High-res multi-view results

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

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

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

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

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

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

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

DeepPCF-MVS	89.96 1	94.20 26	94.77 10	92.49 93	96.52 70	80.00 179	94.00 176	97.08 31	90.05 26	95.65 9	97.29 13	89.66 3	98.97 61	93.95 10	98.71 19	98.50 11

DeepC-MVS_fast	89.43 2	94.04 27	93.79 30	94.80 23	97.48 43	86.78 19	95.65 56	96.89 44	89.40 38	92.81 42	96.97 28	85.37 38	99.24 31	90.87 60	98.69 21	98.38 22
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepC-MVS	88.79 3	93.31 43	92.99 45	94.26 43	96.07 90	85.83 49	94.89 98	96.99 34	89.02 49	89.56 93	97.37 11	82.51 61	99.38 22	92.20 32	98.30 41	97.57 72
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
3Dnovator+	87.14 4	92.42 58	91.37 62	95.55 3	95.63 105	88.73 2	97.07 8	96.77 54	90.84 17	84.02 222	96.62 44	75.95 138	99.34 23	87.77 89	97.68 55	98.59 9

3Dnovator	86.66 5	91.73 65	90.82 75	94.44 36	94.59 150	86.37 33	97.18 6	97.02 33	89.20 42	84.31 218	96.66 42	73.74 173	99.17 35	86.74 104	97.96 50	97.79 65

TAPA-MVS	84.62 6	88.16 146	87.01 157	91.62 129	96.64 64	80.65 163	94.39 137	96.21 92	76.38 283	86.19 154	95.44 83	79.75 92	98.08 130	62.75 328	95.29 94	96.13 117
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
PLC	84.53 7	89.06 125	88.03 131	92.15 107	97.27 52	82.69 118	94.29 146	95.44 155	79.71 253	84.01 223	94.18 124	76.68 122	98.75 79	77.28 231	93.41 126	95.02 153
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
ACMP	84.23 8	89.01 128	88.35 122	90.99 153	94.73 142	81.27 144	95.07 86	95.89 116	86.48 108	83.67 230	94.30 118	69.33 228	97.99 136	87.10 103	88.55 199	93.72 231
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
ACMM	84.12 9	89.14 122	88.48 121	91.12 142	94.65 149	81.22 147	95.31 64	96.12 97	85.31 132	85.92 157	94.34 115	70.19 220	98.06 132	85.65 113	88.86 197	94.08 207
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PCF-MVS	84.11 10	87.74 164	86.08 194	92.70 85	94.02 168	84.43 72	89.27 293	95.87 117	73.62 309	84.43 212	94.33 116	78.48 108	98.86 70	70.27 277	94.45 108	94.81 170
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
OpenMVS	83.78 11	88.74 133	87.29 145	93.08 70	92.70 212	85.39 53	96.57 22	96.43 76	78.74 264	80.85 268	96.07 67	69.64 225	99.01 55	78.01 225	96.65 72	94.83 169

HY-MVS	83.01 12	89.03 126	87.94 134	92.29 103	94.86 139	82.77 111	92.08 255	94.49 202	81.52 236	86.93 138	92.79 177	78.32 110	98.23 107	79.93 199	90.55 163	95.88 129

LTVRE_ROB	82.13 13	86.26 215	84.90 223	90.34 182	94.44 157	81.50 136	92.31 247	94.89 190	83.03 192	79.63 283	92.67 178	69.69 224	97.79 144	71.20 273	86.26 225	91.72 295
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
ACMH+	81.04 14	85.05 244	83.46 256	89.82 208	94.66 147	79.37 204	94.44 132	94.12 215	82.19 211	78.04 291	92.82 174	58.23 317	97.54 157	73.77 262	82.90 255	92.54 276

IB-MVS	80.51 15	85.24 241	83.26 260	91.19 140	92.13 221	79.86 182	91.75 258	91.29 285	83.28 182	80.66 271	88.49 290	61.28 301	98.46 94	80.99 179	79.46 305	95.25 149
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
COLMAP_ROB	80.39 16	83.96 265	82.04 271	89.74 212	95.28 118	79.75 185	94.25 148	92.28 253	75.17 295	78.02 292	93.77 143	58.60 316	97.84 143	65.06 321	85.92 226	91.63 297
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ACMH	80.38 17	85.36 237	83.68 249	90.39 177	94.45 156	80.63 164	94.73 110	94.85 192	82.09 212	77.24 298	92.65 179	60.01 311	97.58 154	72.25 269	84.87 236	92.96 265
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PVSNet	78.82 18	85.55 235	84.65 229	88.23 268	94.72 143	71.93 311	87.12 316	92.75 245	78.80 262	84.95 196	90.53 260	64.43 286	96.71 239	74.74 254	93.86 116	96.06 123

OpenMVS_ROB	74.94 19	79.51 304	77.03 308	86.93 294	87.00 331	76.23 280	92.33 246	90.74 302	68.93 335	74.52 320	88.23 295	49.58 338	96.62 242	57.64 338	84.29 240	87.94 341

PVSNet_0	73.20 20	77.22 310	74.83 313	84.37 317	90.70 287	71.10 318	83.09 341	89.67 321	72.81 318	73.93 323	83.13 332	60.79 306	93.70 319	68.54 295	50.84 353	88.30 340

CMPMVS	59.16 21	80.52 298	79.20 296	84.48 316	83.98 340	67.63 335	89.95 284	93.84 229	64.79 345	66.81 342	91.14 245	57.93 319	95.17 303	76.25 241	88.10 208	90.65 318
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
PMVS	47.18 22	52.22 333	48.46 335	63.48 345	45.72 368	46.20 360	73.41 354	78.31 360	41.03 358	30.06 361	65.68 353	6.05 368	83.43 355	30.04 359	65.86 343	60.80 356
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVE	39.65 23	43.39 336	38.59 342	57.77 347	56.52 366	48.77 358	55.38 360	58.64 367	29.33 362	28.96 362	52.65 358	4.68 369	64.62 363	28.11 360	33.07 355	59.93 357
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
0601test		90.69 83	90.02 90	92.71 84	95.72 101	82.41 124	94.11 161	95.12 177	85.63 125	91.49 72	94.70 105	74.75 156	98.42 97	86.13 111	92.53 141	97.31 79

Anonymous20240529		88.09 149	86.59 180	92.58 89	96.53 69	81.92 131	95.99 38	95.84 119	74.11 305	89.06 101	95.21 91	61.44 300	98.81 76	83.67 139	87.47 214	97.01 94

Anonymous202405211		87.68 165	86.13 190	92.31 101	96.66 63	80.74 162	94.87 101	91.49 280	80.47 245	89.46 96	95.44 83	54.72 328	98.23 107	82.19 160	89.89 174	97.97 53

Anonymous20240521		86.87 200	85.95 199	89.64 218	92.89 209	78.88 221	95.66 53	96.05 103	84.77 144	81.92 256	92.39 185	71.54 198	96.96 221	76.46 238	81.87 270	93.08 263

tttt0517		88.61 135	87.78 136	91.11 145	94.96 134	77.81 255	95.35 62	89.69 320	85.09 138	88.05 116	94.59 111	66.93 266	98.48 92	83.27 142	92.13 145	97.03 93

our_test_3		81.93 282	80.46 282	86.33 303	88.46 320	73.48 297	88.46 305	91.11 286	76.46 281	76.69 300	88.25 294	66.89 267	94.36 313	68.75 294	79.08 306	91.14 306

thisisatest0515		87.33 187	85.99 196	91.37 136	93.49 188	79.55 187	90.63 274	89.56 324	80.17 247	87.56 130	90.86 250	67.07 265	98.28 106	81.50 172	93.02 135	96.29 111

ppachtmachnet_test		81.84 283	80.07 288	87.15 292	88.46 320	74.43 288	89.04 298	92.16 256	75.33 293	77.75 294	88.99 280	66.20 275	95.37 296	65.12 320	77.60 311	91.65 296

SMA-MVS		95.20 5	95.07 7	95.59 2	98.14 26	88.48 4	96.26 28	97.28 20	85.90 118	97.67 1	98.10 1	88.41 10	99.56 2	94.66 4	99.19 1	98.71 5

tfpn111		87.63 171	86.68 171	90.47 173	96.12 83	78.55 227	95.03 89	91.58 273	87.15 89	88.06 113	92.29 190	68.91 236	98.15 115	69.88 286	91.10 150	94.71 173

conf0.01		85.83 225	84.54 231	89.71 214	95.26 120	77.63 262	94.21 151	89.33 325	81.89 221	84.94 197	91.51 225	68.43 252	96.80 231	66.05 310	89.23 186	94.71 173

GSMVS																96.12 118

ESAPD		95.57 1	95.67 1	95.25 6	98.36 18	87.28 11	95.56 59	97.51 4	89.13 45	97.14 2	97.91 3	91.64 1	99.62 1	94.61 5	99.17 2	98.86 2

conf0.002		85.83 225	84.54 231	89.71 214	95.26 120	77.63 262	94.21 151	89.33 325	81.89 221	84.94 197	91.51 225	68.43 252	96.80 231	66.05 310	89.23 186	94.71 173

thresconf0.02		85.75 229	84.54 231	89.38 230	95.26 120	77.63 262	94.21 151	89.33 325	81.89 221	84.94 197	91.51 225	68.43 252	96.80 231	66.05 310	89.23 186	93.70 232

tfpn_n400		85.75 229	84.54 231	89.38 230	95.26 120	77.63 262	94.21 151	89.33 325	81.89 221	84.94 197	91.51 225	68.43 252	96.80 231	66.05 310	89.23 186	93.70 232

tfpnconf		85.75 229	84.54 231	89.38 230	95.26 120	77.63 262	94.21 151	89.33 325	81.89 221	84.94 197	91.51 225	68.43 252	96.80 231	66.05 310	89.23 186	93.70 232

tfpnview11		85.75 229	84.54 231	89.38 230	95.26 120	77.63 262	94.21 151	89.33 325	81.89 221	84.94 197	91.51 225	68.43 252	96.80 231	66.05 310	89.23 186	93.70 232

tfpn1000		86.06 218	84.92 222	89.49 225	95.54 107	77.79 256	94.72 113	89.07 332	82.05 213	85.36 190	91.94 207	68.32 259	96.65 240	67.04 304	90.24 168	94.02 211

test_part2					98.55 5	87.22 12				96.40 4

tfpn_ndepth		86.10 217	84.98 218	89.43 227	95.52 110	78.29 242	94.62 120	89.60 323	81.88 228	85.43 182	90.54 258	68.47 250	96.85 230	68.46 297	90.34 167	93.15 260

test_part1				0.00 357		0.00 372	0.00 363	97.45 7				0.00 374	0.00 369	0.00 366	0.00 367	0.00 367

conf200view11		87.65 167	86.71 168	90.46 175	96.12 83	78.55 227	95.03 89	91.58 273	87.15 89	88.06 113	92.29 190	68.91 236	98.10 122	70.13 281	91.10 150	94.71 173

thres100view900		87.63 171	86.71 168	90.38 179	96.12 83	78.55 227	95.03 89	91.58 273	87.15 89	88.06 113	92.29 190	68.91 236	98.10 122	70.13 281	91.10 150	94.48 192

tfpnnormal		84.72 257	83.23 261	89.20 238	92.79 211	80.05 176	94.48 127	95.81 121	82.38 208	81.08 266	91.21 240	69.01 235	96.95 223	61.69 330	80.59 291	90.58 322

tfpn200view9		87.58 180	86.64 177	90.41 176	95.99 93	78.64 224	94.58 122	91.98 264	86.94 101	88.09 110	91.77 211	69.18 233	98.10 122	70.13 281	91.10 150	94.48 192

view600		87.62 174	86.65 173	90.53 163	96.19 78	78.52 231	95.29 68	91.09 287	87.08 94	87.84 120	93.03 165	68.86 240	98.11 118	69.44 288	91.02 158	94.96 158

view800		87.62 174	86.65 173	90.53 163	96.19 78	78.52 231	95.29 68	91.09 287	87.08 94	87.84 120	93.03 165	68.86 240	98.11 118	69.44 288	91.02 158	94.96 158

conf0.05thres1000		87.62 174	86.65 173	90.53 163	96.19 78	78.52 231	95.29 68	91.09 287	87.08 94	87.84 120	93.03 165	68.86 240	98.11 118	69.44 288	91.02 158	94.96 158

tfpn		87.62 174	86.65 173	90.53 163	96.19 78	78.52 231	95.29 68	91.09 287	87.08 94	87.84 120	93.03 165	68.86 240	98.11 118	69.44 288	91.02 158	94.96 158

v1.0		39.85 339	53.14 334	0.00 357	98.55 5	0.00 372	0.00 363	97.45 7	88.25 67	96.40 4	97.60 6	0.00 374	0.00 369	0.00 366	0.00 367	0.00 367

