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.

LCM-MVSNet		99.43 1	99.49 1	99.24 1	99.95 1	98.13 1	99.37 1	99.57 1	99.82 1	99.86 1	99.85 1	99.52 1	99.73 1	97.58 1	99.94 1	99.85 1

LTVRE_ROB	93.87 1	97.93 2	98.16 3	97.26 23	98.81 23	93.86 27	99.07 2	98.98 3	97.01 11	98.92 5	98.78 14	95.22 32	98.61 155	96.85 4	99.77 12	99.31 38
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
Anonymous20231211		97.78 3	98.31 2	96.16 46	99.55 2	89.37 79	98.40 5	98.89 4	98.75 2	99.48 3	99.62 2	98.70 2	99.40 34	91.60 105	99.84 5	99.71 3

TDRefinement		97.68 4	97.60 4	97.93 2	99.02 11	95.95 6	98.61 3	98.81 5	97.41 8	97.28 47	98.46 28	94.62 45	98.84 119	94.64 26	99.53 43	98.99 70

UA-Net		97.35 5	97.24 13	97.69 5	98.22 60	93.87 26	98.42 4	98.19 24	96.95 12	95.46 122	99.23 4	93.45 58	99.57 13	95.34 17	99.89 4	99.63 10

abl_6		97.31 6	97.12 14	97.86 3	98.54 39	95.32 8	96.61 25	98.35 12	95.81 29	97.55 38	97.44 72	96.51 10	99.40 34	94.06 41	99.23 78	98.85 88

HPM-MVS_fast		97.01 7	96.89 17	97.39 18	99.12 7	93.92 24	97.16 12	98.17 26	93.11 62	96.48 74	97.36 78	96.92 7	99.34 47	94.31 33	99.38 64	98.92 82

v52		96.93 8	97.29 11	95.86 58	98.12 65	88.48 98	97.69 7	97.74 67	94.90 33	98.55 15	98.72 17	93.39 62	99.49 21	96.92 2	99.62 29	99.61 12

V4		96.93 8	97.29 11	95.86 58	98.11 66	88.47 99	97.69 7	97.74 67	94.91 31	98.55 15	98.72 17	93.37 63	99.49 21	96.92 2	99.62 29	99.61 12

mvs_tets		96.83 10	96.71 21	97.17 25	98.83 21	92.51 43	96.58 27	97.61 77	87.57 186	98.80 8	98.90 9	96.50 11	99.59 12	96.15 9	99.47 48	99.40 31

v7n		96.82 11	97.31 10	95.33 77	98.54 39	86.81 123	96.83 19	98.07 35	96.59 17	98.46 19	98.43 32	92.91 73	99.52 17	96.25 8	99.76 13	99.65 9

APD-MVS_3200maxsize		96.82 11	96.65 22	97.32 22	97.95 78	93.82 29	96.31 41	98.25 19	95.51 30	96.99 59	97.05 93	95.63 20	99.39 39	93.31 62	98.88 107	98.75 96

HPM-MVS		96.81 13	96.62 24	97.36 20	98.89 18	93.53 34	97.51 9	98.44 8	92.35 81	95.95 101	96.41 125	96.71 9	99.42 26	93.99 42	99.36 65	99.13 50

pmmvs6		96.80 14	97.36 9	95.15 84	99.12 7	87.82 110	96.68 23	97.86 57	96.10 24	98.14 25	99.28 3	97.94 4	98.21 196	91.38 112	99.69 15	99.42 27

OurMVSNet-221017-0		96.80 14	96.75 20	96.96 32	99.03 10	91.85 52	97.98 6	98.01 43	94.15 44	98.93 4	99.07 5	88.07 167	99.57 13	95.86 11	99.69 15	99.46 25

wuykxyi23d		96.76 16	96.57 26	97.34 21	97.75 84	96.73 3	94.37 105	96.48 163	91.00 119	99.72 2	98.99 6	96.06 15	98.21 196	94.86 22	99.90 2	97.09 189

COLMAP_ROB	91.06 5	96.75 17	96.62 24	97.13 26	98.38 50	94.31 12	96.79 21	98.32 13	96.69 15	96.86 61	97.56 65	95.48 22	98.77 135	90.11 131	99.44 54	98.31 119
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
anonymousdsp		96.74 18	96.42 29	97.68 7	98.00 74	94.03 21	96.97 16	97.61 77	87.68 185	98.45 21	98.77 15	94.20 51	99.50 18	96.70 5	99.40 61	99.53 17

DTE-MVSNet		96.74 18	97.43 5	94.67 95	99.13 5	84.68 153	96.51 30	97.94 54	98.14 3	98.67 12	98.32 35	95.04 36	99.69 2	93.27 63	99.82 10	99.62 11

PS-CasMVS		96.69 20	97.43 5	94.49 107	99.13 5	84.09 161	96.61 25	97.97 48	97.91 5	98.64 13	98.13 40	95.24 31	99.65 3	93.39 59	99.84 5	99.72 2

PEN-MVS		96.69 20	97.39 8	94.61 97	99.16 3	84.50 154	96.54 29	98.05 37	98.06 4	98.64 13	98.25 38	95.01 39	99.65 3	92.95 72	99.83 8	99.68 5

MTAPA		96.65 22	96.38 31	97.47 11	98.95 15	94.05 18	95.88 55	97.62 74	94.46 40	96.29 82	96.94 94	93.56 56	99.37 43	94.29 35	99.42 56	98.99 70

test_djsdf		96.62 23	96.49 28	97.01 30	98.55 38	91.77 54	97.15 13	97.37 99	88.98 153	98.26 23	98.86 10	93.35 65	99.60 8	96.41 6	99.45 52	99.66 7

ACMMP		96.61 24	96.34 32	97.43 15	98.61 31	93.88 25	96.95 17	98.18 25	92.26 84	96.33 78	96.84 103	95.10 35	99.40 34	93.47 55	99.33 68	99.02 67
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
WR-MVS_H		96.60 25	97.05 15	95.24 80	99.02 11	86.44 129	96.78 22	98.08 32	97.42 7	98.48 18	97.86 55	91.76 95	99.63 6	94.23 37	99.84 5	99.66 7

jajsoiax		96.59 26	96.42 29	97.12 27	98.76 25	92.49 44	96.44 35	97.42 95	86.96 196	98.71 10	98.72 17	95.36 26	99.56 16	95.92 10	99.45 52	99.32 37

ACMH	88.36 12	96.59 26	97.43 5	94.07 120	98.56 35	85.33 148	96.33 39	98.30 16	94.66 35	98.72 9	98.30 36	97.51 5	98.00 207	94.87 21	99.59 34	98.86 85
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
v748		96.51 28	97.05 15	94.89 89	98.35 55	85.82 142	96.58 27	97.47 92	96.25 21	98.46 19	98.35 33	93.27 66	99.33 50	95.13 19	99.59 34	99.52 20

XVS		96.49 29	96.18 38	97.44 13	98.56 35	93.99 22	96.50 31	97.95 51	94.58 36	94.38 156	96.49 118	94.56 46	99.39 39	93.57 50	99.05 94	98.93 79

ACMH+	88.43 11	96.48 30	96.82 18	95.47 73	98.54 39	89.06 82	95.65 61	98.61 7	96.10 24	98.16 24	97.52 68	96.90 8	98.62 154	90.30 125	99.60 32	98.72 100

MPTG		96.47 31	96.14 40	97.47 11	98.95 15	94.05 18	93.69 126	97.62 74	94.46 40	96.29 82	96.94 94	93.56 56	99.37 43	94.29 35	99.42 56	98.99 70

APDe-MVS		96.46 32	96.64 23	95.93 55	97.68 93	89.38 78	96.90 18	98.41 11	92.52 76	97.43 44	97.92 50	95.11 34	99.50 18	94.45 30	99.30 70	98.92 82

ACMMPR		96.46 32	96.14 40	97.41 17	98.60 32	93.82 29	96.30 43	97.96 49	92.35 81	95.57 118	96.61 114	94.93 42	99.41 30	93.78 45	99.15 85	99.00 68

mPP-MVS		96.46 32	96.05 47	97.69 5	98.62 29	94.65 9	96.45 33	97.74 67	92.59 75	95.47 120	96.68 112	94.50 48	99.42 26	93.10 68	99.26 74	98.99 70

CP-MVS		96.44 35	96.08 45	97.54 9	98.29 56	94.62 10	96.80 20	98.08 32	92.67 72	95.08 138	96.39 130	94.77 43	99.42 26	93.17 66	99.44 54	98.58 110

region2R		96.41 36	96.09 44	97.38 19	98.62 29	93.81 31	96.32 40	97.96 49	92.26 84	95.28 127	96.57 116	95.02 38	99.41 30	93.63 49	99.11 89	98.94 78

SteuartSystems-ACMMP		96.40 37	96.30 33	96.71 38	98.63 28	91.96 50	95.70 59	98.01 43	93.34 60	96.64 69	96.57 116	94.99 40	99.36 45	93.48 54	99.34 66	98.82 90
Skip Steuart: Steuart Systems R&D Blog.
HFP-MVS		96.39 38	96.17 39	97.04 28	98.51 43	93.37 35	96.30 43	97.98 45	92.35 81	95.63 116	96.47 120	95.37 24	99.27 55	93.78 45	99.14 86	98.48 111

LPG-MVS_test		96.38 39	96.23 36	96.84 36	98.36 53	92.13 47	95.33 70	98.25 19	91.78 101	97.07 53	97.22 83	96.38 12	99.28 53	92.07 93	99.59 34	99.11 52

nrg030		96.32 40	96.55 27	95.62 68	97.83 81	88.55 95	95.77 58	98.29 18	92.68 70	98.03 27	97.91 52	95.13 33	98.95 97	93.85 43	99.49 47	99.36 35

PGM-MVS		96.32 40	95.94 51	97.43 15	98.59 34	93.84 28	95.33 70	98.30 16	91.40 111	95.76 112	96.87 100	95.26 30	99.45 23	92.77 74	99.21 80	99.00 68

ACMM	88.83 9	96.30 42	96.07 46	96.97 31	98.39 49	92.95 41	94.74 89	98.03 40	90.82 122	97.15 51	96.85 101	96.25 14	99.00 89	93.10 68	99.33 68	98.95 77
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMMP_Plus		96.21 43	96.12 42	96.49 45	98.90 17	91.42 57	94.57 98	98.03 40	90.42 132	96.37 77	97.35 79	95.68 19	99.25 57	94.44 31	99.34 66	98.80 92

CP-MVSNet		96.19 44	96.80 19	94.38 113	98.99 13	83.82 163	96.31 41	97.53 86	97.60 6	98.34 22	97.52 68	91.98 91	99.63 6	93.08 70	99.81 11	99.70 4

