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.

LTVRE_ROB	95.06 1	97.73 1	98.39 2	96.95 1	96.33 48	96.94 32	98.30 22	94.90 15	98.61 2	97.73 3	97.97 32	98.57 28	95.74 7	99.24 1	98.70 4	98.72 7	98.70 1
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
COLMAP_ROB	93.74 2	97.09 8	97.98 5	96.05 18	95.97 58	97.78 9	98.56 12	91.72 73	97.53 7	96.01 17	98.14 26	98.76 19	95.28 8	98.76 11	98.23 11	98.77 5	96.67 36
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
3Dnovator+	92.82 3	95.22 50	95.16 61	95.29 35	96.17 52	96.55 38	97.64 44	94.02 31	94.16 39	94.29 49	92.09 141	93.71 150	91.90 56	96.68 62	96.51 45	97.70 47	96.40 39

DeepC-MVS	92.47 4	96.44 15	96.75 22	96.08 17	97.57 7	97.19 28	97.96 34	94.28 24	95.29 21	94.92 37	98.31 22	96.92 85	93.69 29	96.81 59	96.50 46	98.06 38	96.27 42
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
3Dnovator	91.81 5	93.36 98	94.27 86	92.29 112	92.99 152	95.03 87	95.76 103	87.79 159	93.82 44	92.38 94	92.19 140	93.37 154	88.14 123	95.26 90	94.85 85	96.69 74	95.40 56

DeepC-MVS_fast	91.38 6	94.73 58	94.98 63	94.44 51	96.83 34	96.12 52	96.69 69	92.17 60	92.98 57	93.72 64	94.14 119	95.45 121	90.49 103	95.73 79	95.30 73	96.71 73	95.13 63
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepPCF-MVS	90.68 7	94.56 61	94.92 65	94.15 57	94.11 103	95.71 64	97.03 51	90.65 95	93.39 51	94.08 54	95.29 96	94.15 144	93.21 37	95.22 91	94.92 84	95.82 115	95.75 52

ACMH	90.17 8	96.61 11	97.69 11	95.35 31	95.29 75	96.94 32	98.43 16	92.05 65	98.04 5	95.38 22	98.07 29	99.25 7	93.23 36	98.35 16	97.16 36	97.72 45	96.00 46
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMM	90.06 9	96.31 18	96.42 31	96.19 15	97.21 19	97.16 30	98.71 5	93.79 36	94.35 35	93.81 61	92.80 134	98.23 44	95.11 9	98.07 23	97.45 25	98.51 18	96.86 30
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMH+	89.90 10	96.27 19	97.52 12	94.81 47	95.19 77	97.18 29	97.97 33	92.52 49	96.72 9	90.50 130	97.31 59	99.11 9	94.10 23	98.67 12	97.90 15	98.56 16	95.79 50

ACMP	89.62 11	95.96 31	96.28 37	95.59 24	96.58 42	97.23 27	98.26 24	93.22 44	92.33 70	92.31 96	94.29 118	98.73 21	94.68 15	98.04 24	97.14 37	98.47 21	96.17 44
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
OpenMVS	89.22 12	91.09 137	91.42 142	90.71 130	92.79 158	93.61 134	92.74 168	85.47 188	86.10 169	90.73 123	85.71 198	93.07 157	86.69 131	94.07 121	93.34 119	95.86 111	94.02 81

TAPA-MVS	88.94 13	93.78 84	94.31 84	93.18 98	94.14 101	95.99 57	95.74 104	86.98 172	93.43 49	93.88 60	90.16 160	96.88 87	91.05 86	94.33 109	93.95 105	97.28 57	95.40 56
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
PCF-MVS	87.46 14	92.44 122	91.80 137	93.19 97	94.66 86	95.80 62	96.37 92	90.19 100	87.57 153	92.23 97	89.26 167	93.97 146	89.24 111	91.32 169	90.82 165	96.46 80	93.86 84
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
PLC	87.27 15	93.08 107	92.92 123	93.26 93	94.67 85	95.03 87	94.38 129	90.10 101	91.69 84	92.14 98	87.24 186	93.91 147	91.61 65	95.05 95	94.73 95	96.67 75	92.80 103
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
PMVS	87.16 16	95.88 35	96.47 30	95.19 38	97.00 26	96.02 55	96.70 67	91.57 77	94.43 33	95.33 23	97.16 63	95.37 123	92.39 50	98.89 10	98.72 3	98.17 33	94.71 69
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
IB-MVS	86.01 17	88.24 169	87.63 178	88.94 157	92.03 178	91.77 164	92.40 173	85.58 187	78.24 216	84.85 168	71.99 232	93.45 152	83.96 146	93.48 129	92.33 129	94.84 145	92.15 120
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
CMPMVS	66.55 18	85.55 188	87.46 181	83.32 204	84.99 223	81.97 212	79.19 234	75.93 220	79.32 209	88.82 144	85.09 199	91.07 164	82.12 159	92.56 145	89.63 175	88.84 195	92.56 111
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MVE	60.41 19	73.21 228	80.84 209	64.30 231	56.34 238	57.24 239	75.28 238	72.76 224	87.14 161	41.39 239	86.31 194	85.30 187	80.66 171	86.17 206	83.36 201	59.35 236	80.38 202
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
Anonymous20240521		88.80 159	92.64 127	84.33 202	93.67 129	92.83 146	90.74 195	88.29 149	86.80 162	61.65 231	94.89 107	94.99 136	76.46 203	94.73 102	93.50 114	95.18 129	90.73 136

our_test_3					91.78 179	88.87 183	94.37 130

SMA-MVS		96.11 26	96.61 26	95.53 28	97.49 11	97.41 20	97.62 46	93.78 37	94.14 40	94.18 51	97.16 63	94.67 138	92.42 49	97.74 39	97.33 33	97.70 47	97.79 4

tfpn111		87.59 179	86.89 182	88.41 166	92.28 168	93.64 131	93.36 150	88.12 151	80.90 194	80.71 192	73.93 229	82.25 190	79.65 178	94.27 113	94.76 90	96.36 83	88.48 164

conf0.01		85.72 187	83.49 198	88.32 169	92.11 175	93.35 140	93.36 150	88.02 155	80.90 194	80.51 195	74.83 227	59.86 232	79.65 178	93.80 123	94.76 90	96.29 92	86.94 177

conf0.002		84.82 190	81.84 204	88.30 170	92.05 177	93.28 142	93.36 150	88.00 158	80.90 194	80.48 196	73.43 231	52.48 237	79.65 178	93.72 124	92.82 125	96.28 93	86.22 181

thresconf0.02		84.34 194	82.02 203	87.06 182	92.23 172	90.93 171	91.05 190	86.43 180	88.83 140	77.65 210	73.93 229	55.81 233	79.68 177	90.62 174	90.28 168	95.30 123	83.73 189

tfpn_n400		89.03 155	89.39 157	88.61 162	93.98 108	92.33 155	91.83 178	88.97 136	92.97 58	78.90 200	84.93 200	78.24 207	81.77 166	95.00 96	93.67 110	96.22 99	88.59 162

tfpnconf		89.03 155	89.39 157	88.61 162	93.98 108	92.33 155	91.83 178	88.97 136	92.97 58	78.90 200	84.93 200	78.24 207	81.77 166	95.00 96	93.67 110	96.22 99	88.59 162

tfpnview11		88.74 161	88.95 162	88.50 164	93.91 115	92.43 154	91.70 184	88.90 141	90.93 108	78.90 200	84.93 200	78.24 207	81.71 168	94.32 111	94.60 97	95.86 111	87.23 175

tfpn1000		88.13 173	88.68 169	87.49 180	93.94 113	92.64 151	91.50 186	88.70 145	90.12 117	74.35 216	86.74 192	75.27 213	80.14 174	94.16 119	94.66 96	96.33 90	87.16 176