CHOSEN 280x420		85.15 242	83.99 241	88.65 248	92.47 215	78.40 239	79.68 348	92.76 244	74.90 299	81.41 262	89.59 274	69.85 223	95.51 287	79.92 200	95.29 94	92.03 289

CANet		93.54 38	93.20 41	94.55 33	95.65 104	85.73 51	94.94 95	96.69 62	91.89 5	90.69 82	95.88 73	81.99 73	99.54 10	93.14 20	97.95 51	98.39 21

Fast-Effi-MVS+-dtu		87.44 184	86.72 167	89.63 219	92.04 223	77.68 261	94.03 173	93.94 225	85.81 119	82.42 246	91.32 235	70.33 218	97.06 214	80.33 192	90.23 169	94.14 202

Effi-MVS+-dtu		88.65 134	88.35 122	89.54 221	93.33 193	76.39 277	94.47 130	94.36 206	87.70 80	85.43 182	89.56 276	73.45 176	97.26 198	85.57 114	91.28 149	94.97 155

CANet_DTU		90.26 94	89.41 98	92.81 80	93.46 190	83.01 106	93.48 203	94.47 203	89.43 37	87.76 127	94.23 123	70.54 216	99.03 50	84.97 118	96.39 78	96.38 109

MVS_0304		93.25 47	92.62 51	95.14 9	95.72 101	87.58 8	94.71 115	96.59 69	91.78 7	91.46 73	96.18 64	75.45 149	99.55 7	93.53 12	98.19 44	98.28 28

MP-MVS-pluss		94.21 25	94.00 27	94.85 17	98.17 25	86.65 25	94.82 104	97.17 26	86.26 113	92.83 41	97.87 4	85.57 36	99.56 2	94.37 8	98.92 6	98.34 23
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
HSP-MVS		95.30 4	95.48 3	94.76 25	98.49 10	86.52 29	96.91 15	96.73 56	91.73 9	96.10 7	96.69 39	89.90 2	99.30 29	94.70 3	98.04 49	98.45 18

sam_mvs1												71.70 195				96.12 118

sam_mvs												70.60 211

semantic-postprocess				88.18 269	91.71 231	76.87 274		92.65 248	85.40 130	81.44 261	90.54 258	66.21 274	95.00 308	81.04 176	81.05 282	92.66 274

TSAR-MVS + MP.		94.85 9	94.94 8	94.58 32	98.25 22	86.33 35	96.11 34	96.62 67	88.14 70	96.10 7	96.96 29	89.09 8	98.94 65	94.48 6	98.68 24	98.48 13

xiu_mvs_v1_base_debu		90.64 85	90.05 87	92.40 96	93.97 174	84.46 68	93.32 207	95.46 149	85.17 133	92.25 56	94.03 125	70.59 212	98.57 88	90.97 56	94.67 99	94.18 199

OPM-MVS		90.12 95	89.56 94	91.82 122	93.14 198	83.90 80	94.16 158	95.74 127	88.96 50	87.86 118	95.43 85	72.48 190	97.91 141	88.10 86	90.18 170	93.65 237

ACMMP_Plus		94.74 11	94.56 12	95.28 5	98.02 32	87.70 5	95.68 51	97.34 12	88.28 66	95.30 12	97.67 5	85.90 33	99.54 10	93.91 11	98.95 4	98.60 8

ambc				83.06 322	79.99 348	63.51 342	77.47 351	92.86 241		74.34 322	84.45 326	28.74 355	95.06 307	73.06 266	68.89 341	90.61 319

zzz-MVS		94.47 13	94.30 15	95.00 10	98.42 14	86.95 13	95.06 88	96.97 36	91.07 14	93.14 37	97.56 7	84.30 49	99.56 2	93.43 15	98.75 16	98.47 14

MTGPA								96.97 36

mvs-test1		89.45 113	89.14 104	90.38 179	93.33 193	77.63 262	94.95 94	94.36 206	87.70 80	87.10 136	92.81 175	73.45 176	98.03 134	85.57 114	93.04 134	95.48 142

Effi-MVS+		91.59 69	91.11 68	93.01 74	94.35 161	83.39 95	94.60 121	95.10 178	87.10 93	90.57 83	93.10 162	81.43 78	98.07 131	89.29 72	94.48 106	97.59 71

xiu_mvs_v2_base		91.13 77	90.89 74	91.86 119	94.97 133	82.42 122	92.24 248	95.64 135	86.11 117	91.74 70	93.14 160	79.67 97	98.89 66	89.06 74	95.46 90	94.28 198

xiu_mvs_v1_base		90.64 85	90.05 87	92.40 96	93.97 174	84.46 68	93.32 207	95.46 149	85.17 133	92.25 56	94.03 125	70.59 212	98.57 88	90.97 56	94.67 99	94.18 199

new-patchmatchnet		76.41 312	75.17 312	80.13 326	82.65 345	59.61 346	87.66 313	91.08 291	78.23 271	69.85 336	83.22 331	54.76 327	91.63 337	64.14 324	64.89 345	89.16 330

pmmvs6		83.42 270	81.60 273	88.87 243	88.01 327	77.87 253	94.96 93	94.24 210	74.67 301	78.80 287	91.09 247	60.17 310	96.49 249	77.06 236	75.40 318	92.23 287

pmmvs5		84.21 263	82.84 267	88.34 264	88.95 315	76.94 273	92.41 243	91.91 268	75.63 291	80.28 275	91.18 242	64.59 285	95.57 284	77.09 235	83.47 250	92.53 277

test_post1							88.00 309				9.81 365	69.31 230	95.53 285	76.65 237

test_post											10.29 364	70.57 215	95.91 274

Fast-Effi-MVS+		89.41 116	88.64 115	91.71 126	94.74 141	80.81 160	93.54 201	95.10 178	83.11 185	86.82 142	90.67 254	79.74 93	97.75 149	80.51 188	93.55 121	96.57 106

patchmatchnet-post											83.76 329	71.53 199	96.48 250

Anonymous20231211		86.59 209	85.13 215	90.98 155	96.52 70	81.50 136	96.14 32	96.16 93	73.78 307	83.65 231	92.15 195	63.26 290	97.37 189	82.82 149	81.74 274	94.06 208

pmmvs-eth3d		80.97 296	78.72 301	87.74 275	84.99 338	79.97 180	90.11 281	91.65 272	75.36 292	73.51 324	86.03 321	59.45 313	93.96 317	75.17 250	72.21 324	89.29 328

GG-mvs-BLEND				87.94 274	89.73 309	77.91 250	87.80 310	78.23 361		80.58 272	83.86 328	59.88 312	95.33 302	71.20 273	92.22 144	90.60 321

xiu_mvs_v1_base_debi		90.64 85	90.05 87	92.40 96	93.97 174	84.46 68	93.32 207	95.46 149	85.17 133	92.25 56	94.03 125	70.59 212	98.57 88	90.97 56	94.67 99	94.18 199

Anonymous20231206		81.03 295	79.77 291	84.82 314	87.85 330	70.26 325	91.42 266	92.08 259	73.67 308	77.75 294	89.25 278	62.43 294	93.08 327	61.50 331	82.00 266	91.12 307

MTAPA		94.42 18	94.22 18	95.00 10	98.42 14	86.95 13	94.36 145	96.97 36	91.07 14	93.14 37	97.56 7	84.30 49	99.56 2	93.43 15	98.75 16	98.47 14

MTMP							96.16 31	60.64 366

gm-plane-assit					89.60 310	68.00 332			77.28 278		88.99 280		97.57 155	79.44 210

test9_res														91.91 43	98.71 19	98.07 46

MVP-Stereo		85.97 221	84.86 224	89.32 234	90.92 278	82.19 126	92.11 253	94.19 211	78.76 263	78.77 288	91.63 217	68.38 258	96.56 245	75.01 253	93.95 114	89.20 329
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST9					97.53 38	86.49 30	94.07 168	96.78 52	81.61 234	92.77 43	96.20 60	87.71 15	99.12 41

train_agg		93.44 40	93.08 42	94.52 34	97.53 38	86.49 30	94.07 168	96.78 52	81.86 229	92.77 43	96.20 60	87.63 16	99.12 41	92.14 36	98.69 21	97.94 55

gg-mvs-nofinetune		81.77 284	79.37 294	88.99 242	90.85 282	77.73 260	86.29 320	79.63 359	74.88 300	83.19 240	69.05 351	60.34 308	96.11 265	75.46 247	94.64 102	93.11 261

Patchmatch-test1		85.81 227	84.71 227	89.12 239	92.15 219	76.60 275	91.12 272	91.69 271	83.53 174	85.50 176	88.56 289	66.79 268	95.00 308	72.69 267	90.35 166	95.76 135

Patchmatch-test		81.37 291	79.30 295	87.58 279	90.92 278	74.16 291	80.99 345	87.68 342	70.52 331	76.63 301	88.81 283	71.21 202	92.76 329	60.01 336	86.93 223	95.83 132

test_8					97.49 41	86.30 38	94.02 174	96.76 55	81.86 229	92.70 47	96.20 60	87.63 16	99.02 53

MS-PatchMatch		85.05 244	84.16 238	87.73 276	91.42 242	78.51 235	91.25 270	93.53 232	77.50 274	80.15 277	91.58 219	61.99 296	95.51 287	75.69 245	94.35 111	89.16 330

