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	courty.	delive.	electro	facade	kicker	meadow	office	pipes	playgr.	relief	relief.	terrace	terrai.

ACMH+	702.88 1	670.82 93	589.81 93	765.33 95	662.52 92	701.42 89	795.24 93	1698.33 105	598.81 100	226.55 89	403.02 85	187.13 84	786.82 97	724.80 99	646.56 92	422.52 89	866.95 97

PMVS	743.55 2	836.66 98	637.90 95	1068.55 108	1306.50 116	875.12 101	1166.70 114	2629.00 112	512.24 90	196.22 84	282.69 79	237.15 91	597.87 85	842.47 101	765.54 100	514.99 98	950.09 99
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
IB-MVS	750.90 3	552.99 80	511.38 84	601.53 80	606.02 88	735.75 92	688.75 90	1183.86 93	436.09 83	210.63 88	397.40 84	233.85 90	551.05 83	521.77 82	533.78 82	368.88 83	721.05 88
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
ACMH	935.68 4	948.23 101	857.00 101	1054.67 107	946.00 103	970.00 105	1125.00 112	2467.00 110	823.00 106	330.00 101	622.00 105	211.00 89	891.00 104	970.00 104	1061.00 111	569.00 101	1342.00 111
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMM	1129.18 5	1047.56 108	912.90 102	1204.67 109	1040.21 111	1016.71 112	1105.32 110	2918.67 115	813.91 104	327.22 100	665.34 106	267.72 100	1192.58 113	1091.35 112	991.88 104	643.99 107	1543.40 118
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMP	1170.86 6	1091.37 110	943.23 104	1264.21 111	1112.10 113	1138.94 114	1276.90 116	2675.36 114	989.62 109	426.15 111	742.77 109	349.09 113	1454.51 118	1047.36 111	969.90 103	640.22 106	1364.94 113
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
OpenMVS	2049.89 7	1895.92 115	1721.29 116	2099.67 117	2064.00 121	2419.00 125	2138.00 123	4572.00 124	1541.00 123	548.00 114	937.00 114	580.00 119	1983.00 120	1971.00 123	1993.00 121	1293.00 126	2608.00 122

DeepC-MVS_fast	2081.98 8	1311.87 113	1172.50 115	1474.47 114	1411.78 117	1397.23 119	1519.03 119	3401.40 119	1201.29 117	417.90 109	801.95 111	976.25 141	1409.37 116	1114.52 113	1201.12 115	687.33 109	1515.14 117
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
3Dnovator	2220.89 9	2303.77 123	2037.00 125	2615.00 126	2617.00 131	2967.00 132	2616.00 126	5882.00 134	1928.00 129	589.00 116	907.00 113	528.00 118	2443.00 131	2370.00 131	2392.00 132	1543.00 136	3167.00 129

CMPMVS	2507.20 10	2083.60 117	1983.13 121	2200.81 119	2582.70 130	3097.30 133	2332.10 124	4364.50 122	1390.00 119	653.68 119	997.75 116	742.65 129	1880.20 119	2298.80 129	2413.60 133	1391.70 130	2941.80 127
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
DeepPCF-MVS	3033.31 11	2362.79 125	2183.15 127	2572.38 124	2349.28 127	2383.16 124	2740.92 131	5212.97 127	2043.02 130	751.44 122	1466.47 130	1327.42 154	2904.33 134	2573.45 136	2227.77 126	1475.33 131	3260.73 131

3Dnovator+	3173.67 12	2938.77 134	2519.43 130	3428.00 136	3256.00 139	3708.00 142	3443.00 138	7516.00 141	2525.00 137	1121.00 146	972.00 115	925.00 138	3192.00 138	2899.00 139	2897.00 143	2040.00 147	3710.00 140