tfpn_ndepth		85.89 186	86.40 186	85.30 195	91.31 185	92.47 153	90.78 193	87.75 161	84.79 176	71.04 223	76.95 224	78.80 206	74.52 209	92.72 138	93.43 117	96.39 81	85.65 184

conf200view11		87.93 175	87.51 179	88.41 166	92.28 168	93.64 131	93.36 150	88.12 151	80.90 194	80.71 192	78.25 220	82.25 190	79.65 178	94.27 113	94.76 90	96.36 83	88.48 164

thres100view900		86.46 184	86.00 189	86.99 184	92.28 168	91.03 170	91.09 189	84.49 196	80.90 194	80.89 190	78.25 220	82.25 190	77.57 196	90.17 177	92.84 124	95.63 117	86.57 180

tfpnnormal		92.45 121	94.77 71	89.74 146	93.95 111	93.44 139	93.25 157	88.49 147	95.27 23	83.20 177	96.51 73	96.23 105	83.17 150	95.47 81	94.52 100	96.38 82	91.97 124

tfpn200view9		87.94 174	87.51 179	88.44 165	92.28 168	93.63 133	93.35 154	88.11 153	80.90 194	80.89 190	78.25 220	82.25 190	79.65 178	94.27 113	94.76 90	96.36 83	88.48 164

view600		89.09 154	88.78 167	89.46 153	93.59 131	93.33 141	93.92 142	87.76 160	87.40 154	82.79 179	81.29 214	80.71 200	82.59 157	94.28 112	95.72 65	96.12 105	88.70 161

view800		89.42 150	89.11 160	89.78 144	94.00 104	93.71 128	93.96 140	88.47 148	88.10 146	82.91 178	82.61 212	79.85 203	83.10 151	94.92 98	95.38 71	96.26 97	89.19 154

conf0.05thres1000		91.24 136	91.85 136	90.53 132	94.59 91	94.56 106	94.33 134	89.52 123	93.67 45	83.77 175	91.04 147	79.10 205	83.98 144	96.66 64	95.56 69	96.98 70	92.36 116

tfpn		87.65 178	85.66 190	89.96 142	94.36 95	93.94 124	93.85 143	89.02 134	88.71 141	82.78 180	83.79 207	53.79 234	83.43 149	95.35 84	94.54 99	96.35 87	89.51 152

ESAPD		95.63 41	96.35 33	94.80 49	96.76 35	97.29 24	97.74 42	94.15 28	91.69 84	90.01 136	96.65 71	97.29 76	92.45 48	97.41 42	97.18 34	97.67 50	96.95 25

CHOSEN 280x420		79.24 214	78.26 218	80.38 210	79.60 230	68.80 237	89.32 208	75.38 221	77.25 220	78.02 209	75.57 226	76.17 212	81.19 170	88.61 190	81.39 207	78.79 225	80.03 205

CANet		93.07 108	93.05 122	93.10 102	95.90 61	95.41 74	95.88 100	91.94 68	84.77 177	93.36 71	94.05 121	95.25 130	86.25 134	94.33 109	93.94 106	95.30 123	93.58 88

Fast-Effi-MVS+-dtu		89.57 149	88.42 172	90.92 128	93.35 140	91.57 166	93.01 161	95.71 9	78.94 214	87.65 153	84.68 203	93.14 156	82.00 160	90.84 172	91.01 163	93.78 171	88.77 160

Effi-MVS+-dtu		92.32 127	91.66 139	93.09 103	95.13 79	94.73 98	94.57 128	92.14 61	81.74 190	90.33 132	88.13 177	95.91 114	89.24 111	94.23 118	93.65 113	97.12 62	93.23 94

CANet_DTU		88.95 158	89.51 156	88.29 171	93.12 149	91.22 169	93.61 145	83.47 203	80.07 205	90.71 127	89.19 168	93.68 151	76.27 205	91.44 168	91.17 162	92.59 182	89.83 146

MVS_0304		93.92 75	93.81 97	94.05 61	96.06 56	96.00 56	96.43 82	92.76 47	85.99 170	94.43 46	94.04 122	97.08 80	88.12 124	94.65 105	94.20 104	96.47 78	94.71 69

HSP-MVS		95.04 53	95.45 57	94.57 50	96.87 28	97.77 10	98.71 5	93.88 34	91.21 102	91.48 112	95.36 93	98.37 38	90.73 94	94.37 108	92.98 122	95.77 116	98.08 3

TSAR-MVS + MP.		95.99 30	96.57 28	95.31 33	96.87 28	96.50 43	98.71 5	91.58 76	93.25 52	92.71 85	96.86 69	96.57 96	93.92 24	98.09 21	97.91 14	98.08 36	96.81 32

OPM-MVS		95.96 31	96.59 27	95.23 36	96.67 39	96.52 42	97.86 37	93.28 43	95.27 23	93.46 70	96.26 76	98.85 17	92.89 43	97.09 48	96.37 49	97.22 61	95.78 51

ACMMP_Plus		95.86 36	96.18 39	95.47 30	97.11 22	97.26 25	98.37 21	93.48 42	93.49 47	93.99 56	95.61 86	94.11 145	92.49 47	97.87 31	97.44 26	97.40 53	97.52 8

ambc			94.61 75		98.09 5	95.14 84	91.71 183		94.18 38	96.46 14	96.26 76	96.30 102	91.26 75	94.70 103	92.00 141	93.45 173	93.67 85

zzz-MVS		96.18 22	96.01 44	96.38 8	98.30 2	96.18 50	98.51 14	94.48 22	94.56 29	94.81 42	91.73 144	96.96 83	94.30 22	98.09 21	97.83 16	97.91 42	96.73 33

Effi-MVS+		92.93 110	92.16 134	93.83 73	94.29 96	93.53 137	95.04 118	92.98 46	85.27 174	94.46 44	90.24 159	95.34 125	89.99 107	93.72 124	94.23 103	96.22 99	92.79 104

new-patchmatchnet		84.45 193	88.75 168	79.43 213	93.28 141	81.87 213	81.68 231	83.48 202	94.47 30	71.53 222	98.33 19	97.88 66	58.61 226	90.35 175	77.33 218	87.99 197	81.05 199

pmmvs6		94.58 60	97.30 16	91.40 124	94.84 84	94.61 102	93.40 149	92.43 53	98.51 3	85.61 165	98.73 10	99.53 3	84.40 143	97.88 30	97.03 38	97.72 45	94.79 67

pmmvs5		88.63 162	89.70 154	87.39 181	89.24 204	90.64 175	91.87 177	82.13 207	83.34 185	87.86 152	94.58 111	96.15 109	79.87 175	87.33 200	89.07 182	93.39 175	86.76 178

Fast-Effi-MVS+		92.93 110	92.64 127	93.27 92	93.81 121	93.88 125	95.90 99	90.61 96	83.98 182	92.71 85	92.81 133	96.22 106	90.67 96	94.90 100	93.92 107	95.92 110	92.77 105

Anonymous20231211		95.36 47	98.43 1	91.78 120	95.89 63	96.12 52	95.23 116	95.91 8	99.42 1	76.79 211	98.87 5	99.94 1	88.19 122	98.64 13	98.50 5	98.66 10	97.49 9

pmmvs-eth3d		92.34 125	92.33 130	92.34 111	92.67 159	90.67 174	96.37 92	89.06 133	90.98 107	93.60 68	97.13 65	97.02 82	88.29 121	90.20 176	91.42 157	94.07 167	88.89 159

GG-mvs-BLEND		54.28 233	77.89 222	26.72 235	0.37 242	83.31 208	70.04 239	0.39 239	74.71 226	5.36 242	68.78 234	83.06 189	0.62 239	83.73 216	78.99 216	83.55 217	72.68 227