MP-MVS		96.14 45	95.68 63	97.51 10	98.81 23	94.06 16	96.10 47	97.78 66	92.73 69	93.48 178	96.72 110	94.23 50	99.42 26	91.99 95	99.29 72	99.05 63

LS3D		96.11 46	95.83 58	96.95 33	94.75 239	94.20 14	97.34 11	97.98 45	97.31 9	95.32 125	96.77 104	93.08 69	99.20 61	91.79 100	98.16 176	97.44 174

MP-MVS-pluss		96.08 47	95.92 53	96.57 41	99.06 9	91.21 59	93.25 132	98.32 13	87.89 180	96.86 61	97.38 75	95.55 21	99.39 39	95.47 13	99.47 48	99.11 52
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
TranMVSNet+NR-MVSNet		96.07 48	96.26 35	95.50 72	98.26 58	87.69 111	93.75 124	97.86 57	95.96 28	97.48 41	97.14 87	95.33 27	99.44 24	90.79 115	99.76 13	99.38 32

PS-MVSNAJss		96.01 49	96.04 48	95.89 57	98.82 22	88.51 97	95.57 63	97.88 56	88.72 159	98.81 7	98.86 10	90.77 117	99.60 8	95.43 14	99.53 43	99.57 15

#test#		95.89 50	95.51 66	97.04 28	98.51 43	93.37 35	95.14 75	97.98 45	89.34 148	95.63 116	96.47 120	95.37 24	99.27 55	91.99 95	99.14 86	98.48 111

3Dnovator+	92.74 2	95.86 51	95.77 60	96.13 48	96.81 129	90.79 66	96.30 43	97.82 61	96.13 23	94.74 148	97.23 82	91.33 103	99.16 63	93.25 64	98.30 162	98.46 113

test_0402		95.73 52	96.22 37	94.26 116	98.19 62	85.77 143	93.24 133	97.24 116	96.88 14	97.69 36	97.77 58	94.12 52	99.13 69	91.54 109	99.29 72	97.88 148

ACMP	88.15 13	95.71 53	95.43 72	96.54 42	98.17 63	91.73 55	94.24 109	98.08 32	89.46 146	96.61 71	96.47 120	95.85 17	99.12 71	90.45 117	99.56 41	98.77 95
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
XVG-ACMP-BASELINE		95.68 54	95.34 74	96.69 39	98.40 48	93.04 38	94.54 102	98.05 37	90.45 131	96.31 80	96.76 106	92.91 73	98.72 141	91.19 113	99.42 56	98.32 117

DP-MVS		95.62 55	95.84 57	94.97 87	97.16 111	88.62 92	94.54 102	97.64 73	96.94 13	96.58 72	97.32 80	93.07 70	98.72 141	90.45 117	98.84 112	97.57 168

OPM-MVS		95.61 56	95.45 69	96.08 49	98.49 46	91.00 61	92.65 147	97.33 108	90.05 137	96.77 65	96.85 101	95.04 36	98.56 163	92.77 74	99.06 92	98.70 101

RPSCF		95.58 57	94.89 89	97.62 8	97.58 97	96.30 5	95.97 51	97.53 86	92.42 77	93.41 179	97.78 56	91.21 109	97.77 223	91.06 114	97.06 226	98.80 92

MIMVSNet1		95.52 58	95.45 69	95.72 65	99.14 4	89.02 83	96.23 46	96.87 144	93.73 51	97.87 32	98.49 26	90.73 121	99.05 79	86.43 190	99.60 32	99.10 55

Vis-MVSNet		95.50 59	95.48 67	95.56 71	98.11 66	89.40 77	95.35 69	98.22 23	92.36 79	94.11 164	98.07 41	92.02 88	99.44 24	93.38 60	97.67 205	97.85 151
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
pm-mvs1		95.43 60	95.94 51	93.93 126	98.38 50	85.08 150	95.46 67	97.12 124	91.84 98	97.28 47	98.46 28	95.30 29	97.71 228	90.17 129	99.42 56	98.99 70

DeepC-MVS	91.39 4	95.43 60	95.33 75	95.71 66	97.67 94	90.17 67	93.86 122	98.02 42	87.35 188	96.22 88	97.99 47	94.48 49	99.05 79	92.73 77	99.68 18	97.93 142
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
v13		95.39 62	96.12 42	93.18 147	97.22 108	80.81 195	95.55 64	97.57 81	93.42 58	98.02 29	98.49 26	89.62 140	99.18 62	95.54 12	99.68 18	99.54 16

XVG-OURS-SEG-HR		95.38 63	95.00 87	96.51 43	98.10 68	94.07 15	92.46 157	98.13 30	90.69 124	93.75 172	96.25 138	98.03 3	97.02 253	92.08 92	95.55 255	98.45 114

UniMVSNet_NR-MVSNet		95.35 64	95.21 81	95.76 63	97.69 92	88.59 93	92.26 166	97.84 60	94.91 31	96.80 63	95.78 163	90.42 127	99.41 30	91.60 105	99.58 39	99.29 39

FC-MVSNet-test		95.32 65	95.88 55	93.62 133	98.49 46	81.77 182	95.90 54	98.32 13	93.93 48	97.53 39	97.56 65	88.48 153	99.40 34	92.91 73	99.83 8	99.68 5

UniMVSNet (Re)		95.32 65	95.15 83	95.80 61	97.79 82	88.91 85	92.91 140	98.07 35	93.46 57	96.31 80	95.97 154	90.14 131	99.34 47	92.11 90	99.64 26	99.16 47

Gipuma		95.31 67	95.80 59	93.81 131	97.99 77	90.91 63	96.42 36	97.95 51	96.69 15	91.78 218	98.85 12	91.77 94	95.49 290	91.72 101	99.08 91	95.02 257
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
v12		95.29 68	96.02 50	93.10 149	97.14 114	80.63 196	95.39 68	97.55 85	93.19 61	97.98 30	98.44 30	89.40 143	99.16 63	95.38 16	99.67 21	99.52 20

DU-MVS		95.28 69	95.12 85	95.75 64	97.75 84	88.59 93	92.58 148	97.81 62	93.99 45	96.80 63	95.90 155	90.10 135	99.41 30	91.60 105	99.58 39	99.26 40

NR-MVSNet		95.28 69	95.28 78	95.26 79	97.75 84	87.21 117	95.08 77	97.37 99	93.92 49	97.65 37	95.90 155	90.10 135	99.33 50	90.11 131	99.66 23	99.26 40

TransMVSNet (Re)		95.27 71	96.04 48	92.97 155	98.37 52	81.92 181	95.07 78	96.76 150	93.97 47	97.77 34	98.57 21	95.72 18	97.90 210	88.89 154	99.23 78	99.08 59

SD-MVS		95.19 72	95.73 62	93.55 136	96.62 142	88.88 88	94.67 91	98.05 37	91.26 113	97.25 50	96.40 126	95.42 23	94.36 307	92.72 78	99.19 81	97.40 177

HSP-MVS		95.18 73	94.49 100	97.23 24	98.67 27	94.05 18	96.41 37	97.00 128	91.26 113	95.12 133	95.15 184	86.60 201	99.50 18	93.43 58	96.81 231	98.13 131

V9		95.17 74	95.89 54	93.02 152	97.04 117	80.42 198	95.22 74	97.53 86	92.92 68	97.90 31	98.35 33	89.15 147	99.14 67	95.21 18	99.65 25	99.50 22

VPA-MVSNet		95.14 75	95.67 64	93.58 135	97.76 83	83.15 170	94.58 97	97.58 80	93.39 59	97.05 57	98.04 42	93.25 67	98.51 172	89.75 138	99.59 34	99.08 59

v11		95.10 76	95.88 55	92.76 167	96.98 119	79.64 224	95.12 76	97.60 79	92.64 73	98.03 27	98.44 30	89.06 148	99.15 65	95.42 15	99.67 21	99.50 22

V14		95.05 77	95.75 61	92.94 158	96.94 121	80.21 201	95.03 80	97.50 90	92.62 74	97.84 33	98.28 37	88.87 150	99.13 69	95.03 20	99.64 26	99.48 24

HPM-MVS++		95.02 78	94.39 101	96.91 34	97.88 79	93.58 33	94.09 112	96.99 130	91.05 118	92.40 205	95.22 183	91.03 115	99.25 57	92.11 90	98.69 130	97.90 146

APD-MVS		95.00 79	94.69 93	95.93 55	97.38 104	90.88 64	94.59 95	97.81 62	89.22 151	95.46 122	96.17 148	93.42 61	99.34 47	89.30 144	98.87 110	97.56 170
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
PMVS	87.21 14	94.97 80	95.33 75	93.91 127	98.97 14	97.16 2	95.54 65	95.85 192	96.47 18	93.40 181	97.46 71	95.31 28	95.47 291	86.18 193	98.78 123	89.11 324
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
TSAR-MVS + MP.		94.96 81	94.75 91	95.57 70	98.86 20	88.69 89	96.37 38	96.81 146	85.23 213	94.75 147	97.12 89	91.85 93	99.40 34	93.45 56	98.33 157	98.62 106

v15		94.93 82	95.62 65	92.86 163	96.83 127	80.01 214	94.84 87	97.48 91	92.36 79	97.76 35	98.20 39	88.61 151	99.11 72	94.86 22	99.62 29	99.46 25

SixPastTwentyTwo		94.91 83	95.21 81	93.98 122	98.52 42	83.19 169	95.93 52	94.84 215	94.86 34	98.49 17	98.74 16	81.45 239	99.60 8	94.69 25	99.39 63	99.15 48

FIs		94.90 84	95.35 73	93.55 136	98.28 57	81.76 183	95.33 70	98.14 28	93.05 63	97.07 53	97.18 85	87.65 173	99.29 52	91.72 101	99.69 15	99.61 12

Regformer-4		94.90 84	94.67 95	95.59 69	92.78 280	89.02 83	92.39 160	95.91 189	94.50 38	96.41 75	95.56 171	92.10 87	99.01 88	94.23 37	98.14 178	98.74 97

AllTest		94.88 86	94.51 99	96.00 50	98.02 72	92.17 45	95.26 73	98.43 9	90.48 129	95.04 139	96.74 108	92.54 81	97.86 215	85.11 203	98.98 100	97.98 138

Regformer-2		94.86 87	94.55 98	95.77 62	92.83 278	89.98 69	91.87 183	96.40 167	94.38 42	96.19 92	95.04 191	92.47 84	99.04 82	93.49 53	98.31 159	98.28 121

FMVSNet1		94.84 88	95.13 84	93.97 123	97.60 96	84.29 155	95.99 48	96.56 157	92.38 78	97.03 58	98.53 23	90.12 132	98.98 90	88.78 156	99.16 84	98.65 102