PCF-MVS	3738.24 13	2129.60 118	1746.89 117	2576.10 125	2258.22 126	2263.67 123	2650.06 130	6361.78 136	1676.15 125	695.66 120	1209.77 124	737.88 126	2237.28 121	2083.02 125	1835.31 117	1253.58 125	2422.45 120
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
COLMAP_ROB	3798.28 14	2690.62 132	2704.29 139	2674.67 127	3138.00 135	3522.00 141	3826.00 145	3219.00 117	2702.00 141	1138.00 149	2260.00 148	1212.00 153	2968.00 137	2936.00 143	2571.00 136	1759.00 145	3727.00 141
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
PLC	4785.50 15	3275.54 141	3030.86 143	3561.00 139	4093.00 148	4596.00 147	5174.00 154	4267.00 121	3570.00 149	1495.00 155	2940.00 151	1594.00 156	3947.00 145	3817.00 148	3343.00 147	2390.00 149	1356.00 112
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
TAPA-MVS	5463.68 16	2764.21 133	2434.28 129	3149.14 135	3645.15 144	3257.60 137	3452.71 139	6526.32 137	2591.85 139	651.36 118	1964.77 146	947.44 139	2924.41 135	2523.36 134	2452.68 134	1694.86 142	3302.28 132
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
DeepC-MVS	5581.15 17	4824.92 147	5020.53 148	4596.70 147	4714.52 151	3205.14 135	3108.50 134	10234.20 152	3823.34 151	1885.23 158	9002.42 155	2045.34 160	4715.23 151	7652.65 152	3993.41 148	2922.51 152	5421.41 149
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MVE	11086.50 18	13278.69 152	12303.57 153	14416.33 154	9890.00 157	17107.00 160	4634.00 150	59884.00 159	3666.00 150	966.00 130	1792.00 140	896.00 137	5680.00 152	20677.00 157	23030.00 156	5444.00 157	18957.00 155
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
LTVRE_ROB	38377.89 19	49656.08 155	18936.71 155	85495.33 157	306852.00 163	22526.00 162	29206.00 162	112098.00 161	30022.00 158	17348.00 164	2824.00 150	11239.00 164	29457.00 158	20569.00 156	19941.00 155	18011.00 160	25436.00 157
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
ECVR-MVS		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

ECVR-MVS1		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

DVP-MVS++.		3961.71 144	3092.38 144	4975.92 148	4850.81 153	5691.32 151	5760.96 155	12294.80 153	2980.85 147	1135.72 148	1840.86 143	949.63 140	4197.95 147	3019.10 146	2873.21 142	1615.27 139	4291.72 146

GeoE		20.05 50	18.83 50	21.47 51	25.60 51	29.60 52	22.50 51	31.20 51	19.10 52	8.30 50	13.50 52	9.40 51	17.80 51	14.10 50	17.50 50	23.40 52	28.60 52

test_method		18.19 49	15.64 49	21.17 50	19.00 50	22.00 51	22.50 51	38.00 52	15.50 51	7.50 49	13.00 51	7.00 50	19.00 52	15.50 51	15.50 49	21.00 51	21.00 51

pmnet_mix02		659.48 92	547.83 86	789.74 96	720.05 94	846.87 100	740.59 91	2153.63 109	456.15 88	191.24 83	336.49 82	200.39 87	511.90 81	608.74 89	634.29 91	421.05 88	751.91 89

RE-MVS-def										610.10 117

SED-MVS		3539.47 142	2909.05 142	4274.95 146	4528.93 150	4986.51 149	5003.31 153	8985.31 148	2904.53 146	1294.24 153	1839.12 142	1003.69 148	4135.17 146	2926.32 142	2897.04 144	1702.75 143	3806.13 143

xxxxxxxxxxxxxcwj		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

SF-MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

9.14												0.00 1

uanet_test		1000.00 104	1000.00 108	1000.00 103	1000.00 107	1000.00 108	1000.00 106	1000.00 87	1000.00 112	1000.00 135	1000.00 119	1000.00 144	1000.00 108	1000.00 107	1000.00 107	1000.00 116	1000.00 105

ET-MVSNet_ETH3D		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

UniMVSNet_ETH3D		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

EIA-MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

ETV-MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

CS-MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

DVP-MVS		3258.34 140	2529.80 131	4108.31 144	4005.62 147	4693.14 148	4737.88 151	10195.40 151	2408.38 135	941.44 129	1505.82 131	734.32 125	3438.27 143	2449.15 132	2386.04 131	1331.25 128	3531.75 138
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
SR-MVS					610.10 89			610.10 76				610.10 120

DPM-MVS		3051.54 135	2661.57 136	3506.50 137	3532.00 142	3332.00 139	3744.00 143	7839.00 144	2772.00 142	985.00 131	1919.00 144	738.00 127	3319.00 139	2901.00 140	2715.00 138	1620.00 140	4254.00 144

thisisatest0530		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

Anonymous202405211			10000000.00 158		10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161		10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

DCV-MVSNet		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

tttt0517		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

our_test_3					9999.00 158	99.00 60	99.00 59

thisisatest0515		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

SMA-MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1
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
DPE-MVS		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part1		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

thres100view900		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

tfpnnormal		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

tfpn200view9		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

CHOSEN 280x420		2225.10 119	1992.66 122	2496.28 120	2192.10 123	2641.81 127	2621.41 127	5345.34 128	2116.46 131	1002.26 139	1683.84 134	837.43 130	2338.65 123	1920.94 120	2020.28 122	1477.92 132	2727.86 123