Anonymous20231206		87.45 180	89.66 155	84.87 197	94.00 104	87.73 191	91.36 187	86.41 181	88.89 138	75.03 213	92.59 136	96.82 89	72.48 212	89.72 181	88.06 185	89.93 191	83.81 188

MTAPA										94.88 39		96.88 87

MTMP										95.43 21		97.25 77

gm-plane-assit		86.15 185	82.51 201	90.40 134	95.81 65	92.29 157	97.99 31	84.66 195	92.15 75	93.15 79	97.84 38	44.65 239	78.60 185	88.02 197	85.95 194	92.20 183	76.69 215

train_agg		93.89 78	93.46 112	94.40 53	97.35 14	93.78 127	97.63 45	92.19 59	88.12 145	90.52 129	93.57 127	95.78 115	92.31 52	94.78 101	93.46 115	96.36 83	94.70 71

gg-mvs-nofinetune		88.32 165	88.81 165	87.75 177	93.07 151	89.37 181	89.06 209	95.94 7	95.29 21	87.15 155	97.38 58	76.38 211	68.05 218	91.04 171	89.10 181	93.24 177	83.10 193

MS-PatchMatch		87.72 177	88.62 171	86.66 188	90.81 194	88.18 184	90.92 191	82.25 206	85.86 171	80.40 197	90.14 161	89.29 174	84.93 138	89.39 185	89.12 180	90.67 187	88.34 168

Patchmatch-RL test							8.96 242

tmp_tt				28.44 234	36.05 239	15.86 241	21.29 241	6.40 236	54.52 238	51.96 237	50.37 237	38.68 242	9.55 236	61.75 236	59.66 234	45.36 238

canonicalmvs		93.38 97	94.36 82	92.24 113	93.94 113	96.41 47	94.18 137	90.47 99	93.07 56	88.47 148	88.66 171	93.78 149	88.80 115	95.74 78	95.75 64	97.57 51	97.13 16

anonymousdsp		95.45 45	96.70 25	93.99 65	88.43 210	92.05 162	99.18 1	85.42 190	94.29 36	96.10 16	98.63 13	99.08 11	96.11 1	97.77 37	97.41 29	98.70 8	97.69 7

v144192		93.89 78	93.85 93	93.94 69	93.50 133	94.33 107	97.12 48	89.49 124	90.89 109	96.49 13	97.78 42	98.27 41	91.89 57	92.17 155	91.70 146	95.19 128	91.78 129

v1921920		93.90 77	93.82 95	94.00 64	93.74 125	94.31 108	97.12 48	89.33 130	91.13 103	96.77 10	97.90 34	98.06 55	91.95 55	91.93 163	91.54 151	95.10 133	91.85 126

FC-MVSNet-train		92.75 116	95.40 58	89.66 149	95.21 76	94.82 95	97.00 53	89.40 127	91.13 103	81.71 188	97.72 44	96.43 100	77.57 196	96.89 55	96.72 42	97.05 67	94.09 80

UA-Net		96.56 12	96.73 23	96.36 10	98.99 1	97.90 7	97.79 41	95.64 10	92.78 61	92.54 89	96.23 79	95.02 134	94.31 21	98.43 15	98.12 12	98.89 3	98.58 2

v1192		93.98 72	93.94 90	94.01 63	93.91 115	94.63 100	97.00 53	89.75 113	91.01 106	96.50 12	97.93 33	98.26 42	91.74 61	92.06 156	92.05 138	95.18 129	91.66 131

FC-MVSNet-test		91.49 135	94.43 80	88.07 174	94.97 81	90.53 177	95.42 113	91.18 84	93.24 53	72.94 219	98.37 18	93.86 148	78.78 183	97.82 35	96.13 56	95.13 131	91.05 134

v1144		93.83 82	93.87 91	93.78 76	93.72 126	94.57 105	96.85 60	89.98 106	91.31 99	95.90 19	97.89 35	98.40 36	91.13 81	92.01 159	92.01 140	95.10 133	90.94 135

sosnet-low-res		0.00 236	0.00 237	0.00 238	0.00 243	0.00 244	0.00 245	0.00 240	0.00 241	0.00 245	0.00 240	0.00 245	0.00 240	0.00 239	0.00 238	0.00 242	0.00 239

HFP-MVS		96.18 22	96.53 29	95.77 21	97.34 16	97.26 25	98.16 29	94.54 18	94.45 31	92.52 90	95.05 102	96.95 84	93.89 26	97.28 44	97.46 24	98.19 31	97.25 10

v148		92.38 124	92.78 125	91.91 117	92.86 156	92.13 161	94.84 121	87.03 171	91.47 91	93.07 82	96.92 68	98.89 14	90.10 106	92.05 157	89.69 173	93.56 172	88.27 169

sosnet		0.00 236	0.00 237	0.00 238	0.00 243	0.00 244	0.00 245	0.00 240	0.00 241	0.00 245	0.00 240	0.00 245	0.00 240	0.00 239	0.00 238	0.00 242	0.00 239

v748		96.05 29	97.00 20	94.95 45	94.41 93	94.77 97	96.72 66	91.03 88	96.12 16	96.71 11	98.74 8	99.59 2	93.55 31	97.97 29	95.96 58	97.28 57	95.84 49

v7n		96.49 14	97.20 18	95.65 23	95.57 71	96.04 54	97.93 35	92.49 51	96.40 12	97.13 7	98.99 4	99.41 4	93.79 28	97.84 34	96.15 54	97.00 69	95.60 54

v1141		93.47 94	93.56 107	93.36 86	93.48 134	94.17 116	96.42 85	89.62 116	91.44 95	94.99 35	97.81 40	98.42 34	90.94 91	92.00 160	91.38 158	94.74 149	89.69 150

v1neww		93.27 100	93.40 116	93.12 99	93.13 145	94.20 112	96.39 88	89.56 119	89.87 125	93.95 57	97.71 46	98.21 47	91.09 83	92.36 148	91.49 152	94.62 155	89.96 143

DI_MVS_plusplus_trai		90.68 139	90.40 148	91.00 127	92.43 163	92.61 152	94.17 138	88.98 135	88.32 144	88.76 146	93.67 126	87.58 179	86.44 133	89.74 180	90.33 167	95.24 127	90.56 140

v7new		93.27 100	93.40 116	93.12 99	93.13 145	94.20 112	96.39 88	89.56 119	89.87 125	93.95 57	97.71 46	98.21 47	91.09 83	92.36 148	91.49 152	94.62 155	89.96 143

HPM-MVS++		95.21 51	94.89 66	95.59 24	97.79 6	95.39 76	97.68 43	94.05 30	91.91 81	94.35 48	93.38 128	95.07 133	92.94 41	96.01 73	95.88 62	96.73 72	96.61 37

XVS					96.86 30	97.48 16	98.73 3			93.28 73		96.82 89				98.17 33

v1240		93.89 78	93.72 100	94.09 58	93.98 108	94.31 108	97.12 48	89.37 128	90.74 113	96.92 9	98.05 30	97.89 63	92.15 54	91.53 167	91.60 149	94.99 138	91.93 125

v18		93.33 99	93.59 105	93.04 104	92.94 153	94.87 94	96.31 95	90.59 97	88.96 135	92.89 84	97.51 54	97.90 62	91.01 89	92.33 152	91.48 155	94.50 160	92.05 122

pm-mvs1		93.27 100	95.94 46	90.16 137	94.13 102	93.66 129	92.61 169	89.91 110	95.73 18	84.28 173	98.51 16	98.29 40	82.80 153	96.44 67	95.76 63	97.25 59	93.21 95