ANet_high		94.83 89	96.28 34	90.47 231	96.65 136	73.16 297	94.33 107	98.74 6	96.39 20	98.09 26	98.93 8	93.37 63	98.70 147	90.38 120	99.68 18	99.53 17

v17		94.80 90	95.46 68	92.83 164	96.76 132	80.02 212	94.85 85	97.40 97	92.23 86	97.45 43	98.04 42	88.46 155	99.06 77	94.56 27	99.40 61	99.41 28

3Dnovator	92.54 3	94.80 90	94.90 88	94.47 108	95.47 216	87.06 119	96.63 24	97.28 114	91.82 100	94.34 159	97.41 73	90.60 125	98.65 153	92.47 85	98.11 182	97.70 160

v16		94.79 92	95.44 71	92.83 164	96.73 133	80.03 210	94.85 85	97.41 96	92.23 86	97.41 46	98.04 42	88.40 157	99.06 77	94.56 27	99.30 70	99.41 28

CPTT-MVS		94.74 93	94.12 112	96.60 40	98.15 64	93.01 39	95.84 56	97.66 72	89.21 152	93.28 185	95.46 174	88.89 149	98.98 90	89.80 137	98.82 118	97.80 155

XVG-OURS		94.72 94	94.12 112	96.50 44	98.00 74	94.23 13	91.48 200	98.17 26	90.72 123	95.30 126	96.47 120	87.94 170	96.98 254	91.41 111	97.61 208	98.30 120

CSCG		94.69 95	94.75 91	94.52 105	97.55 99	87.87 108	95.01 81	97.57 81	92.68 70	96.20 90	93.44 242	91.92 92	98.78 131	89.11 152	99.24 76	96.92 196

v10		94.68 96	95.27 79	92.90 161	96.57 145	80.15 203	94.65 93	97.57 81	90.68 125	97.43 44	98.00 46	88.18 159	99.15 65	94.84 24	99.55 42	99.41 28

v8		94.65 97	95.29 77	92.74 168	96.65 136	79.77 220	94.59 95	97.17 120	91.86 97	97.47 42	97.93 49	88.16 161	99.08 74	94.32 32	99.47 48	99.38 32

v18		94.63 98	95.26 80	92.74 168	96.60 143	79.81 218	94.64 94	97.37 99	91.87 96	97.26 49	97.91 52	88.13 162	99.04 82	94.30 34	99.24 76	99.38 32

canonicalmvs		94.59 99	94.69 93	94.30 115	95.60 213	87.03 120	95.59 62	98.24 22	91.56 109	95.21 132	92.04 271	94.95 41	98.66 151	91.45 110	97.57 209	97.20 187

CNVR-MVS		94.58 100	94.29 106	95.46 74	96.94 121	89.35 80	91.81 192	96.80 147	89.66 144	93.90 170	95.44 176	92.80 77	98.72 141	92.74 76	98.52 140	98.32 117

Regformer-1		94.55 101	94.33 105	95.19 82	92.83 278	88.54 96	91.87 183	95.84 193	93.99 45	95.95 101	95.04 191	92.00 89	98.79 128	93.14 67	98.31 159	98.23 123

EG-PatchMatch MVS		94.54 102	94.67 95	94.14 118	97.87 80	86.50 125	92.00 174	96.74 151	88.16 176	96.93 60	97.61 63	93.04 71	97.90 210	91.60 105	98.12 181	98.03 135

IS-MVSNet		94.49 103	94.35 104	94.92 88	98.25 59	86.46 128	97.13 15	94.31 229	96.24 22	96.28 85	96.36 133	82.88 226	99.35 46	88.19 165	99.52 45	98.96 76

Baseline_NR-MVSNet		94.47 104	95.09 86	92.60 176	98.50 45	80.82 194	92.08 171	96.68 153	93.82 50	96.29 82	98.56 22	90.10 135	97.75 226	90.10 133	99.66 23	99.24 42

VDD-MVS		94.37 105	94.37 103	94.40 112	97.49 102	86.07 137	93.97 116	93.28 247	94.49 39	96.24 86	97.78 56	87.99 169	98.79 128	88.92 153	99.14 86	98.34 116

EI-MVSNet-Vis-set		94.36 106	94.28 107	94.61 97	92.55 282	85.98 139	92.44 158	94.69 222	93.70 52	96.12 95	95.81 160	91.24 107	98.86 116	93.76 48	98.22 171	98.98 75

EI-MVSNet-UG-set		94.35 107	94.27 109	94.59 102	92.46 283	85.87 140	92.42 159	94.69 222	93.67 56	96.13 94	95.84 159	91.20 110	98.86 116	93.78 45	98.23 169	99.03 66

PHI-MVS		94.34 108	93.80 121	95.95 52	95.65 209	91.67 56	94.82 88	97.86 57	87.86 181	93.04 192	94.16 222	91.58 97	98.78 131	90.27 126	98.96 103	97.41 175

Regformer-3		94.28 109	94.23 111	94.46 109	92.78 280	86.28 133	92.39 160	94.70 221	93.69 55	95.97 99	95.56 171	91.34 102	98.48 176	93.45 56	98.14 178	98.62 106

tfpnnormal		94.27 110	94.87 90	92.48 182	97.71 89	80.88 193	94.55 101	95.41 207	93.70 52	96.67 68	97.72 59	91.40 101	98.18 201	87.45 174	99.18 83	98.36 115

HQP_MVS		94.26 111	93.93 115	95.23 81	97.71 89	88.12 104	94.56 99	97.81 62	91.74 105	93.31 182	95.59 166	86.93 192	98.95 97	89.26 148	98.51 141	98.60 108

OMC-MVS		94.22 112	93.69 129	95.81 60	97.25 107	91.27 58	92.27 165	97.40 97	87.10 194	94.56 152	95.42 177	93.74 54	98.11 204	86.62 186	98.85 111	98.06 133

LCM-MVSNet-Re		94.20 113	94.58 97	93.04 150	95.91 197	83.13 171	93.79 123	99.19 2	92.00 92	98.84 6	98.04 42	93.64 55	99.02 86	81.28 236	98.54 138	96.96 194

DeepPCF-MVS	90.46 6	94.20 113	93.56 134	96.14 47	95.96 193	92.96 40	89.48 258	97.46 93	85.14 215	96.23 87	95.42 177	93.19 68	98.08 205	90.37 121	98.76 125	97.38 180

NCCC		94.08 115	93.54 135	95.70 67	96.49 149	89.90 71	92.39 160	96.91 140	90.64 126	92.33 210	94.60 207	90.58 126	98.96 95	90.21 128	97.70 203	98.23 123

testing_2		94.03 116	94.38 102	93.00 153	96.79 131	81.41 188	92.87 142	96.96 132	85.88 208	97.06 56	97.92 50	91.18 113	98.71 146	91.72 101	99.04 97	98.87 84

VDDNet		94.03 116	94.27 109	93.31 144	98.87 19	82.36 177	95.51 66	91.78 273	97.19 10	96.32 79	98.60 20	84.24 219	98.75 136	87.09 179	98.83 115	98.81 91

EPP-MVSNet		93.91 118	93.68 130	94.59 102	98.08 69	85.55 146	97.44 10	94.03 234	94.22 43	94.94 142	96.19 146	82.07 234	99.57 13	87.28 178	98.89 105	98.65 102

Effi-MVS+-dtu		93.90 119	92.60 156	97.77 4	94.74 240	96.67 4	94.00 114	95.41 207	89.94 139	91.93 217	92.13 269	90.12 132	98.97 94	87.68 171	97.48 215	97.67 163

IterMVS-LS		93.78 120	94.28 107	92.27 188	96.27 172	79.21 237	91.87 183	96.78 148	91.77 103	96.57 73	97.07 91	87.15 185	98.74 139	91.99 95	99.03 98	98.86 85
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DeepC-MVS_fast	89.96 7	93.73 121	93.44 137	94.60 101	96.14 182	87.90 107	93.36 131	97.14 121	85.53 212	93.90 170	95.45 175	91.30 105	98.59 159	89.51 141	98.62 132	97.31 183
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
v7		93.66 122	93.97 114	92.73 170	96.55 146	80.15 203	92.54 149	96.99 130	87.36 187	95.99 98	96.48 119	88.18 159	98.94 100	93.35 61	98.31 159	99.09 56

MVS_111021_LR		93.66 122	93.28 141	94.80 92	96.25 175	90.95 62	90.21 234	95.43 206	87.91 178	93.74 174	94.40 213	92.88 75	96.38 276	90.39 119	98.28 163	97.07 190

MVS_111021_HR		93.63 124	93.42 138	94.26 116	96.65 136	86.96 121	89.30 264	96.23 179	88.36 170	93.57 176	94.60 207	93.45 58	97.77 223	90.23 127	98.38 150	98.03 135

v6		93.59 125	93.93 115	92.56 178	96.65 136	79.77 220	92.50 154	96.40 167	88.55 164	95.94 103	96.23 141	88.13 162	98.87 113	92.46 86	98.50 143	99.06 62

v1neww		93.58 126	93.92 117	92.56 178	96.64 140	79.77 220	92.50 154	96.41 165	88.55 164	95.93 104	96.24 139	88.08 164	98.87 113	92.45 87	98.50 143	99.05 63

v7new		93.58 126	93.92 117	92.56 178	96.64 140	79.77 220	92.50 154	96.41 165	88.55 164	95.93 104	96.24 139	88.08 164	98.87 113	92.45 87	98.50 143	99.05 63

v1144		93.50 128	93.81 120	92.57 177	96.28 171	79.61 226	91.86 187	96.96 132	86.95 197	95.91 107	96.32 134	87.65 173	98.96 95	93.51 52	98.88 107	99.13 50

v1192		93.49 129	93.78 122	92.62 175	96.16 181	79.62 225	91.83 191	97.22 118	86.07 204	96.10 96	96.38 131	87.22 183	99.02 86	94.14 40	98.88 107	99.22 43

WR-MVS		93.49 129	93.72 127	92.80 166	97.57 98	80.03 210	90.14 238	95.68 196	93.70 52	96.62 70	95.39 180	87.21 184	99.04 82	87.50 173	99.64 26	99.33 36

v1		93.43 131	93.77 123	92.41 184	96.37 158	79.24 232	91.84 188	96.38 170	88.33 171	95.87 108	96.22 144	87.45 177	98.89 103	92.61 81	98.83 115	99.09 56