Patchmatch-RL test		81.67 285	79.96 289	86.81 299	85.42 335	71.23 316	82.17 343	87.50 344	78.47 266	77.19 299	82.50 334	70.81 209	93.48 321	82.66 151	72.89 323	95.71 137

agg_prior3		93.27 45	92.89 48	94.40 40	97.49 41	86.12 42	94.07 168	96.73 56	81.46 237	92.46 55	96.05 68	86.90 23	99.15 38	92.14 36	98.69 21	97.94 55

cdsmvs_eth3d_5k		22.14 342	29.52 343	0.00 357	0.00 372	0.00 372	0.00 363	95.76 125	0.00 367	0.00 369	94.29 119	75.66 145	0.00 369	0.00 366	0.00 367	0.00 367

pcd_1.5k_mvsjas		6.64 347	8.86 348	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	79.70 94	0.00 369	0.00 366	0.00 367	0.00 367

pcd1.5k->3k		37.02 340	38.84 341	31.53 352	92.33 217	0.00 372	0.00 363	96.13 96	0.00 367	0.00 369	0.00 369	72.70 185	0.00 369	0.00 366	88.43 204	94.60 181

agg_prior1		93.29 44	92.97 46	94.26 43	97.38 45	85.92 45	93.92 179	96.72 58	81.96 216	92.16 59	96.23 58	87.85 12	98.97 61	91.95 42	98.55 37	97.90 60

agg_prior2														90.54 63	98.68 24	98.27 31

agg_prior					97.38 45	85.92 45		96.72 58		92.16 59			98.97 61

tmp_tt		35.64 341	39.24 340	24.84 353	14.87 369	23.90 369	62.71 359	51.51 369	6.58 364	36.66 359	62.08 356	44.37 347	30.34 366	52.40 341	22.00 362	20.27 362

canonicalmvs		93.27 45	92.75 50	94.85 17	95.70 103	87.66 6	96.33 25	96.41 77	90.00 28	94.09 19	94.60 110	82.33 63	98.62 85	92.40 28	92.86 138	98.27 31

anonymousdsp		87.84 158	87.09 152	90.12 192	89.13 312	80.54 167	94.67 118	95.55 139	82.05 213	83.82 226	92.12 197	71.47 201	97.15 206	87.15 99	87.80 213	92.67 273

alignmvs		93.08 51	92.50 54	94.81 22	95.62 106	87.61 7	95.99 38	96.07 100	89.77 32	94.12 18	94.87 99	80.56 83	98.66 81	92.42 27	93.10 133	98.15 40

nrg030		91.08 78	90.39 78	93.17 65	93.07 200	86.91 15	96.41 24	96.26 85	88.30 65	88.37 108	94.85 102	82.19 67	97.64 153	91.09 55	82.95 254	94.96 158

v144192		87.19 195	86.35 184	89.74 212	90.64 289	78.24 244	93.92 179	95.43 156	81.93 218	85.51 175	91.05 248	74.21 164	97.45 166	82.86 147	81.56 278	93.53 246

FIs		90.51 89	90.35 79	90.99 153	93.99 173	80.98 154	95.73 48	97.54 3	89.15 44	86.72 143	94.68 106	81.83 75	97.24 200	85.18 116	88.31 207	94.76 172

v1921920		86.97 199	86.06 195	89.69 217	90.53 294	78.11 247	93.80 185	95.43 156	81.90 220	85.33 191	91.05 248	72.66 186	97.41 182	82.05 163	81.80 272	93.53 246

UA-Net		92.83 53	92.54 53	93.68 57	96.10 88	84.71 60	95.66 53	96.39 80	91.92 4	93.22 34	96.49 50	83.16 56	98.87 67	84.47 126	95.47 89	97.45 76

v1192		87.25 191	86.33 185	90.00 204	90.76 284	79.04 218	93.80 185	95.48 148	82.57 206	85.48 177	91.18 242	73.38 179	97.42 177	82.30 158	82.06 263	93.53 246

FC-MVSNet-test		90.27 93	90.18 84	90.53 163	93.71 183	79.85 183	95.77 47	97.59 2	89.31 40	86.27 152	94.67 107	81.93 74	97.01 217	84.26 131	88.09 210	94.71 173

v1144		87.61 179	86.79 165	90.06 200	91.01 271	79.34 206	93.95 178	95.42 158	83.36 180	85.66 169	91.31 236	74.98 155	97.42 177	83.37 141	82.06 263	93.42 251

sosnet-low-res		0.00 348	0.00 349	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	0.00 374	0.00 369	0.00 366	0.00 367	0.00 367

HFP-MVS		94.52 12	94.40 13	94.86 15	98.61 3	86.81 17	96.94 10	97.34 12	88.63 57	93.65 25	97.21 19	86.10 29	99.49 16	92.35 29	98.77 14	98.30 26

v148		87.04 198	86.32 186	89.21 237	90.94 276	77.26 270	93.71 194	94.43 204	84.84 142	84.36 216	90.80 252	76.04 133	97.05 215	82.12 161	79.60 304	93.31 253

sosnet		0.00 348	0.00 349	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	0.00 374	0.00 369	0.00 366	0.00 367	0.00 367

v748		86.27 214	85.28 213	89.25 236	90.26 298	77.58 269	94.89 98	95.50 146	84.28 157	81.41 262	90.46 262	72.57 189	97.32 191	79.81 204	78.36 308	92.84 269

uncertanet		0.00 348	0.00 349	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	0.00 374	0.00 369	0.00 366	0.00 367	0.00 367

AllTest		83.42 270	81.39 274	89.52 222	95.01 130	77.79 256	93.12 218	90.89 298	77.41 275	76.12 309	93.34 148	54.08 331	97.51 160	68.31 299	84.27 241	93.26 254

TestCases				89.52 222	95.01 130	77.79 256		90.89 298	77.41 275	76.12 309	93.34 148	54.08 331	97.51 160	68.31 299	84.27 241	93.26 254

v7n		86.81 201	85.76 203	89.95 205	90.72 286	79.25 212	95.07 86	95.92 111	84.45 153	82.29 247	90.86 250	72.60 188	97.53 158	79.42 212	80.52 294	93.08 263

v1141		87.84 158	87.09 152	90.11 197	91.23 260	79.25 212	94.08 166	95.24 169	84.44 154	85.69 167	91.31 236	75.91 139	97.44 173	84.17 133	81.74 274	93.63 240

region2R		94.43 16	94.27 17	94.92 12	98.65 1	86.67 24	96.92 14	97.23 23	88.60 59	93.58 29	97.27 14	85.22 39	99.54 10	92.21 31	98.74 18	98.56 10

testing_2		83.40 272	81.02 277	90.56 162	85.06 337	80.51 168	91.37 267	95.57 137	82.92 198	67.06 341	85.54 324	49.47 339	97.24 200	86.74 104	85.44 230	93.93 213

test_normal		88.13 148	86.78 166	92.18 106	90.55 293	81.19 149	92.74 234	94.64 199	83.84 163	77.49 297	90.51 261	68.49 249	98.16 113	88.22 82	94.55 104	97.21 84

v1neww		87.98 152	87.25 148	90.16 186	91.38 245	79.41 198	94.37 141	95.28 164	84.48 150	85.77 160	91.53 223	76.12 127	97.45 166	84.45 128	81.89 267	93.61 242

PS-MVSNAJss		89.97 99	89.62 93	91.02 150	91.90 224	80.85 159	95.26 75	95.98 107	86.26 113	86.21 153	94.29 119	79.70 94	97.65 151	88.87 76	88.10 208	94.57 184

PS-MVSNAJ		91.18 76	90.92 72	91.96 114	95.26 120	82.60 121	92.09 254	95.70 129	86.27 112	91.84 65	92.46 182	79.70 94	98.99 59	89.08 73	95.86 83	94.29 197

jajsoiax		88.24 144	87.50 139	90.48 172	90.89 280	80.14 173	95.31 64	95.65 134	84.97 140	84.24 220	94.02 128	65.31 281	97.42 177	88.56 78	88.52 201	93.89 215

mvs_tets		88.06 151	87.28 146	90.38 179	90.94 276	79.88 181	95.22 77	95.66 132	85.10 137	84.21 221	93.94 133	63.53 289	97.40 184	88.50 79	88.40 206	93.87 218

#test#		94.32 21	94.14 22	94.86 15	98.61 3	86.81 17	96.43 23	97.34 12	87.51 85	93.65 25	97.21 19	86.10 29	99.49 16	91.68 48	98.77 14	98.30 26

EI-MVSNet-UG-set		92.74 55	92.62 51	93.12 67	94.86 139	83.20 98	94.40 135	95.74 127	90.71 21	92.05 62	96.60 45	84.00 51	98.99 59	91.55 49	93.63 120	97.17 86

EI-MVSNet-Vis-set		93.01 52	92.92 47	93.29 60	95.01 130	83.51 92	94.48 127	95.77 124	90.87 16	92.52 52	96.67 41	84.50 48	99.00 58	91.99 39	94.44 109	97.36 77

Regformer-3		93.68 35	93.64 35	93.81 54	95.36 113	84.61 61	94.68 116	95.83 120	91.27 13	93.60 28	96.71 37	85.75 34	98.86 70	92.87 21	96.65 72	97.96 54

Regformer-4		93.91 31	93.81 29	94.19 45	95.36 113	85.47 52	94.68 116	96.41 77	91.60 11	93.75 24	96.71 37	85.95 32	99.10 43	93.21 19	96.65 72	98.01 52

Regformer-1		94.22 24	94.13 23	94.51 35	95.54 107	86.36 34	94.57 124	96.44 74	91.69 10	94.32 16	96.56 48	87.05 22	99.03 50	93.35 18	97.65 57	98.15 40

Regformer-2		94.33 20	94.22 18	94.68 28	95.54 107	86.75 21	94.57 124	96.70 60	91.84 6	94.41 14	96.56 48	87.19 20	99.13 40	93.50 13	97.65 57	98.16 39

v7new		87.98 152	87.25 148	90.16 186	91.38 245	79.41 198	94.37 141	95.28 164	84.48 150	85.77 160	91.53 223	76.12 127	97.45 166	84.45 128	81.89 267	93.61 242

HPM-MVS++		95.14 7	94.91 9	95.83 1	98.25 22	89.65 1	95.92 42	96.96 39	91.75 8	94.02 21	96.83 33	88.12 11	99.55 7	93.41 17	98.94 5	98.28 28

test_prior4						85.96 44	94.11 161

XVS		94.45 14	94.32 14	94.85 17	98.54 7	86.60 27	96.93 12	97.19 24	90.66 22	92.85 39	97.16 24	85.02 43	99.49 16	91.99 39	98.56 35	98.47 14

v1240		86.78 203	85.85 201	89.56 220	90.45 295	77.79 256	93.61 199	95.37 161	81.65 231	85.43 182	91.15 244	71.50 200	97.43 175	81.47 173	82.05 265	93.47 250

test_prior3		93.60 37	93.53 36	93.82 52	97.29 50	84.49 65	94.12 159	96.88 45	87.67 82	92.63 48	96.39 53	86.62 25	98.87 67	91.50 50	98.67 26	98.11 44

v18		84.97 246	83.76 244	88.60 252	91.36 248	79.41 198	93.82 184	94.04 216	83.00 195	76.61 302	86.60 310	76.19 125	95.43 292	80.39 189	71.79 327	90.96 309

pm-mvs1		86.61 207	85.54 205	89.82 208	91.44 238	80.18 171	95.28 74	94.85 192	83.84 163	81.66 259	92.62 180	72.45 192	96.48 250	79.67 206	78.06 309	92.82 271

test_prior2							94.12 159		87.67 82	92.63 48	96.39 53	86.62 25		91.50 50	98.67 26