CANet		100.44 55	93.07 55	109.04 56	111.90 58	131.06 63	119.40 60	222.42 64	80.48 57	36.93 56	70.80 57	40.92 59	89.90 57	100.59 63	101.42 56	73.68 61	126.25 57

Fast-Effi-MVS+-dtu		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

Effi-MVS+-dtu		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

CANet_DTU		100.44 55	93.07 55	109.04 56	111.90 58	131.06 63	119.40 60	222.42 64	80.48 57	36.93 56	70.80 57	40.92 59	89.90 57	100.59 63	101.42 56	73.68 61	126.25 57

MVS_0304		100.44 55	93.07 55	109.04 56	111.90 58	131.06 63	119.40 60	222.42 64	80.48 57	36.93 56	70.80 57	40.92 59	89.90 57	100.59 63	101.42 56	73.68 61	126.25 57

MSP-MVS		3241.28 139	2825.26 141	3726.65 142	3945.31 146	4305.03 145	4267.51 149	6962.25 139	2896.37 145	1068.15 144	1824.25 141	1061.55 151	4307.30 148	3013.40 145	3171.41 145	1809.38 146	3504.79 137
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
IterMVS-SCA-FT		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

TSAR-MVS + MP.		4216.58 145	4674.68 147	3682.13 141	3752.63 145	4315.48 146	4264.77 148	7782.51 143	2583.81 138	1125.68 147	16722.30 158	882.60 135	3589.10 144	2523.80 135	2486.45 135	1578.08 138	3208.34 130
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
OPM-MVS		3051.54 135	2661.57 136	3506.50 137	3532.00 142	3332.00 139	3744.00 143	7839.00 144	2772.00 142	985.00 131	1919.00 144	738.00 127	3319.00 139	2901.00 140	2715.00 138	1620.00 140	4254.00 144
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMMP_NAP		119.64 66	106.58 59	134.88 67	123.82 62	127.44 61	145.38 64	298.43 72	116.16 71	43.72 61	77.82 61	29.30 56	131.24 68	117.82 70	106.21 60	66.69 59	171.29 71

ambc			999.00 106		999.00 105	999.00 106	999.00 104		999.00 110	999.00 133	999.00 117	999.00 142	999.00 106	999.00 105	999.00 105	999.00 114	999.00 103

zzz-MVS		119.64 66	106.58 59	134.88 67	123.82 62	127.44 61	145.38 64	298.43 72	116.16 71	43.72 61	77.82 61	29.30 56	131.24 68	117.82 70	106.21 60	66.69 59	171.29 71

CS-MVS-test		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

Effi-MVS+		0.53 27	0.53 27	0.53 28	0.53 28	0.53 28	0.53 28	0.53 28	0.53 28	0.53 28	0.53 28	0.53 29	0.53 28	0.53 27	0.53 27	0.53 28	0.53 28

new-patchmatchnet		712.65 94	632.59 94	806.05 99	787.79 101	936.25 104	882.47 101	1795.72 106	528.60 92	244.29 90	471.90 93	257.36 93	681.47 89	705.16 98	659.05 97	444.55 90	869.82 98

pmmvs6		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

pmmvs5		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

Fast-Effi-MVS+		0.41 26	0.41 26	0.41 27	0.41 27	0.41 27	0.41 27	0.41 27	0.41 27	0.41 27	0.41 27	0.41 28	0.41 27	0.41 26	0.41 26	0.41 27	0.41 27

Anonymous20231211		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

pmmvs-eth3d		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

GG-mvs-BLEND		557.53 82	503.49 80	620.58 83	485.90 80	370.41 78	267.30 77	710.53 78	454.42 84	785.72 123	491.23 96	326.12 105	881.92 100	538.27 85	650.05 93	592.08 102	693.94 83

Anonymous20231206		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

MTAPA										41.98 60		28.43 55

MTMP										10000000.00 166		31.71 58

gm-plane-assit		551.84 79	503.49 80	608.24 82	411.90 76	370.41 78	267.30 77	710.53 78	454.42 84	785.72 123	491.23 96	326.12 105	881.92 100	538.27 85	650.05 93	592.08 102	693.94 83

train_agg		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

gg-mvs-nofinetune		557.53 82	503.49 80	620.58 83	485.90 80	370.41 78	267.30 77	710.53 78	454.42 84	785.72 123	491.23 96	326.12 105	881.92 100	538.27 85	650.05 93	592.08 102	693.94 83

SCA		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

MS-PatchMatch		438.85 74	388.71 74	497.33 76	479.00 79	527.00 84	558.00 85	988.00 84	379.00 79	174.00 82	278.00 78	162.00 82	494.00 80	418.00 75	412.00 74	291.00 78	545.00 79