V42		93.43 131	93.58 133	92.97 155	95.34 223	81.22 189	92.67 146	96.49 162	87.25 190	96.20 90	96.37 132	87.32 182	98.85 118	92.39 89	98.21 172	98.85 88

v1141		93.42 133	93.76 124	92.40 186	96.37 158	79.24 232	91.84 188	96.38 170	88.33 171	95.86 109	96.23 141	87.41 179	98.89 103	92.61 81	98.82 118	99.08 59

divwei89l23v2f112		93.42 133	93.76 124	92.41 184	96.37 158	79.24 232	91.84 188	96.38 170	88.33 171	95.86 109	96.23 141	87.41 179	98.89 103	92.61 81	98.83 115	99.09 56

K. test v3		93.37 135	93.27 142	93.66 132	98.05 70	82.62 175	94.35 106	86.62 304	96.05 26	97.51 40	98.85 12	76.59 272	99.65 3	93.21 65	98.20 174	98.73 99

PM-MVS		93.33 136	92.67 154	95.33 77	96.58 144	94.06 16	92.26 166	92.18 265	85.92 207	96.22 88	96.61 114	85.64 213	95.99 284	90.35 123	98.23 169	95.93 235

v1240		93.29 137	93.71 128	92.06 195	96.01 190	77.89 254	91.81 192	97.37 99	85.12 216	96.69 67	96.40 126	86.67 198	99.07 76	94.51 29	98.76 125	99.22 43

test_prior3		93.29 137	92.85 148	94.61 97	95.95 194	87.23 115	90.21 234	97.36 105	89.33 149	90.77 231	94.81 198	90.41 128	98.68 149	88.21 163	98.55 136	97.93 142

v2v482		93.29 137	93.63 131	92.29 187	96.35 166	78.82 243	91.77 195	96.28 175	88.45 167	95.70 115	96.26 137	86.02 208	98.90 101	93.02 71	98.81 121	99.14 49

alignmvs		93.26 140	92.85 148	94.50 106	95.70 205	87.45 112	93.45 129	95.76 194	91.58 108	95.25 129	92.42 264	81.96 236	98.72 141	91.61 104	97.87 197	97.33 182

v1921920		93.26 140	93.61 132	92.19 190	96.04 189	78.31 249	91.88 182	97.24 116	85.17 214	96.19 92	96.19 146	86.76 197	99.05 79	94.18 39	98.84 112	99.22 43

MSLP-MVS++		93.25 142	93.88 119	91.37 214	96.34 167	82.81 174	93.11 134	97.74 67	89.37 147	94.08 166	95.29 182	90.40 130	96.35 278	90.35 123	98.25 167	94.96 258

GBi-Net		93.21 143	92.96 145	93.97 123	95.40 218	84.29 155	95.99 48	96.56 157	88.63 160	95.10 135	98.53 23	81.31 242	98.98 90	86.74 182	98.38 150	98.65 102

test1		93.21 143	92.96 145	93.97 123	95.40 218	84.29 155	95.99 48	96.56 157	88.63 160	95.10 135	98.53 23	81.31 242	98.98 90	86.74 182	98.38 150	98.65 102

v144192		93.20 145	93.54 135	92.16 192	96.05 186	78.26 250	91.95 175	97.14 121	84.98 220	95.96 100	96.11 149	87.08 187	99.04 82	93.79 44	98.84 112	99.17 46

VPNet		93.08 146	93.76 124	91.03 222	98.60 32	75.83 277	91.51 199	95.62 197	91.84 98	95.74 113	97.10 90	89.31 144	98.32 187	85.07 205	99.06 92	98.93 79

UGNet		93.08 146	92.50 159	94.79 93	93.87 263	87.99 106	95.07 78	94.26 231	90.64 126	87.33 289	97.67 61	86.89 195	98.49 173	88.10 167	98.71 128	97.91 145
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
mvs-test1		93.07 148	91.80 170	96.89 35	94.74 240	95.83 7	92.17 169	95.41 207	89.94 139	89.85 252	90.59 295	90.12 132	98.88 107	87.68 171	95.66 253	95.97 233

TSAR-MVS + GP.		93.07 148	92.41 160	95.06 86	95.82 199	90.87 65	90.97 212	92.61 260	88.04 177	94.61 151	93.79 234	88.08 164	97.81 219	89.41 143	98.39 149	96.50 215

MVS_0304		92.99 150	92.54 157	94.35 114	94.67 245	86.06 138	91.16 207	97.92 55	90.01 138	88.33 277	94.41 211	87.02 188	99.22 59	90.36 122	99.00 99	97.76 156

EI-MVSNet		92.99 150	93.26 143	92.19 190	92.12 291	79.21 237	92.32 163	94.67 224	91.77 103	95.24 130	95.85 157	87.14 186	98.49 173	91.99 95	98.26 165	98.86 85

MCST-MVS		92.91 152	92.51 158	94.10 119	97.52 100	85.72 144	91.36 204	97.13 123	80.33 257	92.91 196	94.24 218	91.23 108	98.72 141	89.99 135	97.93 194	97.86 150

QAPM		92.88 153	92.77 150	93.22 146	95.82 199	83.31 167	96.45 33	97.35 107	83.91 228	93.75 172	96.77 104	89.25 145	98.88 107	84.56 210	97.02 228	97.49 172

v148		92.87 154	93.29 139	91.62 206	96.25 175	77.72 256	91.28 205	95.05 211	89.69 143	95.93 104	96.04 151	87.34 181	98.38 183	90.05 134	97.99 191	98.78 94

Effi-MVS+		92.79 155	92.74 152	92.94 158	95.10 229	83.30 168	94.00 114	97.53 86	91.36 112	89.35 261	90.65 294	94.01 53	98.66 151	87.40 176	95.30 263	96.88 199

FMVSNet2		92.78 156	92.73 153	92.95 157	95.40 218	81.98 180	94.18 111	95.53 204	88.63 160	96.05 97	97.37 76	81.31 242	98.81 126	87.38 177	98.67 131	98.06 133

Fast-Effi-MVS+-dtu		92.77 157	92.16 162	94.58 104	94.66 246	88.25 102	92.05 172	96.65 154	89.62 145	90.08 244	91.23 281	92.56 80	98.60 157	86.30 192	96.27 243	96.90 197

LF4IMVS		92.72 158	92.02 165	94.84 91	95.65 209	91.99 49	92.92 139	96.60 156	85.08 218	92.44 204	93.62 236	86.80 196	96.35 278	86.81 181	98.25 167	96.18 227

train_agg		92.71 159	91.83 168	95.35 75	96.45 155	89.46 73	90.60 223	96.92 137	79.37 265	90.49 238	94.39 214	91.20 110	98.88 107	88.66 159	98.43 146	97.72 158

VNet		92.67 160	92.96 145	91.79 201	96.27 172	80.15 203	91.95 175	94.98 212	92.19 89	94.52 154	96.07 150	87.43 178	97.39 241	84.83 207	98.38 150	97.83 152

CDPH-MVS		92.67 160	91.83 168	95.18 83	96.94 121	88.46 100	90.70 220	97.07 125	77.38 279	92.34 209	95.08 188	92.67 79	98.88 107	85.74 195	98.57 135	98.20 126

agg_prior1		92.60 162	91.76 171	95.10 85	96.20 177	88.89 86	90.37 229	96.88 142	79.67 262	90.21 241	94.41 211	91.30 105	98.78 131	88.46 162	98.37 155	97.64 165

XXY-MVS		92.58 163	93.16 144	90.84 227	97.75 84	79.84 217	91.87 183	96.22 181	85.94 206	95.53 119	97.68 60	92.69 78	94.48 303	83.21 220	97.51 210	98.21 125

MVS_Test		92.57 164	93.29 139	90.40 233	93.53 269	75.85 275	92.52 151	96.96 132	88.73 158	92.35 207	96.70 111	90.77 117	98.37 186	92.53 84	95.49 257	96.99 193

agg_prior3		92.56 165	91.62 173	95.35 75	96.39 157	89.45 75	90.61 222	96.82 145	78.82 272	90.03 246	94.14 223	90.72 122	98.88 107	88.66 159	98.43 146	97.72 158

TAPA-MVS	88.58 10	92.49 166	91.75 172	94.73 94	96.50 148	89.69 72	92.91 140	97.68 71	78.02 276	92.79 197	94.10 224	90.85 116	97.96 209	84.76 208	98.16 176	96.54 206
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ab-mvs		92.40 167	92.62 155	91.74 202	97.02 118	81.65 184	95.84 56	95.50 205	86.95 197	92.95 195	97.56 65	90.70 123	97.50 235	79.63 254	97.43 217	96.06 231

CANet		92.38 168	91.99 166	93.52 140	93.82 265	83.46 166	91.14 208	97.00 128	89.81 142	86.47 294	94.04 226	87.90 171	99.21 60	89.50 142	98.27 164	97.90 146

DP-MVS Recon		92.31 169	91.88 167	93.60 134	97.18 110	86.87 122	91.10 210	97.37 99	84.92 221	92.08 214	94.08 225	88.59 152	98.20 198	83.50 217	98.14 178	95.73 240

F-COLMAP		92.28 170	91.06 189	95.95 52	97.52 100	91.90 51	93.53 127	97.18 119	83.98 227	88.70 273	94.04 226	88.41 156	98.55 169	80.17 248	95.99 247	97.39 178

OpenMVS	89.45 8	92.27 171	92.13 164	92.68 172	94.53 251	84.10 160	95.70 59	97.03 126	82.44 244	91.14 228	96.42 124	88.47 154	98.38 183	85.95 194	97.47 216	95.55 247

MVSFormer		92.18 172	92.23 161	92.04 196	94.74 240	80.06 208	97.15 13	97.37 99	88.98 153	88.83 265	92.79 251	77.02 267	99.60 8	96.41 6	96.75 234	96.46 217

HQP-MVS		92.09 173	91.49 178	93.88 128	96.36 163	84.89 151	91.37 201	97.31 109	87.16 191	88.81 267	93.40 243	84.76 216	98.60 157	86.55 188	97.73 200	98.14 130

DELS-MVS		92.05 174	92.16 162	91.72 203	94.44 252	80.13 206	87.62 284	97.25 115	87.34 189	92.22 212	93.18 247	89.54 142	98.73 140	89.67 140	98.20 174	96.30 223
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
TinyColmap		92.00 175	92.76 151	89.71 247	95.62 212	77.02 264	90.72 219	96.17 183	87.70 184	95.26 128	96.29 135	92.54 81	96.45 272	81.77 231	98.77 124	95.66 243

CLD-MVS		91.82 176	91.41 180	93.04 150	96.37 158	83.65 165	86.82 297	97.29 112	84.65 224	92.27 211	89.67 304	92.20 85	97.85 217	83.95 214	99.47 48	97.62 166
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
CNLPA		91.72 177	91.20 186	93.26 145	96.17 180	91.02 60	91.14 208	95.55 203	90.16 136	90.87 230	93.56 239	86.31 204	94.40 306	79.92 253	97.12 224	94.37 270