X-MVStestdata		88.31 142	86.13 190	94.85 17	98.54 7	86.60 27	96.93 12	97.19 24	90.66 22	92.85 39	23.41 363	85.02 43	99.49 16	91.99 39	98.56 35	98.47 14

test_prior				93.82 52	97.29 50	84.49 65		96.88 45					98.87 67			98.11 44

v17		84.93 249	83.70 248	88.62 250	91.36 248	79.48 192	93.83 182	94.03 218	83.04 191	76.51 304	86.57 312	76.05 131	95.42 293	80.31 194	71.65 328	90.96 309

v16		84.96 247	83.74 246	88.62 250	91.40 243	79.48 192	93.83 182	94.04 216	83.03 192	76.54 303	86.59 311	76.11 130	95.42 293	80.33 192	71.80 326	90.95 311

divwei89l23v2f112		87.84 158	87.09 152	90.10 199	91.23 260	79.24 214	94.09 164	95.24 169	84.44 154	85.70 165	91.31 236	75.91 139	97.44 173	84.17 133	81.73 276	93.64 238

v15		84.79 252	83.53 253	88.57 256	91.30 259	79.41 198	93.70 195	94.01 219	83.06 188	76.27 305	86.42 316	76.03 134	95.38 295	80.01 196	71.00 331	90.92 312

旧先验2							93.36 206		71.25 327	94.37 15			97.13 209	86.74 104

新几何2							93.11 220

新几何1				93.10 68	97.30 49	84.35 74		95.56 138	71.09 329	91.26 76	96.24 57	82.87 59	98.86 70	79.19 214	98.10 47	96.07 122

旧先验1					96.79 61	81.81 132		95.67 130			96.81 34	86.69 24			97.66 56	96.97 96

无先验							93.28 213	96.26 85	73.95 306				99.05 46	80.56 186		96.59 105

原ACMM2							92.94 229

原ACMM1				92.01 110	97.34 47	81.05 152		96.81 50	78.89 259	90.45 85	95.92 71	82.65 60	98.84 75	80.68 184	98.26 43	96.14 116

v13		84.72 257	83.44 258	88.58 253	91.31 258	79.52 188	93.77 187	94.00 222	83.03 192	75.85 314	86.38 318	75.84 141	95.35 300	79.83 203	70.95 333	90.87 316

v12		84.74 255	83.46 256	88.58 253	91.32 255	79.50 189	93.75 189	94.01 219	83.06 188	75.98 313	86.41 317	75.82 142	95.36 299	79.87 202	70.89 335	90.89 315

test222					96.55 68	81.70 133	92.22 249	95.01 182	68.36 336	90.20 88	96.14 65	80.26 88			97.80 54	96.05 124

testdata2													98.75 79	78.30 221

segment_acmp												87.16 21

testdata				90.49 171	96.40 72	77.89 252		95.37 161	72.51 319	93.63 27	96.69 39	82.08 69	97.65 151	83.08 143	97.39 60	95.94 126

testdata1							92.15 251		87.94 72

v8		87.50 183	86.71 168	89.89 206	91.37 247	79.40 202	94.50 126	95.38 159	84.81 143	83.60 233	91.33 233	76.05 131	97.42 177	82.84 148	80.51 295	92.84 269

1314		87.51 182	86.57 181	90.34 182	92.42 216	79.74 186	92.63 236	95.35 163	78.35 268	80.14 278	91.62 218	74.05 167	97.15 206	81.05 175	93.53 122	94.12 203

1121		90.42 91	89.49 95	93.20 63	97.27 52	84.46 68	92.63 236	95.51 145	71.01 330	91.20 77	96.21 59	82.92 58	99.05 46	80.56 186	98.07 48	96.10 120

LFMVS		90.08 96	89.13 105	92.95 76	96.71 62	82.32 125	96.08 35	89.91 316	86.79 104	92.15 61	96.81 34	62.60 292	98.34 101	87.18 98	93.90 115	98.19 37

v7		87.75 163	86.96 158	90.12 192	91.20 263	79.50 189	94.28 147	95.46 149	83.45 176	85.75 162	91.56 222	75.13 151	97.43 175	83.60 140	82.18 262	93.42 251

v6		87.98 152	87.25 148	90.16 186	91.36 248	79.39 203	94.37 141	95.27 167	84.48 150	85.78 159	91.51 225	76.15 126	97.46 164	84.46 127	81.88 269	93.62 241

VDD-MVS		90.74 81	89.92 91	93.20 63	96.27 76	83.02 105	95.73 48	93.86 227	88.42 63	92.53 51	96.84 32	62.09 295	98.64 83	90.95 59	92.62 140	97.93 58

v11		84.67 260	83.41 259	88.44 261	91.32 255	79.13 217	93.69 198	93.99 224	82.81 201	76.20 307	86.24 320	75.48 147	95.35 300	79.53 207	71.48 330	90.85 317

VDDNet		89.56 109	88.49 120	92.76 83	95.07 129	82.09 127	96.30 26	93.19 237	81.05 242	91.88 64	96.86 31	61.16 305	98.33 102	88.43 81	92.49 142	97.84 62

v52		86.50 210	85.53 208	89.39 228	89.17 311	78.99 219	94.72 113	95.54 141	83.59 169	82.10 251	90.60 257	71.59 197	97.45 166	82.52 152	79.99 300	91.73 294

V14		84.79 252	83.52 254	88.57 256	91.32 255	79.43 197	93.72 193	94.01 219	83.06 188	76.22 306	86.43 313	76.01 135	95.37 296	79.96 198	70.99 332	90.91 313

v10		87.25 191	86.38 183	89.85 207	91.19 265	79.50 189	94.48 127	95.45 153	83.79 166	83.62 232	91.19 241	75.13 151	97.42 177	81.94 165	80.60 290	92.63 275

V4		86.50 210	85.54 205	89.39 228	89.13 312	78.99 219	94.73 110	95.54 141	83.59 169	82.10 251	90.61 256	71.60 196	97.45 166	82.52 152	80.01 299	91.74 293

VPNet		88.20 145	87.47 141	90.39 177	93.56 187	79.46 194	94.04 172	95.54 141	88.67 56	86.96 137	94.58 112	69.33 228	97.15 206	84.05 135	80.53 293	94.56 185

MVS		87.44 184	86.10 193	91.44 134	92.61 214	83.62 89	92.63 236	95.66 132	67.26 340	81.47 260	92.15 195	77.95 111	98.22 109	79.71 205	95.48 88	92.47 279

v2v482		87.84 158	87.06 155	90.17 185	90.99 272	79.23 216	94.00 176	95.13 176	84.87 141	85.53 173	92.07 203	74.45 159	97.45 166	84.71 124	81.75 273	93.85 221

v1		87.85 157	87.10 151	90.11 197	91.21 262	79.24 214	94.09 164	95.24 169	84.44 154	85.70 165	91.31 236	75.96 137	97.45 166	84.18 132	81.73 276	93.64 238

V42		87.68 165	86.86 160	90.15 190	90.58 290	80.14 173	94.24 149	95.28 164	83.66 168	85.67 168	91.33 233	74.73 157	97.41 182	84.43 130	81.83 271	92.89 267

V9		84.77 254	83.50 255	88.58 253	91.33 253	79.46 194	93.75 189	94.00 222	83.07 187	76.07 311	86.43 313	75.97 136	95.37 296	79.91 201	70.93 334	90.91 313

SD-MVS		94.96 8	95.33 5	93.88 50	97.25 54	86.69 22	96.19 30	97.11 30	90.42 24	96.95 3	97.27 14	89.53 4	96.91 226	94.38 7	98.85 8	98.03 50

GA-MVS		86.61 207	85.27 214	90.66 159	91.33 253	78.71 223	90.40 276	93.81 230	85.34 131	85.12 193	89.57 275	61.25 302	97.11 210	80.99 179	89.59 180	96.15 115

MSLP-MVS++		93.72 34	94.08 24	92.65 86	97.31 48	83.43 93	95.79 46	97.33 15	90.03 27	93.58 29	96.96 29	84.87 45	97.76 146	92.19 33	98.66 28	96.76 101

APDe-MVS		95.46 2	95.64 2	94.91 13	98.26 21	86.29 39	97.46 2	97.40 10	89.03 48	96.20 6	98.10 1	89.39 6	99.34 23	95.88 1	99.03 3	99.10 1

APD-MVS_3200maxsize		93.78 33	93.77 32	93.80 55	97.92 33	84.19 76	96.30 26	96.87 47	86.96 99	93.92 23	97.47 9	83.88 53	98.96 64	92.71 24	97.87 52	98.26 33

ADS-MVSNet2		81.66 286	79.71 292	87.50 281	91.35 251	74.19 290	83.33 339	88.48 336	72.90 316	82.24 249	85.77 322	64.98 283	93.20 325	64.57 322	83.74 245	95.12 150

EI-MVSNet		89.10 123	88.86 113	89.80 211	91.84 226	78.30 241	93.70 195	95.01 182	85.73 122	87.15 134	95.28 87	79.87 91	97.21 204	83.81 138	87.36 217	93.88 217

Regformer		0.00 348	0.00 349	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	0.00 374	0.00 369	0.00 366	0.00 367	0.00 367

CVMVSNet		84.69 259	84.79 226	84.37 317	91.84 226	64.92 340	93.70 195	91.47 281	66.19 342	86.16 155	95.28 87	67.18 264	93.33 323	80.89 181	90.42 165	94.88 167

pmmvs4		85.43 236	83.86 243	90.16 186	90.02 304	82.97 108	90.27 277	92.67 247	75.93 289	80.73 269	91.74 213	71.05 204	95.73 281	78.85 216	83.46 251	91.78 292

EU-MVSNet		81.32 292	80.95 278	82.42 324	88.50 319	63.67 341	93.32 207	91.33 283	64.02 346	80.57 273	92.83 173	61.21 304	92.27 331	76.34 240	80.38 296	91.32 302

VNet		92.24 59	91.91 58	93.24 62	96.59 66	83.43 93	94.84 103	96.44 74	89.19 43	94.08 20	95.90 72	77.85 115	98.17 112	88.90 75	93.38 127	98.13 42

test-LLR		85.87 222	85.41 210	87.25 287	90.95 274	71.67 313	89.55 287	89.88 317	83.41 177	84.54 208	87.95 298	67.25 262	95.11 305	81.82 167	93.37 128	94.97 155

TESTMET0.1,1		83.74 269	82.85 266	86.42 302	89.96 305	71.21 317	89.55 287	87.88 339	77.41 275	83.37 238	87.31 306	56.71 321	93.65 320	80.62 185	92.85 139	94.40 195

test-mter		84.54 261	83.64 251	87.25 287	90.95 274	71.67 313	89.55 287	89.88 317	79.17 256	84.54 208	87.95 298	55.56 324	95.11 305	81.82 167	93.37 128	94.97 155

VPA-MVSNet		89.62 106	88.96 108	91.60 130	93.86 177	82.89 110	95.46 61	97.33 15	87.91 73	88.43 107	93.31 152	74.17 165	97.40 184	87.32 97	82.86 256	94.52 187

