	95.17 371	99.50 89	94.21 350	99.01 151	98.32 290	86.61 350	99.99 2	97.10 182	99.84 85	99.60 79

EPMVS		93.72 357	93.27 356	95.09 379	96.04 414	87.76 401	98.13 161	85.01 421	94.69 338	96.92 335	98.64 249	78.47 399	99.31 375	95.04 298	96.46 395	98.20 357

PAPM_NR		96.82 286	96.32 297	98.30 236	99.07 213	96.69 239	97.48 251	98.76 292	95.81 310	96.61 353	96.47 368	94.12 281	99.17 388	90.82 389	97.78 368	99.06 258

TAMVS		98.24 179	98.05 188	98.80 163	99.07 213	97.18 213	97.88 200	98.81 285	96.66 277	99.17 131	99.21 121	94.81 262	99.77 223	96.96 194	99.88 73	99.44 161

PAPR		95.29 330	94.47 341	97.75 275	97.50 385	95.14 287	94.89 379	98.71 300	91.39 387	95.35 384	95.48 388	94.57 268	99.14 391	84.95 407	97.37 380	98.97 276

RPSCF		98.62 128	98.36 150	99.42 60	99.65 63	99.42 11	98.55 114	99.57 65	97.72 191	98.90 173	99.26 110	96.12 215	99.52 336	95.72 282	99.71 158	99.32 210

Vis-MVSNet (Re-imp)		97.46 240	97.16 251	98.34 232	99.55 93	96.10 252	98.94 77	98.44 314	98.32 143	98.16 257	98.62 253	88.76 337	99.73 246	93.88 334	99.79 115	99.18 243

test_0402		98.76 99	98.71 95	98.93 146	99.56 89	98.14 132	98.45 133	99.34 156	99.28 57	98.95 162	98.91 194	98.34 69	99.79 206	95.63 286	99.91 61	98.86 295

MVS_111021_HR		98.25 178	98.08 186	98.75 175	99.09 209	97.46 194	95.97 338	99.27 190	97.60 201	97.99 273	98.25 293	98.15 90	99.38 366	96.87 204	99.57 213	99.42 168

CSCG		98.68 116	98.50 126	99.20 101	99.45 128	98.63 91	98.56 113	99.57 65	97.87 181	98.85 183	98.04 311	97.66 122	99.84 145	96.72 218	99.81 99	99.13 252

PatchMatch-RL		97.24 260	96.78 275	98.61 193	99.03 225	97.83 167	96.36 317	99.06 237	93.49 363	97.36 320	97.78 325	95.75 234	99.49 345	93.44 346	98.77 323	98.52 334

API-MVS		97.04 274	96.91 266	97.42 306	97.88 359	98.23 126	98.18 155	98.50 312	97.57 203	97.39 318	96.75 362	96.77 185	99.15 390	90.16 392	99.02 305	94.88 413

Test By Simon												96.52 198

TDRefinement		99.42 20	99.38 24	99.55 27	99.76 29	99.33 20	99.68 6	99.71 36	99.38 45	99.53 61	99.61 39	98.64 44	99.80 193	98.24 110	99.84 85	99.52 124

USDC		97.41 246	97.40 236	97.44 305	98.94 236	93.67 336	95.17 371	99.53 83	94.03 355	98.97 158	99.10 147	95.29 247	99.34 371	95.84 278	99.73 145	99.30 217

EPP-MVSNet		98.30 170	98.04 189	99.07 122	99.56 89	97.83 167	99.29 33	98.07 331	99.03 94	98.59 219	99.13 142	92.16 311	99.90 67	96.87 204	99.68 173	99.49 134

PMMVS		96.51 295	95.98 302	98.09 249	97.53 379	95.84 262	94.92 378	98.84 280	91.58 383	96.05 369	95.58 383	95.68 236	99.66 285	95.59 288	98.09 359	98.76 312

PAPM		91.88 382	90.34 385	96.51 342	98.06 352	92.56 354	92.44 410	97.17 354	86.35 407	90.38 414	96.01 374	86.61 350	99.21 386	70.65 420	95.43 405	97.75 380

ACMMP		98.75 100	98.50 126	99.52 42	99.56 89	99.16 47	98.87 84	99.37 141	97.16 251	98.82 189	99.01 172	97.71 119	99.87 107	96.29 254	99.69 168	99.54 113
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		97.17 266	96.71 279	98.55 205	98.56 313	98.05 147	96.33 319	98.93 259	96.91 264	97.06 329	97.39 348	94.38 273	99.45 355	91.66 372	99.18 286	98.14 360