PVSNet_Blended_VisFu		91.63 178	91.20 186	92.94 158	97.73 88	83.95 162	92.14 170	97.46 93	78.85 271	92.35 207	94.98 194	84.16 220	99.08 74	86.36 191	96.77 233	95.79 238

AdaColmap		91.63 178	91.36 182	92.47 183	95.56 214	86.36 132	92.24 168	96.27 176	88.88 157	89.90 251	92.69 255	91.65 96	98.32 187	77.38 272	97.64 206	92.72 304

pmmvs-eth3d		91.54 180	90.73 197	93.99 121	95.76 203	87.86 109	90.83 216	93.98 236	78.23 275	94.02 168	96.22 144	82.62 231	96.83 260	86.57 187	98.33 157	97.29 184

API-MVS		91.52 181	91.61 174	91.26 218	94.16 257	86.26 134	94.66 92	94.82 216	91.17 116	92.13 213	91.08 284	90.03 138	97.06 252	79.09 259	97.35 221	90.45 321

test_normal		91.49 182	91.44 179	91.62 206	95.21 226	79.44 228	90.08 241	93.84 238	82.60 240	94.37 158	94.74 203	86.66 199	98.46 178	88.58 161	96.92 230	96.95 195

xiu_mvs_v1_base_debu		91.47 183	91.52 175	91.33 215	95.69 206	81.56 185	89.92 246	96.05 185	83.22 232	91.26 224	90.74 289	91.55 98	98.82 121	89.29 145	95.91 248	93.62 290

xiu_mvs_v1_base		91.47 183	91.52 175	91.33 215	95.69 206	81.56 185	89.92 246	96.05 185	83.22 232	91.26 224	90.74 289	91.55 98	98.82 121	89.29 145	95.91 248	93.62 290

xiu_mvs_v1_base_debi		91.47 183	91.52 175	91.33 215	95.69 206	81.56 185	89.92 246	96.05 185	83.22 232	91.26 224	90.74 289	91.55 98	98.82 121	89.29 145	95.91 248	93.62 290

DI_MVS_plusplus_test		91.42 186	91.41 180	91.46 211	95.34 223	79.06 239	90.58 225	93.74 240	82.59 241	94.69 150	94.76 202	86.54 202	98.44 180	87.93 169	96.49 241	96.87 200

Test4		91.41 187	91.25 185	91.89 198	95.35 222	80.32 199	90.97 212	96.92 137	81.96 247	95.11 134	93.81 233	81.34 241	98.48 176	88.71 158	97.08 225	96.87 200

LFMVS		91.33 188	91.16 188	91.82 200	96.27 172	79.36 230	95.01 81	85.61 314	96.04 27	94.82 145	97.06 92	72.03 280	98.46 178	84.96 206	98.70 129	97.65 164

Fast-Effi-MVS+		91.28 189	90.86 192	92.53 181	95.45 217	82.53 176	89.25 267	96.52 161	85.00 219	89.91 250	88.55 310	92.94 72	98.84 119	84.72 209	95.44 260	96.22 226

MDA-MVSNet-bldmvs		91.04 190	90.88 191	91.55 209	94.68 244	80.16 202	85.49 306	92.14 268	90.41 133	94.93 143	95.79 161	85.10 214	96.93 256	85.15 201	94.19 285	97.57 168

PAPM_NR		91.03 191	90.81 194	91.68 205	96.73 133	81.10 191	93.72 125	96.35 174	88.19 175	88.77 271	92.12 270	85.09 215	97.25 245	82.40 228	93.90 287	96.68 205

MSDG		90.82 192	90.67 198	91.26 218	94.16 257	83.08 172	86.63 300	96.19 182	90.60 128	91.94 216	91.89 272	89.16 146	95.75 287	80.96 243	94.51 278	94.95 259

test20.03		90.80 193	90.85 193	90.63 229	95.63 211	79.24 232	89.81 252	92.87 253	89.90 141	94.39 155	96.40 126	85.77 209	95.27 298	73.86 292	99.05 94	97.39 178

FMVSNet3		90.78 194	90.32 202	92.16 192	93.03 276	79.92 216	92.54 149	94.95 213	86.17 203	95.10 135	96.01 152	69.97 286	98.75 136	86.74 182	98.38 150	97.82 154

X-MVStestdata		90.70 195	88.45 222	97.44 13	98.56 35	93.99 22	96.50 31	97.95 51	94.58 36	94.38 156	26.89 342	94.56 46	99.39 39	93.57 50	99.05 94	98.93 79

BH-untuned		90.68 196	90.90 190	90.05 244	95.98 192	79.57 227	90.04 242	94.94 214	87.91 178	94.07 167	93.00 248	87.76 172	97.78 222	79.19 258	95.17 266	92.80 302

114514_t		90.51 197	89.80 207	92.63 174	98.00 74	82.24 178	93.40 130	97.29 112	65.84 329	89.40 260	94.80 201	86.99 190	98.75 136	83.88 215	98.61 133	96.89 198

BH-RMVSNet		90.47 198	90.44 200	90.56 230	95.21 226	78.65 247	89.15 268	93.94 237	88.21 174	92.74 198	94.22 219	86.38 203	97.88 212	78.67 261	95.39 261	95.14 254

diffmvs		90.45 199	90.49 199	90.34 234	92.25 286	77.09 263	91.80 194	95.96 188	82.68 239	85.83 298	95.07 189	87.01 189	97.09 250	89.68 139	94.10 286	96.83 202

Vis-MVSNet (Re-imp)		90.42 200	90.16 203	91.20 220	97.66 95	77.32 260	94.33 107	87.66 297	91.20 115	92.99 193	95.13 186	75.40 274	98.28 189	77.86 265	99.19 81	97.99 137

PLC	85.34 15	90.40 201	88.92 217	94.85 90	96.53 147	90.02 68	91.58 197	96.48 163	80.16 258	86.14 296	92.18 268	85.73 210	98.25 194	76.87 275	94.61 277	96.30 223
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
testgi		90.38 202	91.34 183	87.50 283	97.49 102	71.54 306	89.43 259	95.16 210	88.38 169	94.54 153	94.68 206	92.88 75	93.09 317	71.60 306	97.85 198	97.88 148

mvs_anonymous		90.37 203	91.30 184	87.58 282	92.17 290	68.00 315	89.84 251	94.73 220	83.82 230	93.22 190	97.40 74	87.54 175	97.40 240	87.94 168	95.05 268	97.34 181

PVSNet_BlendedMVS		90.35 204	89.96 205	91.54 210	94.81 236	78.80 245	90.14 238	96.93 135	79.43 263	88.68 274	95.06 190	86.27 205	98.15 202	80.27 245	98.04 188	97.68 162

UnsupCasMVSNet_eth		90.33 205	90.34 201	90.28 236	94.64 247	80.24 200	89.69 254	95.88 190	85.77 210	93.94 169	95.69 165	81.99 235	92.98 318	84.21 212	91.30 314	97.62 166

MAR-MVS		90.32 206	88.87 219	94.66 96	94.82 235	91.85 52	94.22 110	94.75 219	80.91 252	87.52 288	88.07 314	86.63 200	97.87 214	76.67 276	96.21 245	94.25 272
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
1121		90.26 207	89.23 209	93.34 142	97.15 113	87.40 113	91.94 177	94.39 227	67.88 323	91.02 229	94.91 196	86.91 194	98.59 159	81.17 239	97.71 202	94.02 279

IterMVS		90.18 208	90.16 203	90.21 241	93.15 274	75.98 274	87.56 287	92.97 252	86.43 201	94.09 165	96.40 126	78.32 257	97.43 237	87.87 170	94.69 275	97.23 185
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
TAMVS		90.16 209	89.05 213	93.49 141	96.49 149	86.37 131	90.34 231	92.55 261	80.84 255	92.99 193	94.57 209	81.94 237	98.20 198	73.51 293	98.21 172	95.90 236

Patchmtry		90.11 210	89.92 206	90.66 228	90.35 309	77.00 265	92.96 138	92.81 254	90.25 135	94.74 148	96.93 96	67.11 292	97.52 234	85.17 199	98.98 100	97.46 173

MVP-Stereo		90.07 211	88.92 217	93.54 138	96.31 169	86.49 126	90.93 214	95.59 201	79.80 259	91.48 220	95.59 166	80.79 247	97.39 241	78.57 262	91.19 315	96.76 204
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
CANet_DTU		89.85 212	89.17 211	91.87 199	92.20 289	80.02 212	90.79 217	95.87 191	86.02 205	82.53 319	91.77 274	80.01 250	98.57 162	85.66 196	97.70 203	97.01 192

EPNet		89.80 213	88.25 225	94.45 110	83.91 343	86.18 135	93.87 121	87.07 302	91.16 117	80.64 330	94.72 204	78.83 253	98.89 103	85.17 199	98.89 105	98.28 121
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CDS-MVSNet		89.55 214	88.22 228	93.53 139	95.37 221	86.49 126	89.26 265	93.59 242	79.76 260	91.15 227	92.31 266	77.12 266	98.38 183	77.51 270	97.92 195	95.71 241
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
MG-MVS		89.54 215	89.80 207	88.76 268	94.88 232	72.47 303	89.60 255	92.44 263	85.82 209	89.48 259	95.98 153	82.85 227	97.74 227	81.87 230	95.27 264	96.08 230

OpenMVS_ROB	85.12 16	89.52 216	89.05 213	90.92 226	94.58 250	81.21 190	91.10 210	93.41 246	77.03 282	93.41 179	93.99 230	83.23 223	97.80 220	79.93 252	94.80 273	93.74 287

MVSTER		89.32 217	88.75 220	91.03 222	90.10 311	76.62 267	90.85 215	94.67 224	82.27 245	95.24 130	95.79 161	61.09 326	98.49 173	90.49 116	98.26 165	97.97 141

RPMNet		89.30 218	89.00 215	90.22 239	91.01 298	78.93 240	92.52 151	87.85 296	91.91 94	89.10 262	96.89 99	68.84 287	97.64 231	90.17 129	92.70 303	94.08 274