X-MVStestdata					96.86 30	97.48 16	98.73 3			93.28 73		96.82 89				98.17 33

v17		93.60 87	93.85 93	93.30 91	93.15 144	94.99 91	96.46 80	90.81 91	89.58 130	93.61 67	97.66 50	98.15 51	91.19 77	92.60 143	91.61 148	94.61 157	92.37 115

v16		93.53 92	93.80 98	93.20 96	93.10 150	94.98 92	96.43 82	90.81 91	89.39 133	93.12 81	97.63 52	98.01 59	91.19 77	92.60 143	91.65 147	94.58 159	92.36 116

divwei89l23v2f112		93.47 94	93.56 107	93.37 84	93.48 134	94.17 116	96.42 85	89.62 116	91.46 92	95.00 33	97.81 40	98.42 34	90.94 91	92.00 160	91.38 158	94.75 147	89.70 148

v15		94.09 71	94.37 81	93.77 77	93.56 132	95.18 82	96.68 71	91.34 81	91.64 86	94.83 41	98.09 28	98.51 31	91.37 71	92.84 136	91.80 144	94.85 144	92.53 113

v13		94.54 63	94.93 64	94.09 58	93.81 121	95.44 72	96.99 55	91.67 74	92.43 67	95.20 27	98.33 19	98.73 21	91.87 58	93.67 126	92.26 131	95.00 137	93.63 87

v12		94.44 64	94.79 70	94.02 62	93.75 124	95.37 77	96.92 56	91.61 75	92.21 72	95.10 29	98.27 23	98.69 23	91.73 62	93.49 128	92.15 136	94.97 141	93.37 92

X-MVS		95.33 49	95.13 62	95.57 26	97.35 14	97.48 16	98.43 16	94.28 24	92.30 71	93.28 73	86.89 190	96.82 89	91.87 58	97.85 32	97.59 21	98.19 31	96.95 25

v8		93.60 87	93.82 95	93.34 87	93.13 145	95.06 86	96.39 88	90.75 93	89.90 123	94.03 55	97.70 48	98.21 47	91.08 85	92.36 148	91.47 156	94.63 153	92.07 121

v7		93.65 85	93.73 99	93.57 81	93.38 138	94.60 103	96.83 62	89.92 109	89.69 128	95.02 31	97.89 35	98.24 43	91.27 73	92.38 147	92.18 134	94.99 138	91.12 133

v6		93.27 100	93.41 114	93.12 99	93.13 145	94.20 112	96.39 88	89.55 121	89.89 124	93.93 59	97.72 44	98.22 46	91.10 82	92.36 148	91.49 152	94.63 153	89.95 145

v11		94.32 67	94.62 74	93.97 66	93.95 111	95.31 78	96.83 62	91.30 82	91.95 79	95.51 20	98.32 21	98.61 26	91.44 69	92.83 137	92.23 133	94.77 146	93.08 98

v52		96.35 16	97.40 14	95.12 40	93.83 119	95.54 68	97.82 39	88.95 139	96.27 14	97.22 5	99.11 2	99.40 5	95.80 5	98.16 19	96.37 49	97.10 64	96.96 23

V14		94.21 70	94.52 77	93.85 72	93.62 130	95.25 81	96.76 65	91.42 79	91.83 82	94.91 38	98.15 25	98.57 28	91.49 68	93.06 135	91.93 142	94.90 143	92.82 102

v10		93.96 73	94.12 88	93.77 77	93.37 139	95.45 71	96.83 62	91.13 85	89.70 127	95.02 31	97.88 37	98.23 44	91.27 73	92.39 146	92.18 134	94.99 138	93.00 100

V4		96.35 16	97.40 14	95.12 40	93.83 119	95.54 68	97.82 39	88.95 139	96.27 14	97.21 6	99.10 3	99.40 5	95.79 6	98.17 18	96.37 49	97.10 64	96.96 23

v2v482		93.42 96	93.49 111	93.32 88	93.44 137	94.05 118	96.36 94	89.76 112	91.41 96	95.24 25	97.63 52	98.34 39	90.44 104	91.65 165	91.76 145	94.69 150	89.62 151

v1		93.48 93	93.57 106	93.37 84	93.48 134	94.18 115	96.41 87	89.61 118	91.46 92	95.03 30	97.82 39	98.43 33	90.95 90	92.00 160	91.37 160	94.75 147	89.70 148

V42		92.67 117	93.50 110	91.71 121	91.41 183	92.96 144	95.71 106	85.00 191	89.67 129	93.22 76	97.67 49	98.01 59	91.02 88	92.65 140	92.12 137	93.86 169	91.42 132

V9		94.33 66	94.66 73	93.94 69	93.69 128	95.31 78	96.84 61	91.53 78	92.04 78	95.00 33	98.22 24	98.64 24	91.62 64	93.29 130	92.05 138	94.93 142	93.10 97

SD-MVS		95.77 39	96.17 40	95.30 34	96.72 37	96.19 49	97.01 52	93.04 45	94.03 41	92.71 85	96.45 74	96.78 93	93.91 25	96.79 60	95.89 61	98.42 25	97.09 18

GA-MVS		88.76 160	88.04 175	89.59 150	92.32 167	91.46 167	92.28 174	86.62 176	83.82 184	89.84 138	92.51 137	81.94 195	83.53 148	89.41 184	89.27 178	92.95 180	87.90 170

MSLP-MVS++		93.91 76	94.30 85	93.45 83	95.51 72	95.83 61	93.12 159	91.93 69	91.45 94	91.40 113	87.42 185	96.12 110	93.27 34	96.57 66	96.40 48	95.49 120	96.29 40

APDe-MVS		96.23 20	97.22 17	95.08 42	96.66 40	97.56 14	98.63 9	93.69 39	94.62 28	89.80 139	97.73 43	98.13 52	93.84 27	97.79 36	97.63 19	97.87 43	97.08 19

TSAR-MVS + COLMAP		93.06 109	93.65 102	92.36 110	94.62 88	94.28 110	95.36 115	89.46 126	92.18 74	91.64 110	95.55 89	95.27 129	88.60 118	93.24 131	92.50 128	94.46 161	92.55 112

CVMVSNet		88.97 157	89.73 153	88.10 173	87.33 218	85.22 198	94.68 126	78.68 214	88.94 137	86.98 158	95.55 89	85.71 185	89.87 108	91.19 170	89.69 173	91.05 186	91.78 129

TSAR-MVS + ACMM		95.17 52	95.95 45	94.26 55	96.07 55	96.46 44	95.67 108	94.21 27	93.84 43	90.99 122	97.18 62	95.24 131	93.55 31	96.60 65	95.61 68	95.06 135	96.69 35

pmmvs4		89.95 146	89.32 159	90.69 131	91.60 182	89.17 182	94.37 130	87.63 162	88.07 149	91.02 121	94.50 113	90.50 169	86.13 135	86.33 204	89.40 176	93.39 175	87.29 174

EU-MVSNet		91.63 134	92.73 126	90.35 135	88.36 211	87.89 189	96.53 76	81.51 211	92.45 66	91.82 107	96.44 75	97.05 81	93.26 35	94.10 120	88.94 183	90.61 188	92.24 119

test-LLR		80.62 210	77.20 226	84.62 201	93.99 106	75.11 228	87.04 216	87.32 167	70.11 232	78.59 207	83.17 209	71.60 216	73.88 210	82.32 218	79.20 214	86.91 203	78.87 211

TESTMET0.1,1		77.47 224	77.20 226	77.78 221	81.94 227	75.11 228	87.04 216	58.33 234	70.11 232	78.59 207	83.17 209	71.60 216	73.88 210	82.32 218	79.20 214	86.91 203	78.87 211

test-mter		78.71 219	78.35 217	79.12 218	84.03 225	76.58 224	88.51 212	59.06 232	71.06 230	78.87 203	83.73 208	71.83 215	76.44 204	83.41 217	80.61 209	87.79 200	81.24 197