Patchmatch-RL test							10000000.00 165

tmp_tt				299.50 73	365.00 75	54.00 57	649.00 88	241.00 68	159.00 73	204.00 86	479.00 94	308.00 103	243.00 74	246.00 73	82.00 55	95.00 75

canonicalmvs		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

anonymousdsp		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

v144192		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

v1921920		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

FC-MVSNet-train		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

UA-Net		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

v1192		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

FC-MVSNet-test		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

v1144		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

sosnet-low-res		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

HFP-MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

v148		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

sosnet		1000.00 104	1000.00 108	1000.00 103	1000.00 107	1000.00 108	1000.00 106	1000.00 87	1000.00 112	1000.00 135	1000.00 119	1000.00 144	1000.00 108	1000.00 107	1000.00 107	1000.00 116	1000.00 105

v7n		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

DI_MVS_plusplus_trai		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

HPM-MVS++		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

XVS					52.20 53	52.20 54	52.20 54			52.20 63		52.20 73				52.20 56

v1240		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

pm-mvs1		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

X-MVStestdata					52.20 53	52.20 54	52.20 54			52.20 63		52.20 73				52.20 56

X-MVS		52.20 52	52.20 52	52.20 53	52.20 53	52.20 54	52.20 54	52.20 53	52.20 54	52.20 63	52.20 54	52.20 73	52.20 56	52.20 53	52.20 52	52.20 56	52.20 56

v8		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

v10		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

v2v482		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

V42		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

SD-MVS		2324.36 124	1910.97 119	2806.65 132	2945.31 134	3305.03 138	3267.51 135	5962.25 135	1896.37 128	848.15 128	1224.25 125	661.55 123	2707.30 133	1913.40 119	1871.41 118	1109.38 121	2504.79 121
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		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

MSLP-MVS++		993.91 102	732.21 98	1299.24 112	1631.22 119	1345.26 117	1480.05 118	2524.20 111	735.65 102	463.57 113	499.89 100	302.78 102	1292.66 114	675.99 96	612.79 84	403.71 87	953.11 101

APDe-MVS		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

TSAR-MVS + COLMAP		6088.23 148	5315.97 149	6989.21 150	6522.51 154	8025.15 156	7938.31 157	15276.20 154	5401.97 154	1914.31 159	3802.65 153	1979.48 159	6704.11 153	5217.07 150	5137.16 150	3579.82 154	7648.29 151

CVMVSNet		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

TSAR-MVS + ACMM		3184.92 137	2679.45 138	3774.64 143	3302.51 140	4168.07 144	4256.74 147	8947.31 147	2634.53 140	1026.25 143	1723.72 139	1043.87 150	3387.29 141	2794.29 137	2687.41 137	1727.73 144	3704.25 139

pmmvs4		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

EU-MVSNet		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

test-LLR		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

TESTMET0.1,1		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

test-mter		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

ACMMPR		1265.65 112	1083.59 113	1478.06 115	1441.06 118	1438.61 120	1540.68 120	3284.05 118	1219.68 118	458.81 112	803.22 112	346.91 112	1421.66 117	1126.11 114	1150.51 113	722.08 111	1500.09 116

testgi		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

test20.03		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

thres600view7		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

ADS-MVSNet		452.36 75	406.02 75	506.42 79	534.76 85	628.22 87	552.79 84	1009.99 91	333.98 75	149.26 78	246.67 75	149.01 80	447.03 78	465.35 79	501.18 79	344.69 82	517.75 77

MP-MVS		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

thres400		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

test123		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

thres200		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

test0.0.03 1		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

pmmvs3		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

EMVS		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

E-PMN		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

PGM-MVS		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

MCST-MVS		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

MVS_Test		654.54 86	583.51 87	737.40 89	721.80 95	822.10 94	808.60 94	1494.00 98	542.20 93	259.90 91	441.60 86	257.70 94	689.10 90	620.80 90	617.70 85	451.00 91	782.50 90

MDA-MVSNet-bldmvs		1.20 30	1.20 30	1.20 31	1.20 31	1.20 32	1.20 32	1.20 32	1.20 32	1.20 32	1.20 32	1.20 33	1.20 32	1.20 31	1.20 30	1.20 32	1.20 32