PatchMatch-RL		89.18 219	88.02 233	92.64 173	95.90 198	92.87 42	88.67 277	91.06 277	80.34 256	90.03 246	91.67 276	83.34 222	94.42 305	76.35 279	94.84 272	90.64 320

jason		89.17 220	88.32 223	91.70 204	95.73 204	80.07 207	88.10 281	93.22 249	71.98 305	90.09 243	92.79 251	78.53 256	98.56 163	87.43 175	97.06 226	96.46 217
jason: jason.
PCF-MVS	84.52 17	89.12 221	87.71 239	93.34 142	96.06 185	85.84 141	86.58 301	97.31 109	68.46 321	93.61 175	93.89 231	87.51 176	98.52 171	67.85 319	98.11 182	95.66 243
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
USDC		89.02 222	89.08 212	88.84 267	95.07 230	74.50 284	88.97 271	96.39 169	73.21 299	93.27 186	96.28 136	82.16 233	96.39 275	77.55 269	98.80 122	95.62 245

xiu_mvs_v2_base		89.00 223	89.19 210	88.46 273	94.86 234	74.63 281	86.97 294	95.60 198	80.88 253	87.83 283	88.62 309	91.04 114	98.81 126	82.51 227	94.38 279	91.93 311

new-patchmatchnet		88.97 224	90.79 195	83.50 311	94.28 256	55.83 341	85.34 307	93.56 243	86.18 202	95.47 120	95.73 164	83.10 224	96.51 269	85.40 198	98.06 186	98.16 128

pmmvs4		88.95 225	87.70 240	92.70 171	94.30 255	85.60 145	87.22 291	92.16 267	74.62 289	89.75 256	94.19 220	77.97 260	96.41 274	82.71 224	96.36 242	96.09 229

N_pmnet		88.90 226	87.25 244	93.83 130	94.40 254	93.81 31	84.73 310	87.09 301	79.36 267	93.26 187	92.43 263	79.29 252	91.68 323	77.50 271	97.22 223	96.00 232

PS-MVSNAJ		88.86 227	88.99 216	88.48 272	94.88 232	74.71 279	86.69 298	95.60 198	80.88 253	87.83 283	87.37 316	90.77 117	98.82 121	82.52 226	94.37 280	91.93 311

Patchmatch-RL test		88.81 228	88.52 221	89.69 248	95.33 225	79.94 215	86.22 302	92.71 258	78.46 273	95.80 111	94.18 221	66.25 300	95.33 296	89.22 150	98.53 139	93.78 285

Anonymous20231206		88.77 229	88.29 224	90.20 242	96.31 169	78.81 244	89.56 257	93.49 245	74.26 293	92.38 206	95.58 169	82.21 232	95.43 293	72.07 301	98.75 127	96.34 221

PVSNet_Blended		88.74 230	88.16 230	90.46 232	94.81 236	78.80 245	86.64 299	96.93 135	74.67 288	88.68 274	89.18 307	86.27 205	98.15 202	80.27 245	96.00 246	94.44 269

UnsupCasMVSNet_bld		88.50 231	88.03 232	89.90 245	95.52 215	78.88 242	87.39 289	94.02 235	79.32 268	93.06 191	94.02 228	80.72 248	94.27 308	75.16 289	93.08 299	96.54 206

testmv		88.46 232	88.11 231	89.48 249	96.00 191	76.14 271	86.20 303	93.75 239	84.48 225	93.57 176	95.52 173	80.91 246	95.09 299	63.97 328	98.61 133	97.22 186

1112_ss		88.42 233	87.41 241	91.45 212	96.69 135	80.99 192	89.72 253	96.72 152	73.37 298	87.00 292	90.69 292	77.38 264	98.20 198	81.38 235	93.72 290	95.15 253

lupinMVS		88.34 234	87.31 242	91.45 212	94.74 240	80.06 208	87.23 290	92.27 264	71.10 309	88.83 265	91.15 282	77.02 267	98.53 170	86.67 185	96.75 234	95.76 239

view600		88.32 235	87.94 234	89.46 251	96.49 149	73.31 292	93.95 117	84.46 326	93.02 64	94.18 160	92.68 256	63.33 316	98.56 163	75.87 283	97.50 211	96.51 208

view800		88.32 235	87.94 234	89.46 251	96.49 149	73.31 292	93.95 117	84.46 326	93.02 64	94.18 160	92.68 256	63.33 316	98.56 163	75.87 283	97.50 211	96.51 208

conf0.05thres1000		88.32 235	87.94 234	89.46 251	96.49 149	73.31 292	93.95 117	84.46 326	93.02 64	94.18 160	92.68 256	63.33 316	98.56 163	75.87 283	97.50 211	96.51 208

tfpn		88.32 235	87.94 234	89.46 251	96.49 149	73.31 292	93.95 117	84.46 326	93.02 64	94.18 160	92.68 256	63.33 316	98.56 163	75.87 283	97.50 211	96.51 208

YYNet1		88.17 239	88.24 226	87.93 278	92.21 288	73.62 289	80.75 326	88.77 286	82.51 243	94.99 141	95.11 187	82.70 229	93.70 312	83.33 218	93.83 288	96.48 216

MDA-MVSNet_test_wron		88.16 240	88.23 227	87.93 278	92.22 287	73.71 288	80.71 327	88.84 285	82.52 242	94.88 144	95.14 185	82.70 229	93.61 313	83.28 219	93.80 289	96.46 217

MS-PatchMatch		88.05 241	87.75 238	88.95 265	93.28 271	77.93 252	87.88 283	92.49 262	75.42 287	92.57 202	93.59 238	80.44 249	94.24 310	81.28 236	92.75 302	94.69 263

CR-MVSNet		87.89 242	87.12 248	90.22 239	91.01 298	78.93 240	92.52 151	92.81 254	73.08 300	89.10 262	96.93 96	67.11 292	97.64 231	88.80 155	92.70 303	94.08 274

pmmvs5		87.87 243	87.14 247	90.07 243	93.26 273	76.97 266	88.89 273	92.18 265	73.71 297	88.36 276	93.89 231	76.86 270	96.73 263	80.32 244	96.81 231	96.51 208

no-one		87.84 244	87.21 245	89.74 246	93.58 268	78.64 248	81.28 325	92.69 259	74.36 291	92.05 215	97.14 87	81.86 238	96.07 282	72.03 302	99.90 2	94.52 266

wuyk23d		87.83 245	90.79 195	78.96 322	90.46 307	88.63 91	92.72 144	90.67 280	91.65 107	98.68 11	97.64 62	96.06 15	77.53 342	59.84 332	99.41 60	70.73 338

FMVSNet5		87.82 246	86.56 258	91.62 206	92.31 285	79.81 218	93.49 128	94.81 218	83.26 231	91.36 222	96.93 96	52.77 338	97.49 236	76.07 280	98.03 189	97.55 171

GA-MVS		87.70 247	86.82 253	90.31 235	93.27 272	77.22 262	84.72 312	92.79 256	85.11 217	89.82 253	90.07 296	66.80 295	97.76 225	84.56 210	94.27 283	95.96 234

TR-MVS		87.70 247	87.17 246	89.27 260	94.11 259	79.26 231	88.69 276	91.86 271	81.94 248	90.69 234	89.79 301	82.82 228	97.42 238	72.65 299	91.98 311	91.14 316

thres600view7		87.66 249	87.10 249	89.36 258	96.05 186	73.17 296	92.72 144	85.31 317	91.89 95	93.29 184	90.97 285	63.42 313	98.39 181	73.23 295	96.99 229	96.51 208

PAPR		87.65 250	86.77 255	90.27 237	92.85 277	77.38 259	88.56 278	96.23 179	76.82 284	84.98 303	89.75 303	86.08 207	97.16 248	72.33 300	93.35 293	96.26 225

PatchT		87.51 251	88.17 229	85.55 296	90.64 302	66.91 319	92.02 173	86.09 307	92.20 88	89.05 264	97.16 86	64.15 309	96.37 277	89.21 151	92.98 301	93.37 296

Test_1112_low_res		87.50 252	86.58 257	90.25 238	96.80 130	77.75 255	87.53 288	96.25 177	69.73 317	86.47 294	93.61 237	75.67 273	97.88 212	79.95 250	93.20 295	95.11 255

conf200view11		87.41 253	86.89 251	88.97 264	96.14 182	73.09 298	93.00 136	85.31 317	92.13 90	93.26 187	90.96 286	63.42 313	98.28 189	71.27 309	96.54 236	95.56 246

EU-MVSNet		87.39 254	86.71 256	89.44 255	93.40 270	76.11 272	94.93 84	90.00 283	57.17 338	95.71 114	97.37 76	64.77 307	97.68 230	92.67 79	94.37 280	94.52 266

thres100view900		87.35 255	86.89 251	88.72 269	96.14 182	73.09 298	93.00 136	85.31 317	92.13 90	93.26 187	90.96 286	63.42 313	98.28 189	71.27 309	96.54 236	94.79 261

Patchmatch-test1		87.28 256	87.30 243	87.22 285	92.01 293	71.98 305	89.43 259	88.11 294	82.26 246	88.71 272	92.20 267	78.65 255	95.81 286	80.99 242	93.30 294	93.87 284

CMPMVS	68.83 22	87.28 256	85.67 268	92.09 194	88.77 324	85.42 147	90.31 232	94.38 228	70.02 316	88.00 281	93.30 245	73.78 276	94.03 311	75.96 282	96.54 236	96.83 202
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
sss		87.23 258	86.82 253	88.46 273	93.96 260	77.94 251	86.84 296	92.78 257	77.59 277	87.61 287	91.83 273	78.75 254	91.92 322	77.84 266	94.20 284	95.52 248

BH-w/o		87.21 259	87.02 250	87.79 281	94.77 238	77.27 261	87.90 282	93.21 251	81.74 249	89.99 248	88.39 312	83.47 221	96.93 256	71.29 308	92.43 305	89.15 323

thres400		87.20 260	86.52 260	89.24 262	95.77 201	72.94 300	91.89 180	86.00 309	90.84 120	92.61 200	89.80 299	63.93 310	98.28 189	71.27 309	96.54 236	96.51 208

CHOSEN 1792x2688		87.19 261	85.92 267	91.00 225	97.13 115	79.41 229	84.51 313	95.60 198	64.14 332	90.07 245	94.81 198	78.26 258	97.14 249	73.34 294	95.38 262	96.46 217

HyFIR lowres test		87.19 261	85.51 269	92.24 189	97.12 116	80.51 197	85.03 308	96.06 184	66.11 328	91.66 219	92.98 249	70.12 285	99.14 67	75.29 288	95.23 265	97.07 190

MIMVSNet		87.13 263	86.54 259	88.89 266	96.05 186	76.11 272	94.39 104	88.51 288	81.37 251	88.27 279	96.75 107	72.38 278	95.52 289	65.71 326	95.47 259	95.03 256

tfpn200view9		87.05 264	86.52 260	88.67 270	95.77 201	72.94 300	91.89 180	86.00 309	90.84 120	92.61 200	89.80 299	63.93 310	98.28 189	71.27 309	96.54 236	94.79 261

cascas		87.02 265	86.28 264	89.25 261	91.56 295	76.45 268	84.33 314	96.78 148	71.01 310	86.89 293	85.91 323	81.35 240	96.94 255	83.09 221	95.60 254	94.35 271