ACMMPR		96.54 13	96.71 24	96.35 11	97.55 9	97.63 11	98.62 10	94.54 18	94.45 31	94.19 50	95.04 104	97.35 75	94.92 13	97.85 32	97.50 23	98.26 29	97.17 15

testgi		86.49 183	90.31 149	82.03 206	95.63 70	88.18 184	93.47 147	84.89 193	93.23 54	69.54 228	87.16 187	97.96 61	60.66 223	91.90 164	89.90 171	87.99 197	83.84 187

test20.03		88.20 171	91.26 143	84.63 200	96.64 41	89.39 180	90.73 196	89.97 107	91.07 105	72.02 221	94.98 105	95.45 121	69.35 214	92.70 139	91.19 161	89.06 194	84.02 186

thres600view7		89.14 153	88.83 164	89.51 152	93.71 127	93.55 135	93.93 141	88.02 155	87.30 157	82.40 183	81.18 215	80.63 201	82.69 156	94.27 113	95.90 60	96.27 95	88.94 158

1111		76.85 225	78.03 221	75.46 225	94.16 99	78.29 221	86.40 222	89.12 131	87.23 158	61.26 233	95.15 99	44.14 240	51.46 232	86.04 207	81.00 208	70.40 235	74.37 221

.test1245		60.07 232	56.75 234	63.93 232	94.16 99	78.29 221	86.40 222	89.12 131	87.23 158	61.26 233	95.15 99	44.14 240	51.46 232	86.04 207	2.51 236	1.21 240	3.92 237

ADS-MVSNet		79.11 216	79.38 212	78.80 219	81.90 228	75.59 226	84.36 227	83.69 199	87.31 155	76.76 212	87.58 183	76.90 210	68.55 217	78.70 226	75.56 222	77.53 226	74.07 223

MP-MVS		96.13 24	95.93 47	96.37 9	98.19 4	97.31 23	98.49 15	94.53 21	91.39 97	94.38 47	94.32 117	96.43 100	94.59 17	97.75 38	97.44 26	98.04 39	96.88 29
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		2.38 234	3.35 235	1.26 237	0.83 240	0.96 243	1.53 243	0.83 237	3.59 239	1.63 244	6.03 238	2.93 243	1.55 238	3.49 237	2.51 236	1.21 240	3.92 237

thres400		88.54 163	88.15 174	88.98 156	93.17 143	92.84 145	93.56 146	86.93 173	86.45 166	82.37 184	79.96 217	81.46 198	81.83 164	93.21 133	94.76 90	96.04 106	88.39 167

test123		2.16 235	2.82 236	1.41 236	0.62 241	1.18 242	1.53 243	0.82 238	2.78 240	2.27 243	4.18 239	1.98 244	1.64 237	2.58 238	3.01 235	1.56 239	4.00 236

thres200		88.29 167	87.88 176	88.76 159	92.50 162	93.55 135	92.47 172	88.02 155	84.80 175	81.44 189	79.28 219	82.20 194	81.83 164	94.27 113	93.67 110	96.27 95	87.40 173

test0.0.03 1		81.51 206	83.30 200	79.42 214	93.99 106	86.50 195	85.93 226	87.32 167	78.16 217	61.62 232	80.78 216	81.78 196	59.87 224	88.40 193	87.27 189	87.78 201	80.19 203

test12356		75.40 227	80.89 208	69.01 229	77.43 234	75.75 225	83.03 229	61.48 230	78.13 218	59.08 235	87.69 182	94.95 137	57.37 227	88.18 195	80.59 210	75.65 230	60.93 233

testus		78.20 221	81.50 206	74.36 227	85.59 221	79.36 218	86.99 218	65.76 227	76.01 222	73.00 218	77.98 223	93.35 155	51.30 234	86.33 204	82.79 203	83.50 218	74.68 220

pmmvs3		81.69 204	83.83 195	79.19 217	78.33 232	78.57 220	89.53 206	58.71 233	78.88 215	84.34 172	88.36 174	91.96 160	77.69 195	87.48 198	82.42 204	86.54 205	79.18 210

testmv		81.49 208	84.76 192	77.67 223	87.67 214	80.25 216	90.12 200	77.62 216	80.34 203	69.71 225	90.92 151	96.47 98	56.57 228	88.58 192	84.92 199	84.33 213	71.86 229

EMVS		77.65 223	77.49 225	77.83 220	87.75 213	71.02 234	81.13 232	70.54 226	86.38 167	74.52 215	89.38 166	80.19 202	78.22 191	89.48 183	67.13 232	74.83 233	58.84 235

E-PMN		77.81 222	77.88 223	77.73 222	88.26 212	70.48 235	80.19 233	71.20 225	86.66 164	72.89 220	88.09 178	81.74 197	78.75 184	90.02 179	68.30 231	75.10 231	59.85 234

test2356		72.95 229	71.24 232	74.95 226	84.89 224	75.49 227	82.67 230	75.38 221	68.02 235	68.65 229	74.40 228	52.81 236	55.61 231	81.50 221	79.80 212	82.50 220	66.70 232

test1235678		81.50 207	84.78 191	77.67 223	87.67 214	80.27 215	90.12 200	77.62 216	80.36 202	69.71 225	90.93 150	96.51 97	56.57 228	88.60 191	84.93 198	84.34 212	71.87 228

PGM-MVS		95.90 34	95.72 50	96.10 16	97.53 10	97.45 19	98.55 13	94.12 29	90.25 115	93.71 65	93.20 130	97.18 79	94.63 16	97.68 40	97.34 32	98.08 36	96.97 22

MCST-MVS		93.60 87	93.40 116	93.83 73	95.30 74	95.40 75	96.49 78	90.87 90	90.08 118	91.72 109	90.28 158	95.99 113	91.69 63	93.94 122	92.99 121	96.93 71	95.13 63

MVS_Test		90.19 142	90.58 145	89.74 146	92.12 174	91.74 165	92.51 170	88.54 146	82.80 187	87.50 154	94.62 110	95.02 134	83.97 145	88.69 189	89.32 177	93.79 170	91.85 126

MDA-MVSNet-bldmvs		89.75 147	91.67 138	87.50 179	74.25 236	90.88 172	94.68 126	85.89 183	91.64 86	91.03 120	95.86 83	94.35 143	89.10 113	96.87 57	86.37 193	90.04 189	85.72 183

CDPH-MVS		93.96 73	93.86 92	94.08 60	96.31 49	95.84 60	96.92 56	91.85 70	87.21 160	91.25 118	92.83 132	96.06 111	91.05 86	95.57 80	94.81 86	97.12 62	94.72 68

diffmvs		88.28 168	88.88 163	87.58 178	89.51 202	88.07 187	91.88 176	85.83 186	87.31 155	86.34 160	96.01 81	88.90 176	81.90 161	85.49 211	86.61 192	90.04 189	89.77 147

PMMVS2		69.86 231	82.14 202	55.52 233	75.19 235	63.08 238	75.52 237	60.97 231	88.50 143	25.11 241	91.77 142	96.44 99	25.43 235	88.70 188	79.34 213	70.93 234	67.17 230

PM-MVS		92.65 118	93.20 121	92.00 116	92.11 175	90.16 178	95.99 98	84.81 194	91.31 99	92.41 93	95.87 82	96.64 95	92.35 51	93.65 127	92.91 123	94.34 164	91.85 126

PS-CasMVS		97.22 5	97.84 7	96.50 5	97.08 23	97.92 6	98.17 28	97.02 2	94.71 27	95.32 24	98.52 15	98.97 12	92.91 42	99.04 4	98.47 6	98.49 19	97.24 12

UniMVSNet_NR-MVSNet		95.34 48	95.51 55	95.14 39	95.80 66	96.55 38	96.61 74	94.79 16	90.04 120	93.78 62	97.51 54	97.25 77	91.19 77	96.68 62	96.31 52	98.65 12	94.22 77

PEN-MVS		97.16 6	97.87 6	96.33 12	97.20 20	97.97 4	98.25 25	96.86 5	95.09 25	94.93 36	98.66 11	99.16 8	92.27 53	98.98 6	98.39 8	98.49 19	96.83 31