CDPH-MVS		6.66 46	6.66 46	6.66 47	6.66 47	6.66 48	6.66 48	6.66 48	6.66 48	6.66 48	6.66 48	6.66 49	6.66 48	6.66 47	6.66 46	6.66 48	6.66 48

casdiffmvs		654.54 86	583.51 87	737.40 89	721.80 95	822.10 94	808.60 94	1494.00 98	542.20 93	259.90 91	441.60 86	257.70 94	689.10 90	620.80 90	617.70 85	451.00 91	782.50 90

diffmvs		654.54 86	583.51 87	737.40 89	721.80 95	822.10 94	808.60 94	1494.00 98	542.20 93	259.90 91	441.60 86	257.70 94	689.10 90	620.80 90	617.70 85	451.00 91	782.50 90

baseline2		654.54 86	583.51 87	737.40 89	721.80 95	822.10 94	808.60 94	1494.00 98	542.20 93	259.90 91	441.60 86	257.70 94	689.10 90	620.80 90	617.70 85	451.00 91	782.50 90

baseline1		654.54 86	583.51 87	737.40 89	721.80 95	822.10 94	808.60 94	1494.00 98	542.20 93	259.90 91	441.60 86	257.70 94	689.10 90	620.80 90	617.70 85	451.00 91	782.50 90

PMMVS2		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

PM-MVS		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

PS-CasMVS		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

UniMVSNet_NR-MVSNet		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

PEN-MVS		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

TransMVSNet (Re)		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

DTE-MVSNet		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

DU-MVS		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

UniMVSNet (Re)		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

CP-MVSNet		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

WR-MVS_H		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

WR-MVS		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

NR-MVSNet		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

Baseline_NR-MVSNet		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

TranMVSNet+NR-MVSNet		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

TSAR-MVS + GP.		1239.27 111	1094.74 114	1407.89 113	1220.99 115	1845.47 122	1680.98 121	3191.81 116	1098.41 116	362.98 102	679.12 107	339.31 110	1323.06 115	1173.24 115	1093.83 112	667.49 108	1433.78 114

abl_6				0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1			0.00 1	0.00 1

mPP-MVS					10000000.00 164							10000000.00 167

SixPastTwentyTwo		210.90 71	189.75 71	235.58 72	225.41 74	284.88 77	267.17 76	485.88 75	164.28 74	76.51 76	137.62 73	76.69 76	214.49 73	206.28 72	208.00 72	144.02 76	250.52 73

LGP-MVS_train		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

baseline		654.54 86	583.51 87	737.40 89	721.80 95	822.10 94	808.60 94	1494.00 98	542.20 93	259.90 91	441.60 86	257.70 94	689.10 90	620.80 90	617.70 85	451.00 91	782.50 90

EPNet_dtu		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x2688		2225.10 119	1992.66 122	2496.28 120	2192.10 123	2641.81 127	2621.41 127	5345.34 128	2116.46 131	1002.26 139	1683.84 134	837.43 130	2338.65 123	1920.94 120	2020.28 122	1477.92 132	2727.86 123

EPNet		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
APD-MVS		1000000000.00 221	1000000000.00 223	1000000000.00 223	1000000000.00 230	1000000000.00 230	1000000000.00 231	1000000000.00 227	1000000000.00 227	1000000000.00 231	1000000000.00 226	1000000000.00 233	1000000000.00 226	1000000000.00 225	1000000000.00 224	1000000000.00 228	1000000000.00 225
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
CNVR-MVS		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

NCCC		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

CP-MVS		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

NP-MVS									10000000.00 161

EG-PatchMatch MVS		402.98 73	364.36 73	448.05 75	435.50 78	473.00 83	489.60 82	910.20 83	338.60 77	127.30 77	205.10 74	123.50 79	434.60 76	450.70 78	447.70 76	291.10 79	511.90 76

tpm cat1		2652.13 128	2606.66 133	2705.18 128	3151.86 136	6902.39 153	3612.17 140	5463.78 131	1457.76 120	391.31 104	1358.61 126	446.44 115	2360.09 126	2296.48 126	2290.90 128	1251.84 122	3494.04 134

SteuartSystems-ACMMP		2615.00 127	2242.57 128	3049.50 134	2828.00 133	2801.00 131	3323.00 137	6648.00 138	2491.00 136	1023.00 142	1605.00 132	697.00 124	2926.00 136	2502.00 133	2279.00 127	1549.00 137	3323.00 133
Skip Steuart: Steuart Systems R&D Blog.
CostFormer		2652.13 128	2606.66 133	2705.18 128	3151.86 136	6902.39 153	3612.17 140	5463.78 131	1457.76 120	391.31 104	1358.61 126	446.44 115	2360.09 126	2296.48 126	2290.90 128	1251.84 122	3494.04 134

CR-MVSNet		557.53 82	503.49 80	620.58 83	485.90 80	370.41 78	267.30 77	710.53 78	454.42 84	785.72 123	491.23 96	326.12 105	881.92 100	538.27 85	650.05 93	592.08 102	693.94 83