WTY-MVS		86.93 266	86.50 262	88.24 275	94.96 231	74.64 280	87.19 292	92.07 270	78.29 274	88.32 278	91.59 279	78.06 259	94.27 308	74.88 290	93.15 297	95.80 237

HY-MVS	82.50 18	86.81 267	85.93 266	89.47 250	93.63 267	77.93 252	94.02 113	91.58 274	75.68 285	83.64 312	93.64 235	77.40 263	97.42 238	71.70 305	92.07 310	93.05 299

1314		86.46 268	86.33 263	86.87 288	91.65 294	74.54 282	91.94 177	94.10 233	74.28 292	84.78 305	87.33 317	83.03 225	95.00 300	78.72 260	91.16 316	91.06 317

LP		86.29 269	85.35 270	89.10 263	87.80 326	76.21 270	89.92 246	90.99 278	84.86 222	87.66 285	92.32 265	70.40 284	96.48 270	81.94 229	82.24 335	94.63 264

Patchmatch-test		86.10 270	86.01 265	86.38 292	90.63 303	74.22 287	89.57 256	86.69 303	85.73 211	89.81 254	92.83 250	65.24 305	91.04 325	77.82 268	95.78 252	93.88 283

tfpn_ndepth		85.85 271	85.15 272	87.98 277	95.19 228	75.36 278	92.79 143	83.18 332	86.97 195	89.92 249	86.43 321	57.44 332	97.85 217	78.18 263	96.22 244	90.72 319

thres200		85.85 271	85.18 271	87.88 280	94.44 252	72.52 302	89.08 269	86.21 306	88.57 163	91.44 221	88.40 311	64.22 308	98.00 207	68.35 318	95.88 251	93.12 298

EPNet_dtu		85.63 273	84.37 275	89.40 257	86.30 336	74.33 286	91.64 196	88.26 290	84.84 223	72.96 341	89.85 297	71.27 282	97.69 229	76.60 277	97.62 207	96.18 227
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
PatchmatchNet		85.22 274	84.64 274	86.98 287	89.51 317	69.83 312	90.52 226	87.34 300	78.87 270	87.22 290	92.74 253	66.91 294	96.53 267	81.77 231	86.88 326	94.58 265
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
CVMVSNet		85.16 275	84.72 273	86.48 290	92.12 291	70.19 309	92.32 163	88.17 293	56.15 339	90.64 235	95.85 157	67.97 290	96.69 264	88.78 156	90.52 318	92.56 305

JIA-IIPM		85.08 276	83.04 284	91.19 221	87.56 328	86.14 136	89.40 261	84.44 330	88.98 153	82.20 321	97.95 48	56.82 334	96.15 280	76.55 278	83.45 331	91.30 315

MVS		84.98 277	84.30 276	87.01 286	91.03 297	77.69 257	91.94 177	94.16 232	59.36 337	84.23 309	87.50 315	85.66 211	96.80 261	71.79 303	93.05 300	86.54 329

test1235678		84.54 278	83.85 280	86.59 289	93.81 266	73.41 291	82.38 320	91.79 272	79.43 263	89.50 258	91.61 278	70.59 283	92.94 319	58.14 334	97.40 219	93.44 294

FPMVS		84.50 279	83.28 282	88.16 276	96.32 168	94.49 11	85.76 304	85.47 315	83.09 235	85.20 301	94.26 217	63.79 312	86.58 338	63.72 329	91.88 313	83.40 332

tpm		84.38 280	84.08 277	85.30 301	90.47 306	63.43 334	89.34 262	85.63 313	77.24 281	87.62 286	95.03 193	61.00 327	97.30 244	79.26 257	91.09 317	95.16 252

tpmvs		84.22 281	83.97 278	84.94 302	87.09 333	65.18 326	91.21 206	88.35 289	82.87 238	85.21 300	90.96 286	65.24 305	96.75 262	79.60 256	85.25 327	92.90 301

ADS-MVSNet2		84.01 282	82.20 288	89.41 256	89.04 321	76.37 269	87.57 285	90.98 279	72.71 303	84.46 306	92.45 260	68.08 288	96.48 270	70.58 314	83.97 328	95.38 250

test-LLR		83.58 283	83.17 283	84.79 304	89.68 314	66.86 321	83.08 317	84.52 324	83.07 236	82.85 317	84.78 327	62.86 321	93.49 314	82.85 222	94.86 270	94.03 277

IB-MVS	77.21 19	83.11 284	81.05 296	89.29 259	91.15 296	75.85 275	85.66 305	86.00 309	79.70 261	82.02 324	86.61 318	48.26 342	98.39 181	77.84 266	92.22 308	93.63 289
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
CostFormer		83.09 285	82.21 287	85.73 295	89.27 320	67.01 318	90.35 230	86.47 305	70.42 314	83.52 314	93.23 246	61.18 325	96.85 259	77.21 273	88.26 324	93.34 297

PMMVS		83.00 286	81.11 295	88.66 271	83.81 344	86.44 129	82.24 322	85.65 312	61.75 336	82.07 322	85.64 324	79.75 251	91.59 324	75.99 281	93.09 298	87.94 328

PVSNet	76.22 20	82.89 287	82.37 286	84.48 306	93.96 260	64.38 331	78.60 330	88.61 287	71.50 307	84.43 308	86.36 322	74.27 275	94.60 302	69.87 316	93.69 291	94.46 268

tpmrst		82.85 288	82.93 285	82.64 315	87.65 327	58.99 338	90.14 238	87.90 295	75.54 286	83.93 310	91.63 277	66.79 297	95.36 294	81.21 238	81.54 336	93.57 293

PatchFormer-LS_test		82.62 289	81.71 290	85.32 300	87.92 325	67.31 317	89.03 270	88.20 292	77.58 278	83.79 311	80.50 337	60.96 328	96.42 273	83.86 216	83.59 330	92.23 308

test0.0.03 1		82.48 290	81.47 293	85.48 297	89.70 313	73.57 290	84.73 310	81.64 335	83.07 236	88.13 280	86.61 318	62.86 321	89.10 335	66.24 325	90.29 319	93.77 286

ADS-MVSNet		82.25 291	81.55 292	84.34 307	89.04 321	65.30 325	87.57 285	85.13 322	72.71 303	84.46 306	92.45 260	68.08 288	92.33 321	70.58 314	83.97 328	95.38 250

DSMNet-mixed		82.21 292	81.56 291	84.16 308	89.57 316	70.00 311	90.65 221	77.66 342	54.99 340	83.30 315	97.57 64	77.89 261	90.50 329	66.86 322	95.54 256	91.97 310

gg-mvs-nofinetune		82.10 293	81.02 297	85.34 299	87.46 331	71.04 307	94.74 89	67.56 345	96.44 19	79.43 333	98.99 6	45.24 343	96.15 280	67.18 321	92.17 309	88.85 325

testus		82.09 294	81.78 289	83.03 313	92.35 284	64.37 332	79.44 328	93.27 248	73.08 300	87.06 291	85.21 326	76.80 271	89.27 333	53.30 337	95.48 258	95.46 249

PAPM		81.91 295	80.11 305	87.31 284	93.87 263	72.32 304	84.02 316	93.22 249	69.47 318	76.13 338	89.84 298	72.15 279	97.23 246	53.27 338	89.02 320	92.37 307

tpmp4_e23		81.87 296	80.41 301	86.27 293	89.29 319	67.84 316	91.58 197	87.61 298	67.42 324	78.60 334	92.71 254	56.42 335	96.87 258	71.44 307	88.63 322	94.10 273

tpm2		81.46 297	80.35 303	84.80 303	89.90 312	65.14 327	90.44 228	85.36 316	65.82 330	82.05 323	92.44 262	57.94 331	96.69 264	70.71 313	88.49 323	92.56 305

PMMVS2		81.31 298	83.44 281	74.92 326	90.52 305	46.49 343	69.19 338	85.23 321	84.30 226	87.95 282	94.71 205	76.95 269	84.36 340	64.07 327	98.09 184	93.89 282

new_pmnet		81.22 299	81.01 298	81.86 317	90.92 300	70.15 310	84.03 315	80.25 340	70.83 312	85.97 297	89.78 302	67.93 291	84.65 339	67.44 320	91.90 312	90.78 318

test-mter		81.21 300	80.01 306	84.79 304	89.68 314	66.86 321	83.08 317	84.52 324	73.85 296	82.85 317	84.78 327	43.66 346	93.49 314	82.85 222	94.86 270	94.03 277

EPMVS		81.17 301	80.37 302	83.58 310	85.58 339	65.08 328	90.31 232	71.34 344	77.31 280	85.80 299	91.30 280	59.38 329	92.70 320	79.99 249	82.34 334	92.96 300

pmmvs3		80.83 302	78.96 309	86.45 291	87.23 332	77.48 258	84.87 309	82.31 333	63.83 333	85.03 302	89.50 306	49.66 340	93.10 316	73.12 297	95.10 267	88.78 327

DWT-MVSNet_test		80.74 303	79.18 308	85.43 298	87.51 330	66.87 320	89.87 250	86.01 308	74.20 294	80.86 328	80.62 336	48.84 341	96.68 266	81.54 233	83.14 333	92.75 303

E-PMN		80.72 304	80.86 299	80.29 320	85.11 340	68.77 314	72.96 334	81.97 334	87.76 183	83.25 316	83.01 333	62.22 324	89.17 334	77.15 274	94.31 282	82.93 333

tpm cat1		80.61 305	79.46 307	84.07 309	88.78 323	65.06 329	89.26 265	88.23 291	62.27 335	81.90 325	89.66 305	62.70 323	95.29 297	71.72 304	80.60 337	91.86 313

1111		80.36 306	81.32 294	77.48 323	94.61 248	44.56 344	81.59 323	90.66 281	86.78 199	90.60 236	93.52 240	30.37 349	90.67 326	66.36 323	97.42 218	97.20 187

EMVS		80.35 307	80.28 304	80.54 319	84.73 342	69.07 313	72.54 336	80.73 337	87.80 182	81.66 326	81.73 334	62.89 320	89.84 331	75.79 287	94.65 276	82.71 334

CHOSEN 280x420		80.04 308	77.97 312	86.23 294	90.13 310	74.53 283	72.87 335	89.59 284	66.38 327	76.29 337	85.32 325	56.96 333	95.36 294	69.49 317	94.72 274	88.79 326

dp		79.28 309	78.62 310	81.24 318	85.97 338	56.45 340	86.91 295	85.26 320	72.97 302	81.45 327	89.17 308	56.01 337	95.45 292	73.19 296	76.68 339	91.82 314