ACMMPR		94.43 16	94.28 16	94.91 13	98.63 2	86.69 22	96.94 10	97.32 17	88.63 57	93.53 32	97.26 16	85.04 42	99.54 10	92.35 29	98.78 13	98.50 11

testgi		80.94 297	80.20 286	83.18 321	87.96 328	66.29 336	91.28 268	90.70 303	83.70 167	78.12 290	92.84 172	51.37 335	90.82 338	63.34 325	82.46 259	92.43 280

test20.03		79.95 301	79.08 298	82.55 323	85.79 334	67.74 334	91.09 273	91.08 291	81.23 240	74.48 321	89.96 270	61.63 298	90.15 339	60.08 334	76.38 315	89.76 324

thres600view7		87.65 167	86.67 172	90.59 160	96.08 89	78.72 222	94.88 100	91.58 273	87.06 98	88.08 112	92.30 189	68.91 236	98.10 122	70.05 285	91.10 150	94.96 158

1111		70.54 322	69.71 322	73.04 336	79.30 349	44.83 361	84.23 333	88.96 333	67.33 338	65.42 343	82.28 335	41.11 350	88.11 344	47.12 349	71.60 329	86.19 343

.test1245		57.63 332	61.79 329	45.14 350	79.30 349	44.83 361	84.23 333	88.96 333	67.33 338	65.42 343	82.28 335	41.11 350	88.11 344	47.12 349	0.39 364	2.46 365

ADS-MVSNet		81.56 288	79.78 290	86.90 296	91.35 251	71.82 312	83.33 339	89.16 331	72.90 316	82.24 249	85.77 322	64.98 283	93.76 318	64.57 322	83.74 245	95.12 150

MP-MVS		94.25 22	94.07 25	94.77 24	98.47 11	86.31 37	96.71 20	96.98 35	89.04 47	91.98 63	97.19 21	85.43 37	99.56 2	92.06 38	98.79 11	98.44 19
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		8.92 344	11.52 345	1.12 356	1.06 370	0.46 371	86.02 321	0.65 372	0.62 365	2.74 367	9.52 366	0.31 373	0.45 368	2.38 364	0.39 364	2.46 365

thres400		87.62 174	86.64 177	90.57 161	95.99 93	78.64 224	94.58 122	91.98 264	86.94 101	88.09 110	91.77 211	69.18 233	98.10 122	70.13 281	91.10 150	94.96 158

test123		8.76 345	11.22 346	1.39 355	0.85 371	0.97 370	85.76 325	0.35 373	0.54 366	2.45 368	8.14 367	0.60 372	0.48 367	2.16 365	0.17 366	2.71 364

thres200		87.21 194	86.24 189	90.12 192	95.36 113	78.53 230	93.26 214	92.10 257	86.42 110	88.00 117	91.11 246	69.24 232	98.00 135	69.58 287	91.04 157	93.83 222

test0.0.03 1		82.41 279	81.69 272	84.59 315	88.23 323	72.89 301	90.24 278	87.83 340	83.41 177	79.86 281	89.78 272	67.25 262	88.99 341	65.18 319	83.42 252	91.90 291

test12356		64.99 326	63.78 325	68.61 343	72.69 355	39.14 364	78.46 349	87.61 343	64.91 344	55.77 350	77.48 345	28.10 356	85.59 351	44.69 352	64.35 346	81.12 349

testus		74.41 316	73.35 314	77.59 332	82.49 346	57.08 349	86.02 321	90.21 308	72.28 321	72.89 329	84.32 327	37.08 352	86.96 347	52.24 342	82.65 257	88.73 333

pmmvs3		71.81 320	68.71 323	81.11 325	75.86 353	70.42 324	86.74 317	83.66 351	58.95 350	68.64 340	80.89 340	36.93 353	89.52 340	63.10 327	63.59 347	83.39 345

testmv		65.49 325	62.66 326	73.96 335	68.78 358	53.14 356	84.70 331	88.56 335	65.94 343	52.35 352	74.65 347	25.02 359	85.14 352	43.54 353	60.40 351	83.60 344

EMVS		42.07 338	41.12 339	44.92 351	63.45 364	35.56 367	73.65 352	63.48 365	33.05 361	26.88 364	45.45 362	21.27 362	67.14 362	19.80 362	23.02 361	32.06 361

E-PMN		43.23 337	42.29 338	46.03 349	65.58 362	37.41 365	73.51 353	64.62 364	33.99 360	28.47 363	47.87 360	19.90 364	67.91 361	22.23 361	24.45 359	32.77 360

test2356		74.50 315	73.27 315	78.20 328	80.81 347	59.84 344	83.76 338	88.33 338	71.43 326	72.37 331	81.84 337	45.60 346	86.26 349	50.97 343	84.32 239	88.50 337

test1235678		72.22 318	70.31 320	77.93 331	78.04 352	58.04 348	85.76 325	89.80 319	70.15 333	63.43 346	80.20 342	42.24 349	87.24 346	48.68 347	74.50 319	88.50 337

PGM-MVS		93.96 30	93.72 33	94.68 28	98.43 13	86.22 40	95.30 66	97.78 1	87.45 86	93.26 33	97.33 12	84.62 47	99.51 14	90.75 62	98.57 34	98.32 25

LCM-MVSNet-Re		88.30 143	88.32 125	88.27 265	94.71 144	72.41 310	93.15 217	90.98 295	87.77 78	79.25 286	91.96 206	78.35 109	95.75 280	83.04 144	95.62 85	96.65 104

LCM-MVSNet		66.00 324	62.16 328	77.51 333	64.51 363	58.29 347	83.87 337	90.90 297	48.17 354	54.69 351	73.31 349	16.83 366	86.75 348	65.47 317	61.67 349	87.48 342

MCST-MVS		94.45 14	94.20 21	95.19 7	98.46 12	87.50 9	95.00 92	97.12 28	87.13 92	92.51 53	96.30 55	89.24 7	99.34 23	93.46 14	98.62 32	98.73 4

mvs_anonymous		89.37 119	89.32 100	89.51 224	93.47 189	74.22 289	91.65 263	94.83 194	82.91 199	85.45 179	93.79 142	81.23 80	96.36 257	86.47 110	94.09 112	97.94 55

MVS_Test		91.31 73	91.11 68	91.93 116	94.37 158	80.14 173	93.46 205	95.80 122	86.46 109	91.35 75	93.77 143	82.21 66	98.09 129	87.57 92	94.95 97	97.55 74

MDA-MVSNet-bldmvs		78.85 308	76.31 309	86.46 300	89.76 308	73.88 294	88.79 300	90.42 304	79.16 257	59.18 349	88.33 293	60.20 309	94.04 316	62.00 329	68.96 340	91.48 300

CDPH-MVS		92.83 53	92.30 55	94.44 36	97.79 35	86.11 43	94.06 171	96.66 64	80.09 249	92.77 43	96.63 43	86.62 25	99.04 49	87.40 94	98.66 28	98.17 38

test12				94.34 41	97.13 55	86.15 41		96.29 84		91.04 79		85.08 41	99.01 55		98.13 46	97.86 61

casdiffmvs		91.72 66	91.26 65	93.10 68	94.66 147	83.75 84	94.77 108	96.00 106	83.98 160	90.74 81	93.96 132	82.08 69	98.19 111	91.47 52	93.68 118	97.36 77

diffmvs		90.50 90	90.33 80	91.02 150	93.04 202	78.59 226	92.85 231	95.07 181	87.32 88	88.32 109	93.34 148	80.46 84	97.40 184	88.50 79	94.06 113	97.07 91

casdiffmvs1		92.43 57	92.18 57	93.17 65	95.33 116	83.03 103	95.08 85	96.41 77	83.18 184	93.20 35	94.49 113	83.84 54	98.29 105	92.16 34	95.96 81	98.20 36

diffmvs1		91.33 72	91.22 67	91.68 127	93.43 191	79.77 184	93.02 224	95.50 146	87.72 79	90.47 84	93.87 140	81.76 76	97.52 159	89.84 68	95.36 93	97.74 67

YYNet1		79.22 306	77.20 306	85.28 311	88.20 325	72.66 306	85.87 323	90.05 314	74.33 304	62.70 347	87.61 303	66.09 278	92.03 332	66.94 305	72.97 322	91.15 305

PMMVS2		59.60 329	56.40 331	69.21 342	68.83 357	46.58 359	73.02 356	77.48 362	55.07 352	49.21 354	72.95 350	17.43 365	80.04 357	49.32 346	44.33 354	80.99 350

MDA-MVSNet_test_wron		79.21 307	77.19 307	85.29 310	88.22 324	72.77 304	85.87 323	90.06 312	74.34 303	62.62 348	87.56 304	66.14 277	91.99 333	66.90 308	73.01 321	91.10 308

tpmvs		83.35 273	82.07 270	87.20 291	91.07 270	71.00 320	88.31 307	91.70 270	78.91 258	80.49 274	87.18 308	69.30 231	97.08 212	68.12 302	83.56 249	93.51 249

PM-MVS		78.11 309	76.12 311	84.09 320	83.54 342	70.08 326	88.97 299	85.27 349	79.93 250	74.73 319	86.43 313	34.70 354	93.48 321	79.43 211	72.06 325	88.72 334

HQP_MVS		90.60 88	90.19 83	91.82 122	94.70 145	82.73 115	95.85 44	96.22 89	90.81 18	86.91 139	94.86 100	74.23 162	98.12 116	88.15 83	89.99 171	94.63 178

plane_prior7					94.70 145	82.74 114

plane_prior6					94.52 152	82.75 112						74.23 162

plane_prior5								96.22 89					98.12 116	88.15 83	89.99 171	94.63 178

plane_prior4											94.86 100

plane_prior3						82.75 112			90.26 25	86.91 139

plane_prior2							95.85 44		90.81 18

plane_prior1					94.59 150

plane_prior						82.73 115	95.21 78		89.66 35						89.88 175

PS-CasMVS		87.32 188	86.88 159	88.63 249	92.99 206	76.33 279	95.33 63	96.61 68	88.22 68	83.30 239	93.07 163	73.03 182	95.79 279	78.36 220	81.00 286	93.75 229

UniMVSNet_NR-MVSNet		89.92 102	89.29 101	91.81 124	93.39 192	83.72 85	94.43 133	97.12 28	89.80 31	86.46 146	93.32 151	83.16 56	97.23 202	84.92 119	81.02 284	94.49 191

PEN-MVS		86.80 202	86.27 188	88.40 262	92.32 218	75.71 283	95.18 79	96.38 81	87.97 71	82.82 243	93.15 159	73.39 178	95.92 272	76.15 243	79.03 307	93.59 244

TransMVSNet (Re)		84.43 262	83.06 263	88.54 258	91.72 230	78.44 237	95.18 79	92.82 243	82.73 203	79.67 282	92.12 197	73.49 175	95.96 271	71.10 276	68.73 342	91.21 304

DTE-MVSNet		86.11 216	85.48 209	87.98 272	91.65 234	74.92 286	94.93 96	95.75 126	87.36 87	82.26 248	93.04 164	72.85 183	95.82 277	74.04 259	77.46 313	93.20 256

DU-MVS		89.34 120	88.50 118	91.85 120	93.04 202	83.72 85	94.47 130	96.59 69	89.50 36	86.46 146	93.29 154	77.25 116	97.23 202	84.92 119	81.02 284	94.59 182