Patchmtry						1825.90 121	885.90 102	1405.90 97		1285.90 151

PatchT		878.42 100	785.05 100	987.36 101	1050.05 112	922.05 103	1111.05 111	677.05 77	950.05 108	1285.90 151	750.05 110	640.05 122	850.05 98	950.05 102	950.05 102	950.05 113	333.05 74

tpmrst		2688.71 131	2604.46 132	2787.00 131	2472.96 128	3190.36 134	3313.69 136	5003.06 126	1837.26 127	1097.38 145	1721.89 138	1012.20 149	2415.09 130	2970.27 144	2736.80 140	2419.79 150	4762.44 147

tpm		2652.13 128	2606.66 133	2705.18 128	3151.86 136	6902.39 153	3612.17 140	5463.78 131	1457.76 120	391.31 104	1358.61 126	446.44 115	2360.09 126	2296.48 126	2290.90 128	1251.84 122	3494.04 134

DELS-MVS		458.84 77	423.31 77	500.30 77	511.99 83	616.59 86	578.86 86	991.10 85	355.79 78	158.99 79	319.09 80	190.62 85	453.64 79	437.73 77	439.52 75	307.20 80	603.81 80
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
RPMNet		858.01 99	961.99 105	736.69 88	550.05 86	1120.24 113	1212.05 115	463.05 74	485.90 89	550.05 115	580.05 103	890.05 136	559.05 84	1485.90 116	1185.90 114	1085.90 120	985.90 102

MVSTER		834.63 97	737.03 99	948.49 100	988.86 104	1140.51 115	1129.34 113	1832.80 108	682.42 101	319.01 99	550.98 102	311.35 104	872.51 99	763.95 100	757.83 99	548.41 99	952.20 100

CPTT-MVS		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

GBi-Net		39.84 51	35.75 51	44.63 52	43.04 52	49.88 53	51.06 53	86.51 54	35.34 53	17.20 53	29.83 53	15.85 54	43.43 55	35.35 52	35.70 51	26.51 55	48.28 55

PVSNet_Blended_VisFu		129.22 68	115.76 68	144.92 69	140.60 71	162.80 74	166.50 73	281.20 69	114.70 61	55.50 66	96.20 63	51.80 70	140.60 70	114.70 67	114.70 69	85.10 65	155.40 61

PVSNet_BlendedMVS		129.22 68	115.76 68	144.92 69	140.60 71	162.80 74	166.50 73	281.20 69	114.70 61	55.50 66	96.20 63	51.80 70	140.60 70	114.70 67	114.70 69	85.10 65	155.40 61

PVSNet_Blended		129.22 68	115.76 68	144.92 69	140.60 71	162.80 74	166.50 73	281.20 69	114.70 61	55.50 66	96.20 63	51.80 70	140.60 70	114.70 67	114.70 69	85.10 65	155.40 61

FMVSNet5		116.86 59	110.47 61	124.32 60	131.47 64	157.41 67	150.67 66	199.64 57	115.30 64	56.61 69	97.70 66	51.77 63	117.26 61	77.26 54	113.14 62	90.25 68	160.68 64

test1		116.86 59	110.47 61	124.32 60	131.47 64	157.41 67	150.67 66	199.64 57	115.30 64	56.61 69	97.70 66	51.77 63	117.26 61	77.26 54	113.14 62	90.25 68	160.68 64

new_pmnet		75.00 53	74.67 53	75.39 54	85.42 56	96.03 58	98.77 57	173.23 55	69.57 55	36.19 54	56.93 55	117.43 77	32.98 53	85.38 61	68.41 53	25.74 53	28.95 53

FMVSNet3		116.86 59	110.47 61	124.32 60	131.47 64	157.41 67	150.67 66	199.64 57	115.30 64	56.61 69	97.70 66	51.77 63	117.26 61	77.26 54	113.14 62	90.25 68	160.68 64

dps		534.60 78	472.40 78	607.16 81	690.38 93	718.85 90	636.03 87	1231.66 94	422.74 81	198.65 85	325.68 81	194.97 86	512.90 82	509.81 81	513.65 80	373.33 84	621.11 81

FMVSNet2		116.86 59	110.47 61	124.32 60	131.47 64	157.41 67	150.67 66	199.64 57	115.30 64	56.61 69	97.70 66	51.77 63	117.26 61	77.26 54	113.14 62	90.25 68	160.68 64

FMVSNet1		116.86 59	110.47 61	124.32 60	131.47 64	157.41 67	150.67 66	199.64 57	115.30 64	56.61 69	97.70 66	51.77 63	117.26 61	77.26 54	113.14 62	90.25 68	160.68 64

N_pmnet		75.00 53	74.67 53	75.39 54	85.42 56	96.03 58	98.77 57	173.23 55	69.57 55	36.19 54	56.93 55	117.43 77	32.98 53	85.38 61	68.41 53	25.74 53	28.95 53