TESTMET0.1,1		79.09 310	78.04 311	82.25 316	87.52 329	64.03 333	83.08 317	80.62 338	70.28 315	80.16 332	83.22 332	44.13 345	90.56 328	79.95 250	93.36 292	92.15 309

MVS-HIRNet		78.83 311	80.60 300	73.51 327	93.07 275	47.37 342	87.10 293	78.00 341	68.94 319	77.53 336	97.26 81	71.45 281	94.62 301	63.28 330	88.74 321	78.55 337

test12356		76.35 312	77.41 313	73.19 328	90.70 301	38.86 347	74.56 332	91.14 276	74.55 290	80.54 331	88.18 313	52.36 339	90.49 330	52.38 339	92.26 307	90.21 322

test2356		75.58 313	73.13 315	82.95 314	86.10 337	66.42 323	75.07 331	84.87 323	70.91 311	80.85 329	80.66 335	38.02 348	88.98 336	49.32 340	92.35 306	93.44 294

PVSNet_0	70.34 21	74.58 314	72.96 316	79.47 321	90.63 303	66.24 324	73.26 333	83.40 331	63.67 334	78.02 335	78.35 338	72.53 277	89.59 332	56.68 335	60.05 342	82.57 335

testpf		74.01 315	76.37 314	66.95 329	80.56 345	60.00 336	88.43 280	75.07 343	81.54 250	75.75 339	83.73 329	38.93 347	83.09 341	84.01 213	79.32 338	57.75 339

MVE	59.87 23	73.86 316	72.65 317	77.47 324	87.00 335	74.35 285	61.37 340	60.93 347	67.27 325	69.69 342	86.49 320	81.24 245	72.33 343	56.45 336	83.45 331	85.74 330
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
PNet_i23d		72.03 317	70.91 318	75.38 325	90.46 307	57.84 339	71.73 337	81.53 336	83.86 229	82.21 320	83.49 331	29.97 351	87.80 337	60.78 331	54.12 343	80.51 336

.test1245		64.72 318	70.88 319	46.22 331	94.61 248	44.56 344	81.59 323	90.66 281	86.78 199	90.60 236	93.52 240	30.37 349	90.67 326	66.36 323	3.45 345	3.44 343

pcd1.5k->3k		41.03 319	43.65 321	33.18 332	98.74 26	0.00 351	0.00 341	97.57 81	0.00 345	0.00 347	0.00 347	97.01 6	0.00 348	0.00 345	99.52 45	99.53 17

tmp_tt		37.97 320	44.33 320	18.88 333	11.80 347	21.54 348	63.51 339	45.66 350	4.23 342	51.34 344	50.48 341	59.08 330	22.11 345	44.50 341	68.35 341	13.00 341

cdsmvs_eth3d_5k		23.35 321	31.13 322	0.00 336	0.00 350	0.00 351	0.00 341	95.58 202	0.00 345	0.00 347	91.15 282	93.43 60	0.00 348	0.00 345	0.00 347	0.00 345

test123		9.49 322	12.01 323	1.91 334	2.87 348	1.30 349	82.38 320	1.34 352	1.36 343	2.84 345	6.56 344	2.45 352	0.97 346	2.73 343	5.56 344	3.47 342

testmvs		9.02 323	11.42 324	1.81 335	2.77 349	1.13 350	79.44 328	1.90 351	1.18 344	2.65 346	6.80 343	1.95 353	0.87 347	2.62 344	3.45 345	3.44 343

pcd_1.5k_mvsjas		7.56 324	10.09 325	0.00 336	0.00 350	0.00 351	0.00 341	0.00 353	0.00 345	0.00 347	0.00 347	90.77 117	0.00 348	0.00 345	0.00 347	0.00 345

ab-mvs-re		7.56 324	10.08 326	0.00 336	0.00 350	0.00 351	0.00 341	0.00 353	0.00 345	0.00 347	90.69 292	0.00 354	0.00 348	0.00 345	0.00 347	0.00 345

sosnet-low-res		0.00 326	0.00 327	0.00 336	0.00 350	0.00 351	0.00 341	0.00 353	0.00 345	0.00 347	0.00 347	0.00 354	0.00 348	0.00 345	0.00 347	0.00 345

sosnet		0.00 326	0.00 327	0.00 336	0.00 350	0.00 351	0.00 341	0.00 353	0.00 345	0.00 347	0.00 347	0.00 354	0.00 348	0.00 345	0.00 347	0.00 345

uncertanet		0.00 326	0.00 327	0.00 336	0.00 350	0.00 351	0.00 341	0.00 353	0.00 345	0.00 347	0.00 347	0.00 354	0.00 348	0.00 345	0.00 347	0.00 345

Regformer		0.00 326	0.00 327	0.00 336	0.00 350	0.00 351	0.00 341	0.00 353	0.00 345	0.00 347	0.00 347	0.00 354	0.00 348	0.00 345	0.00 347	0.00 345

uanet		0.00 326	0.00 327	0.00 336	0.00 350	0.00 351	0.00 341	0.00 353	0.00 345	0.00 347	0.00 347	0.00 354	0.00 348	0.00 345	0.00 347	0.00 345

test_part2					98.21 61	89.41 76				96.72 66

test_part1								98.14 28				94.69 44			99.10 90	98.17 127

test11111								98.09 31

sam_mvs1												66.64 298

sam_mvs												66.41 299

semantic-postprocess				91.94 197	93.89 262	79.22 236		93.51 244	91.53 110	95.37 124	96.62 113	77.17 265	98.90 101	91.89 99	94.95 269	97.70 160

ambc				92.98 154	96.88 125	83.01 173	95.92 53	96.38 170		96.41 75	97.48 70	88.26 158	97.80 220	89.96 136	98.93 104	98.12 132

MTGPA								97.62 74

test_post1							90.21 234				5.85 346	65.36 303	96.00 283	79.61 255

test_post											6.07 345	65.74 302	95.84 285

patchmatchnet-post											91.71 275	66.22 301	97.59 233

GG-mvs-BLEND				83.24 312	85.06 341	71.03 308	94.99 83	65.55 346		74.09 340	75.51 339	44.57 344	94.46 304	59.57 333	87.54 325	84.24 331

MTMP								54.62 348

gm-plane-assit					87.08 334	59.33 337			71.22 308		83.58 330		97.20 247	73.95 291

test9_res														88.16 166	98.40 148	97.83 152

TEST9					96.45 155	89.46 73	90.60 223	96.92 137	79.09 269	90.49 238	94.39 214	91.31 104	98.88 107

test_8					96.37 158	89.14 81	90.51 227	96.89 141	79.37 265	90.42 240	94.36 216	91.20 110	98.82 121

agg_prior2														87.06 180	98.36 156	97.98 138

agg_prior					96.20 177	88.89 86		96.88 142		90.21 241			98.78 131

TestCases				96.00 50	98.02 72	92.17 45		98.43 9	90.48 129	95.04 139	96.74 108	92.54 81	97.86 215	85.11 203	98.98 100	97.98 138

test_prior4						89.91 70	90.74 218

test_prior2							90.21 234		89.33 149	90.77 231	94.81 198	90.41 128		88.21 163	98.55 136

test_prior				94.61 97	95.95 194	87.23 115		97.36 105					98.68 149			97.93 142

旧先验2							90.00 244		68.65 320	92.71 199			96.52 268	85.15 201

新几何2							90.02 243

新几何1				93.17 148	97.16 111	87.29 114		94.43 226	67.95 322	91.29 223	94.94 195	86.97 191	98.23 195	81.06 241	97.75 199	93.98 280

旧先验1					96.20 177	84.17 159		94.82 216			95.57 170	89.57 141			97.89 196	96.32 222

无先验							89.94 245	95.75 195	70.81 313				98.59 159	81.17 239		94.81 260

原ACMM2							89.34 262

原ACMM1				92.87 162	96.91 124	84.22 158		97.01 127	76.84 283	89.64 257	94.46 210	88.00 168	98.70 147	81.53 234	98.01 190	95.70 242

test222					96.95 120	85.27 149	88.83 274	93.61 241	65.09 331	90.74 233	94.85 197	84.62 218			97.36 220	93.91 281

testdata2													98.03 206	80.24 247

segment_acmp												92.14 86

testdata				91.03 222	96.87 126	82.01 179		94.28 230	71.55 306	92.46 203	95.42 177	85.65 212	97.38 243	82.64 225	97.27 222	93.70 288

testdata1							88.96 272		88.44 168

test12				94.43 111	95.95 194	86.75 124		96.24 178		89.76 255		89.79 139	98.79 128		97.95 193	97.75 157

plane_prior7					97.71 89	88.68 90

plane_prior6					97.21 109	88.23 103						86.93 192

plane_prior5								97.81 62					98.95 97	89.26 148	98.51 141	98.60 108

plane_prior4											95.59 166

plane_prior3						88.43 101			90.35 134	93.31 182

plane_prior2							94.56 99		91.74 105

plane_prior1					97.38 104

plane_prior						88.12 104	93.01 135		88.98 153						98.06 186

n2								0.00 353

nn								0.00 353

door-mid								92.13 269

lessismore_v0				93.87 129	98.05 70	83.77 164		80.32 339		97.13 52	97.91 52	77.49 262	99.11 72	92.62 80	98.08 185	98.74 97

LGP-MVS_train				96.84 36	98.36 53	92.13 47		98.25 19	91.78 101	97.07 53	97.22 83	96.38 12	99.28 53	92.07 93	99.59 34	99.11 52

test11								96.65 154

door								91.26 275

HQP5-MVS						84.89 151

HQP-NCC					96.36 163		91.37 201		87.16 191	88.81 267

ACMP_Plane					96.36 163		91.37 201		87.16 191	88.81 267

BP-MVS														86.55 188

HQP4-MVS										88.81 267			98.61 155			98.15 129

HQP3-MVS								97.31 109							97.73 200

HQP2-MVS												84.76 216

NP-MVS					96.82 128	87.10 118					93.40 243

MDTV_nov1_ep13_2view						42.48 346	88.45 279		67.22 326	83.56 313		66.80 295		72.86 298		94.06 276

MDTV_nov1_ep13			83.88 279		89.42 318	61.52 335	88.74 275	87.41 299	73.99 295	84.96 304	94.01 229	65.25 304	95.53 288	78.02 264	93.16 296

ACMMP++_ref															98.82 118

ACMMP++															99.25 75

Test By Simon												90.61 124

ITE_SJBPF				95.95 52	97.34 106	93.36 37		96.55 160	91.93 93	94.82 145	95.39 180	91.99 90	97.08 251	85.53 197	97.96 192	97.41 175

DeepMVS_CX				53.83 330	70.38 346	64.56 330		48.52 349	33.01 341	65.50 343	74.21 340	56.19 336	46.64 344	38.45 342	70.07 340	50.30 340

High-resolution multi-view benchmark