TransMVSNet (Re)		93.55 91	96.32 35	90.32 136	94.38 94	94.05 118	93.30 156	89.53 122	97.15 8	85.12 167	98.83 6	97.89 63	82.21 158	96.75 61	96.14 55	97.35 55	93.46 90

DTE-MVSNet		97.16 6	97.75 9	96.47 6	97.40 12	97.95 5	98.20 27	96.89 4	95.30 20	95.15 28	98.66 11	98.80 18	92.77 46	98.97 7	98.27 10	98.44 23	96.28 41

DU-MVS		95.51 42	95.68 51	95.33 32	96.45 46	96.44 45	96.61 74	95.32 11	89.97 121	93.78 62	97.46 56	98.07 54	91.19 77	97.03 49	96.53 44	98.61 14	94.22 77

UniMVSNet (Re)		95.46 43	95.86 48	95.00 44	96.09 53	96.60 37	96.68 71	94.99 13	90.36 114	92.13 99	97.64 51	98.13 52	91.38 70	96.90 54	96.74 41	98.73 6	94.63 72

CP-MVSNet		96.97 10	97.42 13	96.44 7	97.06 24	97.82 8	98.12 30	96.98 3	93.50 46	95.21 26	97.98 31	98.44 32	92.83 45	98.93 8	98.37 9	98.46 22	96.91 28

WR-MVS_H		97.06 9	97.78 8	96.23 14	96.74 36	98.04 3	98.25 25	97.32 1	94.40 34	93.71 65	98.55 14	98.89 14	92.97 39	98.91 9	98.45 7	98.38 28	97.19 14

WR-MVS		97.53 3	98.20 4	96.76 3	96.93 27	98.17 1	98.60 11	96.67 6	96.39 13	94.46 44	99.14 1	98.92 13	94.57 18	99.06 3	98.80 2	99.32 1	96.92 27

NR-MVSNet		94.55 62	95.66 53	93.25 95	94.26 98	96.44 45	96.69 69	95.32 11	89.97 121	91.79 108	97.46 56	98.39 37	82.85 152	96.87 57	96.48 47	98.57 15	93.98 82

Baseline_NR-MVSNet		94.85 55	95.35 59	94.26 55	96.45 46	93.86 126	96.70 67	94.54 18	90.07 119	90.17 135	98.77 7	97.89 63	90.64 98	97.03 49	96.16 53	97.04 68	93.67 85

TranMVSNet+NR-MVSNet		95.72 40	96.42 31	94.91 46	96.21 51	96.77 36	96.90 59	94.99 13	92.62 63	91.92 103	98.51 16	98.63 25	90.82 93	97.27 45	96.83 40	98.63 13	94.31 76

TSAR-MVS + GP.		94.25 68	94.81 69	93.60 80	96.52 44	95.80 62	94.37 130	92.47 52	90.89 109	88.92 142	95.34 94	94.38 142	92.85 44	96.36 69	95.62 67	96.47 78	95.28 60

abl_6				91.88 118	93.76 123	94.98 92	95.64 109	88.97 136	86.20 168	90.00 137	86.31 194	94.50 141	87.31 126			95.60 118	92.48 114

mPP-MVS					98.24 3							97.65 71

DWT-MVSNet_training		79.22 215	73.99 231	85.33 194	88.57 208	84.41 203	90.56 198	80.96 213	73.90 229	85.72 164	75.62 225	50.09 238	81.30 169	76.91 231	77.02 219	84.88 208	79.97 206

testpf		72.68 230	66.81 233	79.53 212	86.52 220	73.89 231	83.56 228	88.74 144	58.70 237	79.68 199	71.31 233	53.64 235	62.23 222	68.68 234	66.64 233	76.46 228	74.82 218

SixPastTwentyTwo		97.36 4	97.73 10	96.92 2	97.36 13	96.15 51	98.29 23	94.43 23	96.50 11	96.96 8	98.74 8	98.74 20	96.04 3	99.03 5	97.74 17	98.44 23	97.22 13

LGP-MVS_train		96.10 27	96.29 36	95.87 20	96.72 37	97.35 22	98.43 16	93.83 35	90.81 112	92.67 88	95.05 102	98.86 16	95.01 10	98.11 20	97.37 31	98.52 17	96.50 38

EPNet_dtu		87.40 181	86.27 187	88.72 160	95.68 69	83.37 207	92.09 175	90.08 102	78.11 219	91.29 115	86.33 193	89.74 171	75.39 206	89.07 186	87.89 186	87.81 199	89.38 153
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x2688		86.64 182	86.62 184	86.65 189	90.33 197	87.86 190	93.19 158	83.30 204	83.95 183	82.32 185	87.93 179	89.34 173	86.92 129	85.64 210	84.95 197	83.85 216	86.68 179

EPNet		90.17 143	89.07 161	91.45 123	97.25 18	90.62 176	94.84 121	93.54 41	80.96 193	91.85 105	86.98 189	85.88 184	77.79 193	92.30 153	92.58 127	93.41 174	94.20 79
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
APD-MVS		95.38 46	95.68 51	95.03 43	97.30 17	96.90 34	97.83 38	93.92 32	89.40 131	90.35 131	95.41 92	97.69 70	92.97 39	97.24 46	97.17 35	97.83 44	95.96 47
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
LP		84.09 195	84.31 193	83.85 203	79.40 231	84.34 204	90.26 199	84.02 197	87.99 150	84.66 169	91.61 145	79.13 204	80.58 172	85.90 209	81.59 206	84.16 215	79.59 207

CNVR-MVS		94.24 69	94.47 79	93.96 68	96.56 43	95.67 65	96.43 82	91.95 67	92.08 76	91.28 116	90.51 156	95.35 124	91.20 76	96.34 70	95.50 70	96.34 88	95.88 48

NCCC		93.87 81	93.42 113	94.40 53	96.84 32	95.42 73	96.47 79	92.62 48	92.36 69	92.05 100	83.83 206	95.55 117	91.84 60	95.89 75	95.23 76	96.56 76	95.63 53

CP-MVS		96.21 21	96.16 42	96.27 13	97.56 8	97.13 31	98.43 16	94.70 17	92.62 63	94.13 53	92.71 135	98.03 58	94.54 19	98.00 27	97.60 20	98.23 30	97.05 20

NP-MVS									85.48 172

EG-PatchMatch MVS		94.81 56	95.53 54	93.97 66	95.89 63	94.62 101	95.55 112	88.18 150	92.77 62	94.88 39	97.04 67	98.61 26	93.31 33	96.89 55	95.19 77	95.99 108	93.56 89

tpm cat1		80.03 211	75.93 229	84.81 198	89.31 203	83.26 209	88.86 210	86.55 179	79.24 211	86.10 161	84.22 205	63.62 229	77.37 198	73.43 232	70.88 230	80.67 223	76.87 214

SteuartSystems-ACMMP		95.96 31	96.13 43	95.76 22	97.06 24	97.36 21	98.40 20	94.24 26	91.49 89	91.91 104	94.50 113	96.89 86	94.99 11	98.01 26	97.44 26	97.97 41	97.25 10
Skip Steuart: Steuart Systems R&D Blog.
tpmp4_e23		82.16 201	78.26 218	86.70 187	89.92 198	84.82 200	91.17 188	89.95 108	81.21 192	87.10 156	81.91 213	64.01 228	77.88 192	79.89 225	74.99 225	84.18 214	81.00 200

CostFormer		82.15 202	79.54 211	85.20 196	88.92 206	85.70 197	90.87 192	86.26 182	79.19 212	83.87 174	87.89 181	69.20 220	76.62 202	77.50 230	75.28 223	84.69 209	82.02 195