PatchmatchNet		95.58 325	95.67 310	95.30 376	97.34 389	87.32 403	97.65 232	96.65 368	95.30 325	97.07 328	98.69 237	84.77 365	99.75 236	94.97 301	98.64 335	98.83 297
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS		98.29 173	97.95 198	99.34 75	98.44 326	99.16 47	98.12 164	99.38 137	96.01 303	98.06 267	98.43 277	97.80 114	99.67 274	95.69 284	99.58 209	99.20 236

F-COLMAP		97.30 254	96.68 281	99.14 110	99.19 185	98.39 110	97.27 268	99.30 176	92.93 369	96.62 352	98.00 312	95.73 235	99.68 271	92.62 363	98.46 343	99.35 201

ANet_high		99.57 7	99.67 5	99.28 87	99.89 6	98.09 137	99.14 54	99.93 5	99.82 5	99.93 6	99.81 6	99.17 18	99.94 36	99.31 42	100.00 1	99.82 27

wuyk23d		96.06 309	97.62 225	91.38 399	98.65 302	98.57 98	98.85 87	96.95 362	96.86 267	99.90 12	99.16 134	99.18 17	98.40 407	89.23 396	99.77 126	77.18 419

OMC-MVS		97.88 207	97.49 232	99.04 131	98.89 251	98.63 91	96.94 286	99.25 196	95.02 330	98.53 229	98.51 266	97.27 155	99.47 351	93.50 345	99.51 230	99.01 267

MG-MVS		96.77 287	96.61 286	97.26 313	98.31 336	93.06 344	95.93 343	98.12 330	96.45 286	97.92 275	98.73 230	93.77 288	99.39 364	91.19 383	99.04 301	99.33 208

AdaColmap		97.14 268	96.71 279	98.46 218	98.34 334	97.80 174	96.95 285	98.93 259	95.58 316	96.92 335	97.66 332	95.87 231	99.53 332	90.97 385	99.14 290	98.04 365

uanet		0.00 394	0.00 397	0.00 407	0.00 430	0.00 432	0.00 418	0.00 431	0.00 425	0.00 426	0.00 425	0.00 430	0.00 426	0.00 425	0.00 424	0.00 422

ITE_SJBPF				98.87 154	99.22 176	98.48 106		99.35 150	97.50 211	98.28 249	98.60 257	97.64 126	99.35 370	93.86 335	99.27 268	98.79 308

DeepMVS_CX				93.44 395	98.24 340	94.21 312		94.34 394	64.28 419	91.34 413	94.87 401	89.45 335	92.77 420	77.54 418	93.14 413	93.35 415

TinyColmap		97.89 205	97.98 195	97.60 288	98.86 254	94.35 309	96.21 326	99.44 117	97.45 221	99.06 140	98.88 204	97.99 102	99.28 381	94.38 321	99.58 209	99.18 243

MAR-MVS		96.47 299	95.70 308	98.79 166	97.92 357	99.12 61	98.28 146	98.60 307	92.16 379	95.54 380	96.17 373	94.77 265	99.52 336	89.62 394	98.23 349	97.72 382
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		97.90 203	97.69 217	98.52 210	99.17 193	97.66 183	97.19 276	99.47 106	96.31 291	97.85 283	98.20 298	96.71 191	99.52 336	94.62 309	99.72 153	98.38 349

MSDG		97.71 223	97.52 230	98.28 238	98.91 245	96.82 230	94.42 392	99.37 141	97.65 195	98.37 244	98.29 292	97.40 148	99.33 373	94.09 328	99.22 277	98.68 323

LS3D		98.63 125	98.38 148	99.36 66	97.25 391	99.38 12	99.12 57	99.32 163	99.21 63	98.44 236	98.88 204	97.31 151	99.80 193	96.58 228	99.34 257	98.92 285

CLD-MVS		97.49 238	97.16 251	98.48 216	99.07 213	97.03 220	94.71 382	99.21 205	94.46 343	98.06 267	97.16 355	97.57 132	99.48 348	94.46 314	99.78 120	98.95 279
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS		93.44 361	92.23 367	97.08 320	99.25 170	97.86 164	95.61 356	97.16 355	92.90 370	93.76 404	98.65 246	75.94 401	95.66 417	79.30 417	97.49 373	97.73 381

Gipuma		99.03 63	99.16 48	98.64 185	99.94 2	98.51 104	99.32 23	99.75 34	99.58 29	98.60 217	99.62 36	98.22 80	99.51 341	97.70 148	99.73 145	97.89 371
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015

High-resolution multi-view benchmark