UGNet		100.44 55	93.07 55	109.04 56	111.90 58	131.06 63	119.40 60	222.42 64	80.48 57	36.93 56	70.80 57	40.92 59	89.90 57	100.59 63	101.42 56	73.68 61	126.25 57
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
DROMVSNet		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

MDTV_nov1_ep13_2view		9.99 47	9.99 47	9.99 48	9.99 48	9.99 49	9.99 49	9.99 49	9.99 49	9.99 51	9.99 49	9.99 52	9.99 49	9.99 48	9.99 47	9.99 49	9.99 49

MDTV_nov1_ep13		9.99 47	9.99 47	9.99 48	9.99 48	9.99 49	9.99 49	9.99 49	9.99 49	9.99 51	9.99 49	9.99 52	9.99 49	9.99 48	9.99 47	9.99 49	9.99 49

MIMVSNet1		116.86 59	110.47 61	124.32 60	131.47 64	157.41 67	150.67 66	199.64 57	115.30 64	56.61 69	97.70 66	51.77 63	117.26 61	77.26 54	113.14 62	90.25 68	160.68 64

MIMVSNet		116.86 59	110.47 61	124.32 60	131.47 64	157.41 67	150.67 66	199.64 57	115.30 64	56.61 69	97.70 66	51.77 63	117.26 61	77.26 54	113.14 62	90.25 68	160.68 64

IterMVS-LS		714.97 95	638.00 96	804.77 98	793.60 102	914.20 102	886.50 103	1612.70 104	588.30 99	285.30 98	491.20 95	278.40 101	759.20 96	677.40 97	681.30 98	491.30 97	835.20 96
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet		0.88 28	0.88 28	0.88 29	0.88 29	0.88 29	0.88 29	0.88 29	0.88 29	0.88 29	0.88 29	0.88 30	0.88 29	0.88 28	0.88 28	0.88 29	0.88 29
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
IterMVS		554.60 81	488.63 79	631.57 86	636.90 90	700.80 88	674.70 89	1271.10 96	430.50 82	207.10 87	370.50 83	202.70 88	611.80 86	534.20 84	545.30 83	387.80 85	636.40 82
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MVS_111021_LR		1055.24 109	916.36 103	1217.27 110	1129.93 114	1268.26 116	1313.88 117	2635.76 113	923.19 107	396.92 107	704.88 108	327.66 109	1136.32 112	965.38 103	946.95 101	690.83 110	1278.20 110

HQP-MVS		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

QAPM		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

Vis-MVSNet		2390.77 126	1976.57 120	2874.00 133	2644.00 132	3248.00 136	3040.00 133	7371.00 140	1627.00 124	421.00 110	1200.00 123	622.00 121	2251.00 122	2326.00 130	2052.00 125	1517.00 135	2761.00 126
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet		1975.98 116	1797.02 118	2184.76 118	2111.07 122	2443.03 126	2503.43 125	4063.71 120	1684.46 126	711.34 121	1456.05 129	848.70 134	2396.26 129	1900.93 118	1915.01 119	1322.75 127	2330.99 119

HyFIR lowres test		2225.10 119	1992.66 122	2496.28 120	2192.10 123	2641.81 127	2621.41 127	5345.34 128	2116.46 131	1002.26 139	1683.84 134	837.43 130	2338.65 123	1920.94 120	2020.28 122	1477.92 132	2727.86 123

EPMVS		999.00 103	999.00 106	999.00 102	999.00 105	999.00 106	999.00 104	999.00 86	999.00 110	999.00 133	999.00 117	999.00 142	999.00 106	999.00 105	999.00 105	999.00 114	999.00 103

TAMVS		0.88 28	0.88 28	0.88 29	0.88 29	0.88 29	0.88 29	0.88 29	0.88 29	0.88 29	0.88 29	0.88 30	0.88 29	0.88 28	0.88 28	0.88 29	0.88 29

IS_MVSNet		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

RPSCF		376.53 72	341.80 72	417.05 74	418.60 77	457.01 82	467.46 81	825.25 82	336.12 76	159.32 80	260.40 76	151.13 81	386.94 75	364.25 74	352.10 73	244.72 77	471.62 75

Vis-MVSNet (Re-imp)		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

MVS_111021_HR		3192.50 138	2773.91 140	3680.86 140	3515.58 141	3815.81 143	4020.82 146	7766.11 142	2775.23 144	1300.96 154	2221.19 147	1117.25 152	3420.01 142	2873.98 138	2835.60 141	2061.69 148	3778.31 142

CSCG		727.26 96	663.25 97	801.94 97	590.65 87	811.25 93	854.12 100	1805.32 107	816.43 105	388.25 103	612.42 104	345.37 111	621.61 87	507.46 80	471.55 78	551.65 100	1078.31 109