CR-MVSNet		85.32 189	81.58 205	89.69 148	90.36 196	84.79 201	86.72 220	92.22 56	75.38 224	90.73 123	90.41 157	67.88 222	84.86 139	83.76 214	85.74 195	93.24 177	83.14 191

Patchmtry						83.74 206	86.72 220	92.22 56		90.73 123

PatchT		83.44 196	81.10 207	86.18 190	77.92 233	82.58 211	89.87 203	87.39 166	75.88 223	90.73 123	89.86 162	66.71 225	84.86 139	83.76 214	85.74 195	86.33 206	83.14 191

tpmrst		78.81 218	76.18 228	81.87 207	88.56 209	77.45 223	86.74 219	81.52 210	80.08 204	83.48 176	90.84 152	66.88 223	74.54 207	73.04 233	71.02 229	76.38 229	73.95 224

tpm		81.58 205	78.84 213	84.79 199	91.11 190	79.50 217	89.79 204	83.75 198	79.30 210	92.05 100	90.98 148	64.78 227	74.54 207	80.50 223	76.67 220	77.49 227	80.15 204

DELS-MVS		92.33 126	93.61 104	90.83 129	92.84 157	95.13 85	94.76 124	87.22 170	87.78 152	88.42 150	95.78 85	95.28 128	85.71 137	94.44 107	93.91 108	96.01 107	92.97 101
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		83.42 197	78.40 216	89.28 154	89.79 200	84.79 201	90.64 197	92.11 63	75.38 224	87.10 156	79.80 218	61.99 231	82.79 154	81.88 220	82.07 205	93.23 179	82.87 194

no-one		92.05 132	94.57 76	89.12 155	85.55 222	87.65 192	94.21 136	77.34 218	93.43 49	89.64 140	95.11 101	99.11 9	95.86 4	95.38 83	95.24 75	92.08 185	96.11 45

MVSTER		84.79 191	83.79 196	85.96 191	89.14 205	89.80 179	89.39 207	82.99 205	74.16 228	82.78 180	85.97 196	66.81 224	76.84 200	90.77 173	88.83 184	94.66 151	90.19 142

CPTT-MVS		95.00 54	94.52 77	95.57 26	96.84 32	96.78 35	97.88 36	93.67 40	92.20 73	92.35 95	85.87 197	97.56 72	94.98 12	96.96 52	96.07 57	97.70 47	96.18 43

GBi-Net		89.35 151	90.58 145	87.91 175	91.22 187	94.05 118	92.88 164	90.05 103	79.40 206	78.60 204	90.58 153	87.05 180	78.54 186	95.32 86	94.98 81	96.17 102	92.67 107

PVSNet_Blended_VisFu		93.60 87	93.41 114	93.83 73	96.31 49	95.65 66	95.71 106	90.58 98	88.08 148	93.17 78	95.29 96	92.20 159	90.72 95	94.69 104	93.41 118	96.51 77	94.54 73

PVSNet_BlendedMVS		90.09 144	90.12 150	90.05 140	92.40 164	92.74 149	91.74 180	85.89 183	80.54 200	90.30 133	88.54 172	95.51 118	84.69 141	92.64 141	90.25 169	95.28 125	90.61 138

PVSNet_Blended		90.09 144	90.12 150	90.05 140	92.40 164	92.74 149	91.74 180	85.89 183	80.54 200	90.30 133	88.54 172	95.51 118	84.69 141	92.64 141	90.25 169	95.28 125	90.61 138

FMVSNet5		79.08 217	78.83 214	79.38 215	87.52 217	86.78 193	87.64 214	78.15 215	69.54 234	70.64 224	65.97 236	65.44 226	63.87 221	90.17 177	90.46 166	88.48 196	83.45 190

test1		89.35 151	90.58 145	87.91 175	91.22 187	94.05 118	92.88 164	90.05 103	79.40 206	78.60 204	90.58 153	87.05 180	78.54 186	95.32 86	94.98 81	96.17 102	92.67 107

new_pmnet		76.65 226	83.52 197	68.63 230	82.60 226	72.08 233	76.76 236	64.17 228	84.41 179	49.73 238	91.77 142	91.53 162	56.16 230	86.59 202	83.26 202	82.37 221	75.02 217

FMVSNet3		87.90 176	88.63 170	87.04 183	89.78 201	93.46 138	91.62 185	90.05 103	79.40 206	78.60 204	90.58 153	87.05 180	77.07 199	88.03 196	89.86 172	95.12 132	92.04 123

dps		81.42 209	77.88 223	85.56 192	87.67 214	85.17 199	88.37 213	87.46 164	74.37 227	84.55 170	86.80 191	62.18 230	80.20 173	81.13 222	77.52 217	85.10 207	77.98 213

FMVSNet2		90.28 141	92.04 135	88.23 172	91.22 187	94.05 118	92.88 164	90.69 94	86.53 165	79.89 198	94.38 116	92.73 158	78.54 186	91.64 166	92.26 131	96.17 102	92.67 107

FMVSNet1		92.86 113	95.26 60	90.06 139	92.40 164	95.16 83	94.37 130	92.22 56	93.18 55	82.16 187	96.76 70	97.48 73	81.85 163	95.32 86	94.98 81	97.34 56	93.93 83

N_pmnet		79.33 212	84.22 194	73.62 228	91.72 180	73.72 232	86.11 224	76.36 219	92.38 68	53.38 236	95.54 91	95.62 116	59.14 225	84.23 213	74.84 226	75.03 232	73.25 225

UGNet		92.31 128	94.70 72	89.53 151	90.99 191	95.53 70	96.19 96	92.10 64	91.35 98	85.76 162	95.31 95	95.48 120	76.84 200	95.22 91	94.79 88	95.32 122	95.19 61
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
MDTV_nov1_ep13_2view		88.22 170	87.85 177	88.65 161	91.40 184	86.75 194	94.07 139	84.97 192	88.86 139	93.20 77	96.11 80	96.21 108	83.70 147	87.29 201	80.29 211	84.56 210	79.46 208

MDTV_nov1_ep13		82.33 200	79.66 210	85.45 193	88.83 207	83.88 205	90.09 202	81.98 208	79.07 213	88.82 144	88.70 170	73.77 214	78.41 190	80.29 224	76.08 221	84.56 210	75.83 216

MIMVSNet1		92.52 120	94.88 67	89.77 145	96.09 53	91.99 163	96.92 56	89.68 115	95.92 17	84.55 170	96.64 72	98.21 47	78.44 189	96.08 72	95.10 78	92.91 181	90.22 141

MIMVSNet		84.76 192	86.75 183	82.44 205	91.71 181	85.95 196	89.74 205	89.49 124	85.28 173	69.69 227	87.93 179	90.88 167	64.85 220	88.26 194	87.74 187	89.18 193	81.24 197

IterMVS-LS		92.10 130	92.33 130	91.82 119	93.18 142	93.66 129	92.80 167	92.27 55	90.82 111	90.59 128	97.19 61	90.97 166	87.76 125	89.60 182	90.94 164	94.34 164	93.16 96
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet		88.41 164	89.79 152	86.79 186	94.55 92	90.82 173	92.50 171	89.85 111	83.26 186	80.52 194	91.05 146	89.93 170	69.11 215	93.17 134	92.71 126	94.21 166	87.63 171
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
IterMVS		88.32 165	88.25 173	88.41 166	90.83 193	91.24 168	93.07 160	81.69 209	86.77 163	88.55 147	95.61 86	86.91 183	87.01 127	87.38 199	83.77 200	89.29 192	86.06 182
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MVS_111021_LR		93.15 105	93.65 102	92.56 108	93.89 117	92.28 158	95.09 117	86.92 174	91.26 101	92.99 83	94.46 115	96.22 106	90.64 98	95.11 94	93.45 116	95.85 113	92.74 106