UniMVSNet (Re)		89.80 104	89.07 106	92.01 110	93.60 186	84.52 64	94.78 107	97.47 6	89.26 41	86.44 149	92.32 188	82.10 68	97.39 188	84.81 122	80.84 288	94.12 203

CP-MVSNet		87.63 171	87.26 147	88.74 246	93.12 199	76.59 276	95.29 68	96.58 71	88.43 62	83.49 236	92.98 169	75.28 150	95.83 276	78.97 215	81.15 281	93.79 223

WR-MVS_H		87.80 162	87.37 143	89.10 241	93.23 196	78.12 246	95.61 57	97.30 18	87.90 74	83.72 228	92.01 205	79.65 98	96.01 269	76.36 239	80.54 292	93.16 258

WR-MVS		88.38 139	87.67 138	90.52 169	93.30 195	80.18 171	93.26 214	95.96 109	88.57 60	85.47 178	92.81 175	76.12 127	96.91 226	81.24 174	82.29 260	94.47 194

NR-MVSNet		88.58 137	87.47 141	91.93 116	93.04 202	84.16 77	94.77 108	96.25 87	89.05 46	80.04 280	93.29 154	79.02 100	97.05 215	81.71 170	80.05 298	94.59 182

Baseline_NR-MVSNet		87.07 197	86.63 179	88.40 262	91.44 238	77.87 253	94.23 150	92.57 249	84.12 159	85.74 164	92.08 201	77.25 116	96.04 266	82.29 159	79.94 301	91.30 303

TranMVSNet+NR-MVSNet		88.84 130	87.95 133	91.49 132	92.68 213	83.01 106	94.92 97	96.31 83	89.88 30	85.53 173	93.85 141	76.63 123	96.96 221	81.91 166	79.87 303	94.50 189

TSAR-MVS + GP.		93.66 36	93.41 37	94.41 39	96.59 66	86.78 19	94.40 135	93.93 226	89.77 32	94.21 17	95.59 82	87.35 18	98.61 86	92.72 23	96.15 80	97.83 63

abl_6		93.18 50	93.05 43	93.57 59	97.52 40	84.27 75	95.53 60	96.67 63	87.85 76	93.20 35	97.22 18	80.35 85	99.18 34	91.91 43	97.21 62	97.26 80

n2								0.00 374

nn								0.00 374

mPP-MVS		93.99 29	93.78 31	94.63 30	98.50 9	85.90 48	96.87 16	96.91 43	88.70 55	91.83 67	97.17 23	83.96 52	99.55 7	91.44 53	98.64 31	98.43 20

door-mid								85.49 347

DI_MVS_plusplus_test		88.15 147	86.82 162	92.14 108	90.67 288	81.07 151	93.01 225	94.59 200	83.83 165	77.78 293	90.63 255	68.51 248	98.16 113	88.02 87	94.37 110	97.17 86

XVG-OURS-SEG-HR		89.95 100	89.45 96	91.47 133	94.00 172	81.21 148	91.87 256	96.06 102	85.78 120	88.55 105	95.73 78	74.67 158	97.27 196	88.71 77	89.64 179	95.91 127

DWT-MVSNet_test		84.95 248	83.68 249	88.77 244	91.43 241	73.75 295	91.74 259	90.98 295	80.66 244	83.84 225	87.36 305	62.44 293	97.11 210	78.84 217	85.81 227	95.46 143

MVSFormer		91.68 68	91.30 63	92.80 81	93.86 177	83.88 81	95.96 40	95.90 114	84.66 147	91.76 68	94.91 97	77.92 112	97.30 192	89.64 70	97.11 63	97.24 81

jason		90.80 80	90.10 85	92.90 78	93.04 202	83.53 91	93.08 221	94.15 213	80.22 246	91.41 74	94.91 97	76.87 118	97.93 140	90.28 66	96.90 66	97.24 81
jason: jason.
lupinMVS		90.92 79	90.21 82	93.03 73	93.86 177	83.88 81	92.81 232	93.86 227	79.84 251	91.76 68	94.29 119	77.92 112	98.04 133	90.48 65	97.11 63	97.17 86

test_djsdf		89.03 126	88.64 115	90.21 184	90.74 285	79.28 210	95.96 40	95.90 114	84.66 147	85.33 191	92.94 170	74.02 168	97.30 192	89.64 70	88.53 200	94.05 209

Test4		85.75 229	83.72 247	91.83 121	88.08 326	81.03 153	92.48 241	95.54 141	83.38 179	73.40 326	88.57 288	50.99 336	97.37 189	86.61 109	94.47 107	97.09 90

HPM-MVS_fast		93.40 42	93.22 40	93.94 49	98.36 18	84.83 58	97.15 7	96.80 51	85.77 121	92.47 54	97.13 25	82.38 62	99.07 44	90.51 64	98.40 39	97.92 59

PatchFormer-LS_test		86.02 219	85.13 215	88.70 247	91.52 235	74.12 292	91.19 271	92.09 258	82.71 204	84.30 219	87.24 307	70.87 207	96.98 219	81.04 176	85.17 234	95.00 154

testpf		71.41 321	72.11 319	69.30 341	84.53 339	59.79 345	62.74 358	83.14 352	71.11 328	68.83 339	81.57 339	46.70 344	84.83 354	74.51 258	75.86 317	63.30 354

K. test v3		81.59 287	80.15 287	85.91 306	89.89 307	69.42 329	92.57 239	87.71 341	85.56 126	73.44 325	89.71 273	55.58 323	95.52 286	77.17 233	69.76 338	92.78 272

lessismore_v0				86.04 304	88.46 320	68.78 331		80.59 357		73.01 328	90.11 267	55.39 325	96.43 254	75.06 252	65.06 344	92.90 266

SixPastTwentyTwo		83.91 266	82.90 265	86.92 295	90.99 272	70.67 322	93.48 203	91.99 263	85.54 127	77.62 296	92.11 199	60.59 307	96.87 228	76.05 244	77.75 310	93.20 256

OurMVSNet-221017-0		85.35 238	84.64 230	87.49 282	90.77 283	72.59 308	94.01 175	94.40 205	84.72 146	79.62 284	93.17 158	61.91 297	96.72 237	81.99 164	81.16 279	93.16 258

HPM-MVS		94.02 28	93.88 28	94.43 38	98.39 16	85.78 50	97.25 5	97.07 32	86.90 103	92.62 50	96.80 36	84.85 46	99.17 35	92.43 26	98.65 30	98.33 24
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
XVG-OURS		89.40 118	88.70 114	91.52 131	94.06 166	81.46 140	91.27 269	96.07 100	86.14 116	88.89 103	95.77 77	68.73 245	97.26 198	87.39 95	89.96 173	95.83 132

XVG-ACMP-BASELINE		86.00 220	84.84 225	89.45 226	91.20 263	78.00 248	91.70 261	95.55 139	85.05 139	82.97 241	92.25 194	54.49 329	97.48 162	82.93 146	87.45 216	92.89 267

LPG-MVS_test		89.45 113	88.90 111	91.12 142	94.47 154	81.49 138	95.30 66	96.14 94	86.73 105	85.45 179	95.16 92	69.89 221	98.10 122	87.70 90	89.23 186	93.77 227

LGP-MVS_train				91.12 142	94.47 154	81.49 138		96.14 94	86.73 105	85.45 179	95.16 92	69.89 221	98.10 122	87.70 90	89.23 186	93.77 227

test11								96.57 72

door								85.33 348

EPNet_dtu		86.49 212	85.94 200	88.14 270	90.24 299	72.82 302	94.11 161	92.20 255	86.66 107	79.42 285	92.36 187	73.52 174	95.81 278	71.26 272	93.66 119	95.80 134
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x2688		88.84 130	87.69 137	92.30 102	96.14 82	81.42 142	90.01 282	95.86 118	74.52 302	87.41 131	93.94 133	75.46 148	98.36 98	80.36 190	95.53 86	97.12 89

EPNet		91.79 62	91.02 71	94.10 46	90.10 301	85.25 55	96.03 37	92.05 260	92.83 1	87.39 133	95.78 76	79.39 99	99.01 55	88.13 85	97.48 59	98.05 48
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS						81.56 134

HQP-NCC					94.17 163		94.39 137		88.81 51	85.43 182

ACMP_Plane					94.17 163		94.39 137		88.81 51	85.43 182

APD-MVS		94.24 23	94.07 25	94.75 26	98.06 30	86.90 16	95.88 43	96.94 41	85.68 124	95.05 13	97.18 22	87.31 19	99.07 44	91.90 46	98.61 33	98.28 28
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS														87.11 101

HQP4-MVS										85.43 182			97.96 137			94.51 188

HQP3-MVS								96.04 104							89.77 177

HQP2-MVS												73.83 171

LP		75.51 314	72.15 318	85.61 308	87.86 329	73.93 293	80.20 347	88.43 337	67.39 337	70.05 335	80.56 341	58.18 318	93.18 326	46.28 351	70.36 337	89.71 326

CNVR-MVS		95.40 3	95.37 4	95.50 4	98.11 27	88.51 3	95.29 68	96.96 39	92.09 3	95.32 11	97.08 26	89.49 5	99.33 26	95.10 2	98.85 8	98.66 6

NCCC		94.81 10	94.69 11	95.17 8	97.83 34	87.46 10	95.66 53	96.93 42	92.34 2	93.94 22	96.58 46	87.74 14	99.44 20	92.83 22	98.40 39	98.62 7

114514_t		89.51 110	88.50 118	92.54 91	98.11 27	81.99 129	95.16 81	96.36 82	70.19 332	85.81 158	95.25 89	76.70 121	98.63 84	82.07 162	96.86 68	97.00 95

CP-MVS		94.34 19	94.21 20	94.74 27	98.39 16	86.64 26	97.60 1	97.24 21	88.53 61	92.73 46	97.23 17	85.20 40	99.32 27	92.15 35	98.83 10	98.25 34

DSMNet-mixed		76.94 311	76.29 310	78.89 327	83.10 343	56.11 353	87.78 311	79.77 358	60.65 349	75.64 315	88.71 285	61.56 299	88.34 343	60.07 335	89.29 185	92.21 288

tpm2		84.08 264	82.94 264	87.48 283	91.39 244	71.27 315	89.23 295	90.37 305	71.95 323	84.64 205	89.33 277	67.30 261	96.55 247	75.17 250	87.09 221	94.63 178

NP-MVS					94.37 158	82.42 122					93.98 130

EG-PatchMatch MVS		82.37 280	80.34 283	88.46 260	90.27 297	79.35 205	92.80 233	94.33 208	77.14 279	73.26 327	90.18 266	47.47 343	96.72 237	70.25 278	87.32 219	89.30 327

tpm cat1		81.96 281	80.27 284	87.01 293	91.09 269	71.02 319	87.38 315	91.53 279	66.25 341	80.17 276	86.35 319	68.22 260	96.15 264	69.16 292	82.29 260	93.86 220

SteuartSystems-ACMMP		95.20 5	95.32 6	94.85 17	96.99 57	86.33 35	97.33 3	97.30 18	91.38 12	95.39 10	97.46 10	88.98 9	99.40 21	94.12 9	98.89 7	98.82 3
Skip Steuart: Steuart Systems R&D Blog.
tpmp4_e23		83.87 268	82.33 269	88.48 259	91.46 237	72.82 302	89.82 285	91.57 277	73.02 315	81.86 258	89.05 279	66.20 275	96.97 220	71.57 271	86.39 224	95.66 138