PatchMatch-RL		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

TDRefinement		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

USDC		1000.00 104	1000.00 108	1000.00 103	1000.00 107	1000.00 108	1000.00 106	1000.00 87	1000.00 112	1000.00 135	1000.00 119	1000.00 144	1000.00 108	1000.00 107	1000.00 107	1000.00 116	1000.00 105

EPP-MVSNet		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

PMMVS		10000000.00 157	10000000.00 158	10000000.00 159	10000000.00 164	10000000.00 165	10000000.00 165	10000000.00 162	10000000.00 161	10000000.00 166	10000000.00 161	10000000.00 167	10000000.00 161	10000000.00 160	10000000.00 159	10000000.00 163	10000000.00 160

ACMMP		9999.00 151	9999.00 152	9999.00 153	9999.00 158	9999.00 159	9999.00 160	9999.00 150	9999.00 156	9999.00 162	9999.00 156	9999.00 163	9999.00 156	9999.00 154	9999.00 153	9999.00 158	9999.00 154
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		17763.08 153	15907.71 154	19927.67 155	19334.00 160	22387.00 161	22896.00 161	38668.00 157	15772.00 157	7632.00 161	13229.00 157	7123.00 162	19334.00 157	15773.00 155	15700.00 154	11702.00 159	21370.00 156

PatchmatchNet		452.63 76	410.20 76	502.13 78	520.70 84	614.40 85	546.00 83	1018.80 92	379.00 79	167.50 81	277.10 77	169.40 83	437.10 77	437.10 76	457.50 77	322.70 81	536.90 78
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS		99999.00 156	99999.00 157	99999.00 158	99999.00 162	99999.00 164	99999.00 164	99999.00 160	99999.00 160	99999.00 165	99999.00 160	99999.00 166	99999.00 160	99999.00 159	99999.00 158	99999.00 162	99999.00 159

OMC-MVS		4439.92 146	3906.78 146	5061.92 149	4748.70 152	5679.38 150	5855.03 156	9923.00 149	4023.36 152	1740.95 157	1693.78 137	1693.78 158	4658.45 150	4254.77 149	4135.74 149	3445.36 153	5866.63 150

AdaColmap		2288.90 122	2080.73 126	2531.77 123	2485.98 129	2757.87 130	2974.47 132	4914.62 125	2255.54 134	804.63 127	1611.14 133	842.30 133	2657.83 132	2056.92 124	1960.62 120	1353.09 129	3080.73 128

DeepMVS_CX						1.00 31	1.00 31	1.00 31	1.00 31	1.00 31	1.00 31	1.00 32	1.00 31	1.00 30		1.00 31	1.00 31

TinyColmap		1000.00 104	1000.00 108	1000.00 103	1000.00 107	1000.00 108	1000.00 106	1000.00 87	1000.00 112	1000.00 135	1000.00 119	1000.00 144	1000.00 108	1000.00 107	1000.00 107	1000.00 116	1000.00 105

MAR-MVS		3961.62 143	3726.55 145	4235.86 145	4107.62 149	6522.83 152	4862.93 152	7956.64 146	3380.98 148	1665.13 156	3231.54 152	1650.34 157	4357.29 149	3198.61 147	3209.42 146	2465.52 151	4892.15 148
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020
MSDG		31705.85 154	29167.57 156	34667.17 156	44079.00 161	28314.00 163	44778.00 163	43648.00 158	31045.00 159	14849.00 163	26179.00 159	13752.00 165	38088.00 159	30859.00 158	30835.00 157	22561.00 161	43189.00 158

LS3D		7481.83 150	6596.02 151	8515.28 152	9871.71 156	9844.03 158	9225.16 159	18308.40 156	5364.90 153	1267.41 150	2381.61 149	1512.79 155	7225.72 154	8875.69 153	9516.28 152	5193.26 156	8676.83 152

CLD-MVS		6986.85 149	6222.57 150	7878.50 151	7707.00 155	8884.00 157	9025.00 158	15607.00 155	6148.00 155	2571.00 160	4822.00 154	2082.00 161	7875.00 155	6389.00 151	6449.00 151	4486.00 155	8784.00 153
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS		1356.65 114	1072.60 112	1688.04 116	1840.79 120	1397.01 118	1793.24 122	4397.86 123	804.66 103	408.78 108	538.65 101	407.36 114	894.84 105	1587.73 117	1286.38 116	792.73 112	1486.39 115

Gipuma		587.77 85	529.57 85	655.67 87	637.00 91	733.00 91	749.00 92	1245.00 95	525.00 91	269.00 97	445.00 92	253.00 92	637.00 88	525.00 83	525.00 81	397.00 86	701.00 87
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015

High-resolution multi-view benchmark