HQP-MVS		92.87 112	92.49 129	93.31 89	95.75 67	95.01 90	95.64 109	91.06 87	88.54 142	91.62 111	88.16 176	96.25 104	89.47 110	92.26 154	91.81 143	96.34 88	95.40 56

QAPM		92.57 119	93.51 109	91.47 122	92.91 155	94.82 95	93.01 161	87.51 163	91.49 89	91.21 119	92.24 138	91.70 161	88.74 116	94.54 106	94.39 102	95.41 121	95.37 59

Vis-MVSNet		94.39 65	95.85 49	92.68 107	90.91 192	95.88 59	97.62 46	91.41 80	91.95 79	89.20 141	97.29 60	96.26 103	90.60 102	96.95 53	95.91 59	96.32 91	96.71 34
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet		78.28 220	75.28 230	81.79 208	80.33 229	69.38 236	76.83 235	86.59 177	70.76 231	86.66 159	89.57 164	81.04 199	77.74 194	77.81 229	71.65 228	82.62 219	66.73 231

HyFIR lowres test		88.19 172	86.56 185	90.09 138	91.24 186	92.17 160	94.30 135	88.79 143	84.06 180	85.45 166	89.52 165	85.64 186	88.64 117	85.40 212	87.28 188	92.14 184	81.87 196

EPMVS		79.26 213	78.20 220	80.49 209	87.04 219	78.86 219	86.08 225	83.51 201	82.63 188	73.94 217	89.59 163	68.67 221	72.03 213	78.17 228	75.08 224	80.37 224	74.37 221

TAMVS		82.96 198	86.15 188	79.24 216	90.57 195	83.12 210	87.29 215	75.12 223	84.06 180	65.81 230	92.22 139	88.27 178	69.11 215	88.72 187	87.26 190	87.56 202	79.38 209

IS_MVSNet		92.76 115	93.25 120	92.19 114	94.91 83	95.56 67	95.86 101	92.12 62	88.10 146	82.71 182	93.15 131	88.30 177	88.86 114	97.29 43	96.95 39	98.66 10	93.38 91

RPSCF		95.46 43	96.95 21	93.73 79	95.72 68	95.94 58	95.58 111	88.08 154	95.31 19	91.34 114	96.26 76	98.04 57	93.63 30	98.28 17	97.67 18	98.01 40	97.13 16

Vis-MVSNet (Re-imp)		90.68 139	92.18 132	88.92 158	94.63 87	92.75 148	92.91 163	91.20 83	89.21 134	75.01 214	93.96 125	89.07 175	82.72 155	95.88 76	95.30 73	97.08 66	89.08 157

MVS_111021_HR		93.82 83	94.26 87	93.31 89	95.01 80	93.97 123	95.73 105	89.75 113	92.06 77	92.49 91	94.01 124	96.05 112	90.61 101	95.95 74	94.78 89	96.28 93	93.04 99

CSCG		96.07 28	97.15 19	94.81 47	96.06 56	97.58 13	96.52 77	90.98 89	96.51 10	93.60 68	97.13 65	98.55 30	93.01 38	97.17 47	95.36 72	98.68 9	97.78 5

PatchMatch-RL		89.59 148	88.80 166	90.51 133	92.20 173	88.00 188	91.72 182	86.64 175	84.75 178	88.25 151	87.10 188	90.66 168	89.85 109	93.23 132	92.28 130	94.41 163	85.60 185

TDRefinement		97.59 2	98.32 3	96.73 4	95.90 61	98.10 2	99.08 2	93.92 32	98.24 4	96.44 15	98.12 27	97.86 68	96.06 2	99.24 1	98.93 1	99.00 2	97.77 6

USDC		92.17 129	92.17 133	92.18 115	92.93 154	92.22 159	93.66 144	87.41 165	93.49 47	97.99 1	94.10 120	96.68 94	86.46 132	92.04 158	89.18 179	94.61 157	87.47 172

EPP-MVSNet		93.63 86	93.95 89	93.26 93	95.15 78	96.54 41	96.18 97	91.97 66	91.74 83	85.76 162	94.95 106	84.27 188	91.60 66	97.61 41	97.38 30	98.87 4	95.18 62

PMMVS		81.93 203	83.48 199	80.12 211	72.35 237	75.05 230	88.54 211	64.01 229	77.02 221	82.22 186	87.51 184	91.12 163	79.70 176	86.59 202	86.64 191	93.88 168	80.41 201

ACMMP		96.12 25	96.27 38	95.93 19	97.20 20	97.60 12	98.64 8	93.74 38	92.47 65	93.13 80	93.23 129	98.06 55	94.51 20	97.99 28	97.57 22	98.39 27	96.99 21
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		93.14 106	93.67 101	92.53 109	94.62 88	94.73 98	95.00 119	86.57 178	92.85 60	92.43 92	90.94 149	94.67 138	90.35 105	95.41 82	93.70 109	96.23 98	93.37 92

PatchmatchNet		82.44 199	78.69 215	86.83 185	89.81 199	81.55 214	90.78 193	87.27 169	82.39 189	88.85 143	88.31 175	70.96 218	81.90 161	78.58 227	74.33 227	82.35 222	74.69 219
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS		94.65 59	94.84 68	94.44 51	94.95 82	96.55 38	96.46 80	91.10 86	88.96 135	96.00 18	94.55 112	95.32 126	90.67 96	96.97 51	96.69 43	97.44 52	94.84 65

OMC-MVS		94.74 57	95.46 56	93.91 71	94.62 88	96.26 48	96.64 73	89.36 129	94.20 37	94.15 52	94.02 123	97.73 69	91.34 72	96.15 71	95.04 80	97.37 54	94.80 66

AdaColmap		92.41 123	91.49 141	93.48 82	95.96 59	95.02 89	95.37 114	91.73 72	87.97 151	91.28 116	82.82 211	91.04 165	90.62 100	95.82 77	95.07 79	95.95 109	92.67 107

DeepMVS_CX						47.68 240	53.20 240	19.21 235	63.24 236	26.96 240	66.50 235	69.82 219	66.91 219	64.27 235		54.91 237	72.72 226

TinyColmap		93.17 104	93.33 119	93.00 105	93.84 118	92.76 147	94.75 125	88.90 141	93.97 42	97.48 4	95.28 98	95.29 127	88.37 120	95.31 89	91.58 150	94.65 152	89.10 156

MAR-MVS		91.86 133	91.14 144	92.71 106	94.29 96	94.24 111	94.91 120	91.82 71	81.66 191	93.32 72	84.51 204	93.42 153	86.86 130	95.16 93	94.44 101	95.05 136	94.53 74
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		92.09 131	92.84 124	91.22 125	92.55 160	92.97 143	93.42 148	85.43 189	90.24 116	91.83 106	94.70 109	94.59 140	88.48 119	94.91 99	93.31 120	95.59 119	89.15 155

LS3D		95.83 38	96.35 33	95.22 37	96.47 45	97.49 15	97.99 31	92.35 54	94.92 26	94.58 43	94.88 108	95.11 132	91.52 67	98.48 14	98.05 13	98.42 25	95.49 55

CLD-MVS		92.81 114	94.32 83	91.05 126	95.39 73	95.31 78	95.82 102	81.44 212	89.40 131	91.94 102	95.86 83	97.36 74	85.83 136	95.35 84	94.59 98	95.85 113	92.34 118
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS		90.81 138	91.60 140	89.88 143	92.52 161	88.18 184	93.31 155	83.62 200	91.59 88	88.45 149	88.96 169	89.73 172	86.96 128	96.42 68	95.69 66	94.43 162	90.65 137

Gipuma		95.86 36	96.17 40	95.50 29	95.92 60	94.59 104	94.77 123	92.50 50	97.82 6	97.90 2	95.56 88	97.88 66	94.71 14	98.02 25	94.81 86	97.23 60	94.48 75
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015

High-resolution multi-view benchmark