CostFormer		85.77 228	84.94 221	88.26 266	91.16 268	72.58 309	89.47 291	91.04 294	76.26 286	86.45 148	89.97 269	70.74 210	96.86 229	82.35 157	87.07 222	95.34 148

CR-MVSNet		85.35 238	83.76 244	90.12 192	90.58 290	79.34 206	85.24 328	91.96 266	78.27 269	85.55 171	87.87 301	71.03 205	95.61 282	73.96 261	89.36 183	95.40 145

JIA-IIPM		81.04 294	78.98 300	87.25 287	88.64 317	73.48 297	81.75 344	89.61 322	73.19 312	82.05 253	73.71 348	66.07 279	95.87 275	71.18 275	84.60 238	92.41 281

Patchmtry		82.71 276	80.93 279	88.06 271	90.05 303	76.37 278	84.74 330	91.96 266	72.28 321	81.32 264	87.87 301	71.03 205	95.50 289	68.97 293	80.15 297	92.32 285

PatchT		82.68 277	81.27 275	86.89 297	90.09 302	70.94 321	84.06 335	90.15 309	74.91 298	85.63 170	83.57 330	69.37 227	94.87 310	65.19 318	88.50 202	94.84 168

tpmrst		85.35 238	84.99 217	86.43 301	90.88 281	67.88 333	88.71 301	91.43 282	80.13 248	86.08 156	88.80 284	73.05 181	96.02 268	82.48 154	83.40 253	95.40 145

BH-w/o		87.57 181	87.05 156	89.12 239	94.90 138	77.90 251	92.41 243	93.51 233	82.89 200	83.70 229	91.34 232	75.75 144	97.07 213	75.49 246	93.49 123	92.39 282

tpm		84.73 256	84.02 240	86.87 298	90.33 296	68.90 330	89.06 297	89.94 315	80.85 243	85.75 162	89.86 271	68.54 247	95.97 270	77.76 226	84.05 243	95.75 136

DELS-MVS		93.43 41	93.25 39	93.97 47	95.42 112	85.04 56	93.06 223	97.13 27	90.74 20	91.84 65	95.09 95	86.32 28	99.21 32	91.22 54	98.45 38	97.65 68
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		88.60 136	88.13 130	90.01 203	95.24 127	78.50 236	93.29 212	94.15 213	84.75 145	84.46 210	93.40 147	75.76 143	97.40 184	77.59 228	94.52 105	94.12 203

RPMNet		83.18 274	80.87 280	90.12 192	90.58 290	79.34 206	85.24 328	90.78 301	71.44 325	85.55 171	82.97 333	70.87 207	95.61 282	61.01 332	89.36 183	95.40 145

no-one		61.56 328	56.58 330	76.49 334	67.80 361	62.76 343	78.13 350	86.11 345	63.16 347	43.24 356	64.70 354	26.12 358	88.95 342	50.84 344	29.15 356	77.77 351

MVSTER		88.84 130	88.29 126	90.51 170	92.95 207	80.44 170	93.73 191	95.01 182	84.66 147	87.15 134	93.12 161	72.79 184	97.21 204	87.86 88	87.36 217	93.87 218

CPTT-MVS		91.99 60	91.80 59	92.55 90	98.24 24	81.98 130	96.76 19	96.49 73	81.89 221	90.24 87	96.44 52	78.59 105	98.61 86	89.68 69	97.85 53	97.06 92

GBi-Net		87.26 189	85.98 197	91.08 146	94.01 169	83.10 100	95.14 82	94.94 185	83.57 171	84.37 213	91.64 214	66.59 270	96.34 258	78.23 222	85.36 231	93.79 223

PVSNet_Blended_VisFu		91.38 71	90.91 73	92.80 81	96.39 73	83.17 99	94.87 101	96.66 64	83.29 181	89.27 97	94.46 114	80.29 87	99.17 35	87.57 92	95.37 91	96.05 124

PVSNet_BlendedMVS		89.98 98	89.70 92	90.82 157	96.12 83	81.25 145	93.92 179	96.83 48	83.49 175	89.10 99	92.26 193	81.04 81	98.85 73	86.72 107	87.86 212	92.35 284

UnsupCasMVSNet_eth		80.07 300	78.27 302	85.46 309	85.24 336	72.63 307	88.45 306	94.87 191	82.99 196	71.64 334	88.07 297	56.34 322	91.75 335	73.48 264	63.36 348	92.01 290

UnsupCasMVSNet_bld		76.23 313	73.27 315	85.09 313	83.79 341	72.92 300	85.65 327	93.47 234	71.52 324	68.84 338	79.08 344	49.77 337	93.21 324	66.81 309	60.52 350	89.13 332

PVSNet_Blended		90.73 82	90.32 81	91.98 113	96.12 83	81.25 145	92.55 240	96.83 48	82.04 215	89.10 99	92.56 181	81.04 81	98.85 73	86.72 107	95.91 82	95.84 131

FMVSNet5		81.52 289	79.60 293	87.27 285	91.17 266	77.95 249	91.49 265	92.26 254	76.87 280	76.16 308	87.91 300	51.67 334	92.34 330	67.74 303	81.16 279	91.52 298

test1		87.26 189	85.98 197	91.08 146	94.01 169	83.10 100	95.14 82	94.94 185	83.57 171	84.37 213	91.64 214	66.59 270	96.34 258	78.23 222	85.36 231	93.79 223

new_pmnet		72.15 319	70.13 321	78.20 328	82.95 344	65.68 337	83.91 336	82.40 354	62.94 348	64.47 345	79.82 343	42.85 348	86.26 349	57.41 339	74.44 320	82.65 347

FMVSNet3		87.40 186	86.11 192	91.30 138	93.79 182	83.64 88	94.20 157	94.81 195	83.89 162	84.37 213	91.87 210	68.45 251	96.56 245	78.23 222	85.36 231	93.70 232

dp		81.47 290	80.23 285	85.17 312	89.92 306	65.49 339	86.74 317	90.10 311	76.30 285	81.10 265	87.12 309	62.81 291	95.92 272	68.13 301	79.88 302	94.09 206

FMVSNet2		87.19 195	85.82 202	91.30 138	94.01 169	83.67 87	94.79 106	94.94 185	83.57 171	83.88 224	92.05 204	66.59 270	96.51 248	77.56 229	85.01 235	93.73 230

FMVSNet1		85.85 223	84.11 239	91.08 146	92.81 210	83.10 100	95.14 82	94.94 185	81.64 232	82.68 244	91.64 214	59.01 315	96.34 258	75.37 248	83.78 244	93.79 223

N_pmnet		68.89 323	68.44 324	70.23 339	89.07 314	28.79 368	88.06 308	19.50 370	69.47 334	71.86 333	84.93 325	61.24 303	91.75 335	54.70 340	77.15 314	90.15 323

cascas		86.43 213	84.98 218	90.80 158	92.10 222	80.92 157	90.24 278	95.91 113	73.10 313	83.57 234	88.39 291	65.15 282	97.46 164	84.90 121	91.43 148	94.03 210

BH-RMVSNet		88.37 140	87.48 140	91.02 150	95.28 118	79.45 196	92.89 230	93.07 239	85.45 129	86.91 139	94.84 103	70.35 217	97.76 146	73.97 260	94.59 103	95.85 130

UGNet		89.95 100	88.95 109	92.95 76	94.51 153	83.31 96	95.70 50	95.23 172	89.37 39	87.58 129	93.94 133	64.00 287	98.78 78	83.92 136	96.31 79	96.74 103
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		89.60 107	88.92 110	91.67 128	95.47 111	81.15 150	92.38 245	94.78 196	83.11 185	89.06 101	94.32 117	78.67 104	96.61 244	81.57 171	90.89 162	97.24 81

XXY-MVS		87.65 167	86.85 161	90.03 201	92.14 220	80.60 166	93.76 188	95.23 172	82.94 197	84.60 206	94.02 128	74.27 161	95.49 290	81.04 176	83.68 247	94.01 212

sss		88.93 129	88.26 128	90.94 156	94.05 167	80.78 161	91.71 260	95.38 159	81.55 235	88.63 104	93.91 137	75.04 154	95.47 291	82.47 155	91.61 147	96.57 106

Test_1112_low_res		87.65 167	86.51 182	91.08 146	94.94 135	79.28 210	91.77 257	94.30 209	76.04 288	83.51 235	92.37 186	77.86 114	97.73 150	78.69 218	89.13 194	96.22 114

1112_ss		88.42 138	87.33 144	91.72 125	94.92 136	80.98 154	92.97 228	94.54 201	78.16 272	83.82 226	93.88 138	78.78 102	97.91 141	79.45 209	89.41 181	96.26 113

ab-mvs-re		7.82 346	10.43 347	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	93.88 138	0.00 374	0.00 369	0.00 366	0.00 367	0.00 367

ab-mvs		89.41 116	88.35 122	92.60 87	95.15 128	82.65 119	92.20 250	95.60 136	83.97 161	88.55 105	93.70 146	74.16 166	98.21 110	82.46 156	89.37 182	96.94 97

TR-MVS		86.78 203	85.76 203	89.82 208	94.37 158	78.41 238	92.47 242	92.83 242	81.11 241	86.36 150	92.40 184	68.73 245	97.48 162	73.75 263	89.85 176	93.57 245

MDTV_nov1_ep13_2view						55.91 354	87.62 314		73.32 311	84.59 207		70.33 218		74.65 255		95.50 141

MDTV_nov1_ep13			83.56 252		91.69 233	69.93 327	87.75 312	91.54 278	78.60 265	84.86 203	88.90 282	69.54 226	96.03 267	70.25 278	88.93 196

MIMVSNet1		79.38 305	77.28 305	85.69 307	86.35 333	73.67 296	91.61 264	92.75 245	78.11 273	72.64 330	88.12 296	48.16 341	91.97 334	60.32 333	77.49 312	91.43 301

MIMVSNet		82.59 278	80.53 281	88.76 245	91.51 236	78.32 240	86.57 319	90.13 310	79.32 255	80.70 270	88.69 287	52.98 333	93.07 328	66.03 316	88.86 197	94.90 166

IterMVS-LS		88.36 141	87.91 135	89.70 216	93.80 180	78.29 242	93.73 191	95.08 180	85.73 122	84.75 204	91.90 209	79.88 90	96.92 225	83.83 137	82.51 258	93.89 215
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet		89.45 113	88.51 117	92.29 103	93.62 185	83.61 90	93.01 225	94.68 198	81.95 217	87.82 125	93.24 156	78.69 103	96.99 218	80.34 191	93.23 131	96.28 112
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref															87.47 214

IterMVS		84.88 250	83.98 242	87.60 278	91.44 238	76.03 281	90.18 280	92.41 251	83.24 183	81.06 267	90.42 263	66.60 269	94.28 314	79.46 208	80.98 287	92.48 278
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon		91.95 61	91.28 64	93.96 48	98.33 20	85.92 45	94.66 119	96.66 64	82.69 205	90.03 91	95.82 75	82.30 64	99.03 50	84.57 125	96.48 77	96.91 98

MVS_111021_LR		92.47 56	92.29 56	92.98 75	95.99 93	84.43 72	93.08 221	96.09 98	88.20 69	91.12 78	95.72 79	81.33 79	97.76 146	91.74 47	97.37 61	96.75 102

DP-MVS		87.25 191	85.36 212	92.90 78	97.65 36	83.24 97	94.81 105	92.00 262	74.99 297	81.92 256	95.00 96	72.66 186	99.05 46	66.92 307	92.33 143	96.40 108

ACMMP++															88.01 211

HQP-MVS		89.80 104	89.28 102	91.34 137	94.17 163	81.56 134	94.39 137	96.04 104	88.81 51	85.43 182	93.97 131	73.83 171	97.96 137	87.11 101	89.77 177	94.50 189

QAPM		89.51 110	88.15 129	93.59 58	94.92 136	84.58 62	96.82 18	96.70 60	78.43 267	83.41 237	96.19 63	73.18 180	99.30 29	77.11 234	96.54 75	96.89 99

Vis-MVSNet		91.75 64	91.23 66	93.29 60	95.32 117	83.78 83	96.14 32	95.98 107	89.89 29	90.45 85	96.58 46	75.09 153	98.31 104	84.75 123	96.90 66	97.78 66
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet		73.70 317	72.20 317	78.18 330	91.81 228	56.42 352	82.94 342	82.58 353	55.24 351	68.88 337	66.48 352	55.32 326	95.13 304	58.12 337	88.42 205	83.01 346

IS-MVSNet		91.43 70	91.09 70	92.46 94	95.87 98	81.38 143	96.95 9	93.69 231	89.72 34	89.50 95	95.98 69	78.57 106	97.77 145	83.02 145	96.50 76	98.22 35

HyFIR lowres test		88.09 149	86.81 163	91.93 116	96.00 92	80.63 164	90.01 282	95.79 123	73.42 310	87.68 128	92.10 200	73.86 170	97.96 137	80.75 182	91.70 146	97.19 85

EPMVS		83.90 267	82.70 268	87.51 280	90.23 300	72.67 305	88.62 303	81.96 355	81.37 239	85.01 195	88.34 292	66.31 273	94.45 311	75.30 249	87.12 220	95.43 144

PAPM_NR		91.22 75	90.78 76	92.52 92	97.60 37	81.46 140	94.37 141	96.24 88	86.39 111	87.41 131	94.80 104	82.06 71	98.48 92	82.80 150	95.37 91	97.61 70

TAMVS		89.21 121	88.29 126	91.96 114	93.71 183	82.62 120	93.30 211	94.19 211	82.22 210	87.78 126	93.94 133	78.83 101	96.95 223	77.70 227	92.98 136	96.32 110

PAPR		90.02 97	89.27 103	92.29 103	95.78 99	80.95 156	92.68 235	96.22 89	81.91 219	86.66 144	93.75 145	82.23 65	98.44 96	79.40 213	94.79 98	97.48 75

RPSCF		85.07 243	84.27 237	87.48 283	92.91 208	70.62 323	91.69 262	92.46 250	76.20 287	82.67 245	95.22 90	63.94 288	97.29 195	77.51 230	85.80 228	94.53 186

Vis-MVSNet (Re-imp)		89.59 108	89.44 97	90.03 201	95.74 100	75.85 282	95.61 57	90.80 300	87.66 84	87.83 124	95.40 86	76.79 120	96.46 252	78.37 219	96.73 69	97.80 64

test_0402		81.30 293	79.17 297	87.67 277	93.19 197	78.17 245	92.98 227	91.71 269	75.25 294	76.02 312	90.31 264	59.23 314	96.37 256	50.22 345	83.63 248	88.47 339

MVS_111021_HR		93.45 39	93.31 38	93.84 51	96.99 57	84.84 57	93.24 216	97.24 21	88.76 54	91.60 71	95.85 74	86.07 31	98.66 81	91.91 43	98.16 45	98.03 50

CSCG		93.23 49	93.05 43	93.76 56	98.04 31	84.07 78	96.22 29	97.37 11	84.15 158	90.05 90	95.66 80	87.77 13	99.15 38	89.91 67	98.27 42	98.07 46

PatchMatch-RL		86.77 205	85.54 205	90.47 173	95.88 96	82.71 117	90.54 275	92.31 252	79.82 252	84.32 217	91.57 221	68.77 244	96.39 255	73.16 265	93.48 125	92.32 285

API-MVS		90.66 84	90.07 86	92.45 95	96.36 74	84.57 63	96.06 36	95.22 174	82.39 207	89.13 98	94.27 122	80.32 86	98.46 94	80.16 195	96.71 70	94.33 196

Test By Simon												80.02 89

TDRefinement		79.81 302	77.34 304	87.22 290	79.24 351	75.48 285	93.12 218	92.03 261	76.45 282	75.01 317	91.58 219	49.19 340	96.44 253	70.22 280	69.18 339	89.75 325

USDC		82.76 275	81.26 276	87.26 286	91.17 266	74.55 287	89.27 293	93.39 235	78.26 270	75.30 316	92.08 201	54.43 330	96.63 241	71.64 270	85.79 229	90.61 319

EPP-MVSNet		91.70 67	91.56 61	92.13 109	95.88 96	80.50 169	97.33 3	95.25 168	86.15 115	89.76 92	95.60 81	83.42 55	98.32 103	87.37 96	93.25 130	97.56 73

PMMVS		85.71 234	84.96 220	87.95 273	88.90 316	77.09 271	88.68 302	90.06 312	72.32 320	86.47 145	90.76 253	72.15 193	94.40 312	81.78 169	93.49 123	92.36 283

PAPM		86.68 206	85.39 211	90.53 163	93.05 201	79.33 209	89.79 286	94.77 197	78.82 261	81.95 255	93.24 156	76.81 119	97.30 192	66.94 305	93.16 132	94.95 165

ACMMP		93.24 48	92.88 49	94.30 42	98.09 29	85.33 54	96.86 17	97.45 7	88.33 64	90.15 89	97.03 27	81.44 77	99.51 14	90.85 61	95.74 84	98.04 49
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		89.07 124	87.98 132	92.34 100	96.87 59	84.78 59	94.08 166	93.24 236	81.41 238	84.46 210	95.13 94	75.57 146	96.62 242	77.21 232	93.84 117	95.61 140

PatchmatchNet		85.85 223	84.70 228	89.29 235	91.76 229	75.54 284	88.49 304	91.30 284	81.63 233	85.05 194	88.70 286	71.71 194	96.24 261	74.61 256	89.05 195	96.08 121
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS		93.89 32	93.65 34	94.62 31	96.84 60	86.43 32	96.69 21	97.49 5	85.15 136	93.56 31	96.28 56	85.60 35	99.31 28	92.45 25	98.79 11	98.12 43

F-COLMAP		87.95 155	86.80 164	91.40 135	96.35 75	80.88 158	94.73 110	95.45 153	79.65 254	82.04 254	94.61 109	71.13 203	98.50 91	76.24 242	91.05 156	94.80 171

ANet_high		58.88 330	54.22 333	72.86 337	56.50 367	56.67 351	80.75 346	86.00 346	73.09 314	37.39 358	64.63 355	22.17 361	79.49 359	43.51 354	23.96 360	82.43 348

PNet_i23d		50.48 335	47.18 336	60.36 346	68.59 359	44.56 363	72.75 357	72.61 363	43.92 356	33.91 360	60.19 357	6.16 367	73.52 360	38.50 357	28.04 357	63.01 355

wuyk23d		21.27 343	20.48 344	23.63 354	68.59 359	36.41 366	49.57 362	6.85 371	9.37 363	7.89 366	4.46 368	4.03 370	31.37 365	17.47 363	16.07 363	3.12 363

OMC-MVS		91.23 74	90.62 77	93.08 70	96.27 76	84.07 78	93.52 202	95.93 110	86.95 100	89.51 94	96.13 66	78.50 107	98.35 100	85.84 112	92.90 137	96.83 100

MG-MVS		91.77 63	91.70 60	92.00 112	97.08 56	80.03 178	93.60 200	95.18 175	87.85 76	90.89 80	96.47 51	82.06 71	98.36 98	85.07 117	97.04 65	97.62 69

wuykxyi23d		50.55 334	44.13 337	69.81 340	56.77 365	54.58 355	73.22 355	80.78 356	39.79 359	22.08 365	46.69 361	4.03 370	79.71 358	47.65 348	26.13 358	75.14 352

AdaColmap		89.89 103	89.07 106	92.37 99	97.41 44	83.03 103	94.42 134	95.92 111	82.81 201	86.34 151	94.65 108	73.89 169	99.02 53	80.69 183	95.51 87	95.05 152

uanet		0.00 348	0.00 349	0.00 357	0.00 372	0.00 372	0.00 363	0.00 374	0.00 367	0.00 369	0.00 369	0.00 374	0.00 369	0.00 366	0.00 367	0.00 367

ITE_SJBPF				88.24 267	91.88 225	77.05 272		92.92 240	85.54 127	80.13 279	93.30 153	57.29 320	96.20 262	72.46 268	84.71 237	91.49 299

DeepMVS_CX				56.31 348	74.23 354	51.81 357		56.67 368	44.85 355	48.54 355	75.16 346	27.87 357	58.74 364	40.92 355	52.22 352	58.39 358

TinyColmap		79.76 303	77.69 303	85.97 305	91.71 231	73.12 299	89.55 287	90.36 306	75.03 296	72.03 332	90.19 265	46.22 345	96.19 263	63.11 326	81.03 283	88.59 336

MAR-MVS		90.30 92	89.37 99	93.07 72	96.61 65	84.48 67	95.68 51	95.67 130	82.36 209	87.85 119	92.85 171	76.63 123	98.80 77	80.01 196	96.68 71	95.91 127
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		80.37 299	79.07 299	84.27 319	86.64 332	69.87 328	89.39 292	91.05 293	76.38 283	74.97 318	90.00 268	47.85 342	94.25 315	74.55 257	80.82 289	88.69 335

MSDG		84.86 251	83.09 262	90.14 191	93.80 180	80.05 176	89.18 296	93.09 238	78.89 259	78.19 289	91.91 208	65.86 280	97.27 196	68.47 296	88.45 203	93.11 261

LS3D		87.89 156	86.32 186	92.59 88	96.07 90	82.92 109	95.23 76	94.92 189	75.66 290	82.89 242	95.98 69	72.48 190	99.21 32	68.43 298	95.23 96	95.64 139

CLD-MVS		89.47 112	88.90 111	91.18 141	94.22 162	82.07 128	92.13 252	96.09 98	87.90 74	85.37 189	92.45 183	74.38 160	97.56 156	87.15 99	90.43 164	93.93 213
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS		64.63 327	62.55 327	70.88 338	70.80 356	56.71 350	84.42 332	84.42 350	51.78 353	49.57 353	81.61 338	23.49 360	81.48 356	40.61 356	76.25 316	74.46 353

Gipuma		57.99 331	54.91 332	67.24 344	88.51 318	65.59 338	52.21 361	90.33 307	43.58 357	42.84 357	51.18 359	20.29 363	85.07 353	34.77 358	70.45 336	51.05 359
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015

High-resolution multi-view benchmark