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	75.99 1	82.04 18	87.16 4	76.07 22	63.57 121	70.27 70	86.48 39	62.99 7	89.00 5	80.32 7	86.25 25	91.04 57	74.66 4	92.58 3	90.29 4	88.42 35	90.72 3
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	75.87 2	84.34 2	89.80 2	77.97 13	75.52 45	82.76 4	90.39 21	54.21 50	89.37 3	83.18 2	89.90 8	95.58 11	72.34 10	92.31 4	90.04 5	92.17 5	88.61 18
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
DeepC-MVS	73.80 3	82.34 13	86.87 7	77.06 19	78.62 35	84.34 1	90.30 23	63.54 2	83.10 27	71.30 42	86.91 23	90.54 71	67.12 32	87.81 35	87.05 24	91.46 15	88.37 21
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
3Dnovator+	72.94 4	78.78 34	83.05 43	73.80 34	70.70 68	81.34 11	88.33 33	56.01 41	81.33 42	72.87 36	78.06 102	81.15 138	63.83 45	87.39 36	85.82 26	91.06 18	86.28 35

DeepPCF-MVS	71.57 5	79.49 32	84.05 39	74.17 32	74.14 50	80.88 20	89.33 28	56.24 40	82.41 33	71.58 40	82.27 66	86.47 112	66.47 34	84.80 51	84.16 36	87.26 43	87.34 27

DeepC-MVS_fast	71.40 6	78.48 36	82.92 44	73.31 37	76.44 43	82.23 6	87.59 38	56.56 36	77.79 62	68.91 59	77.00 107	87.32 103	61.90 54	85.40 46	84.37 33	88.46 34	86.33 34
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ACMM	71.24 7	82.85 9	86.59 11	78.50 10	80.10 25	78.59 31	91.77 12	60.76 23	84.43 15	76.49 25	81.58 79	93.50 19	70.45 20	91.38 7	89.42 9	91.42 16	87.22 28
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PMVS	70.37 8	81.82 19	87.08 5	75.68 24	77.06 41	77.23 37	87.77 37	56.25 39	83.33 25	67.18 78	89.48 10	87.94 94	77.70 1	93.02 2	92.57 2	88.13 37	86.00 36
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
ACMP	70.35 9	82.17 15	86.45 13	77.18 18	79.33 27	81.00 17	89.27 29	58.63 30	81.35 41	75.46 30	82.97 56	95.08 12	68.90 25	90.49 14	87.43 22	91.48 14	86.84 30
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
ACMH+	67.97 10	80.15 29	86.16 16	73.14 38	73.82 53	76.41 40	83.59 48	54.82 48	87.35 6	70.86 46	86.98 22	96.27 5	66.50 33	89.17 25	83.39 40	89.26 29	83.56 47

ACMH	66.19 11	78.12 38	84.55 35	70.63 48	69.62 74	72.40 64	80.77 65	46.43 87	89.24 4	77.99 17	87.42 16	95.83 9	62.95 50	86.27 42	78.24 66	86.00 54	82.46 50
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
TAPA-MVS	66.11 12	75.37 56	79.24 63	70.86 45	67.63 80	74.09 52	83.17 51	44.75 101	81.82 37	80.83 5	65.61 160	88.04 93	61.58 56	83.21 63	80.12 56	87.17 44	81.82 54
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
3Dnovator	65.69 13	69.43 99	75.74 83	62.06 112	60.78 141	70.50 69	75.85 92	39.57 164	74.44 76	57.41 107	75.91 111	77.73 156	55.34 101	76.86 96	75.61 85	83.44 67	79.14 67

PCF-MVS	65.25 14	73.99 61	76.74 76	70.79 46	71.61 61	75.33 47	83.76 47	50.40 64	74.88 73	74.50 32	67.60 148	85.36 121	58.30 74	78.61 90	74.25 90	86.15 52	81.13 58
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
PLC	64.88 15	75.76 55	80.22 59	70.57 49	70.46 70	77.75 35	82.01 58	48.84 70	80.74 48	70.85 47	71.32 135	84.82 124	63.69 46	84.73 52	82.35 48	87.54 41	79.80 63
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
OpenMVS	60.79 16	64.42 130	69.72 138	58.23 129	61.63 135	62.17 122	64.11 158	37.54 181	67.17 133	55.71 114	65.89 159	74.89 164	52.67 116	72.20 137	68.29 130	77.73 124	77.39 78

IB-MVS	57.02 17	61.37 143	65.39 151	56.69 136	56.65 170	60.85 131	70.70 128	37.90 179	49.37 210	45.37 157	48.75 222	79.14 146	53.55 112	76.26 101	70.85 107	75.97 130	72.50 105
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	45.32 18	58.10 159	65.24 153	49.76 169	47.88 204	46.86 199	48.16 224	32.82 203	58.06 172	61.35 96	59.64 191	80.00 142	47.27 140	70.15 165	64.10 171	61.08 193	77.85 76
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MVE	28.01 19	35.86 229	43.56 231	26.88 230	22.33 238	19.75 239	30.85 239	23.88 220	49.90 207	10.48 237	43.64 229	61.87 201	48.99 131	47.26 230	42.15 222	24.76 235	40.37 222
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
Anonymous20240521		58.52 157	68.24 141	47.16 192	66.58 85	55.82 160	56.32 195	43.57 111	64.95 144	19.00 230	80.82 85	84.79 125	31.28 207	69.41 170	63.87 174	66.23 185	58.05 174

our_test_3					52.72 189	53.66 170	69.11 137

SMA-MVS		82.46 11	86.30 14	77.99 12	80.13 23	80.41 24	91.20 15	60.85 22	85.43 9	79.65 12	84.19 40	87.27 104	66.00 36	88.65 29	87.80 19	90.12 22	90.34 4

tfpn111		55.56 179	60.91 179	49.32 174	58.57 161	56.49 149	58.01 183	40.73 151	53.23 189	30.91 202	49.82 219	66.40 191	34.18 193	73.03 119	68.06 131	73.54 143	59.36 168

conf0.01		53.73 184	57.58 188	49.24 177	58.35 166	56.17 154	58.01 183	40.65 155	53.23 189	30.80 205	51.96 215	43.35 230	34.18 193	72.49 129	68.06 131	73.43 146	57.80 177

conf0.002		52.78 188	55.83 192	49.22 178	58.28 168	56.09 156	58.01 183	40.64 156	53.23 189	30.79 206	50.10 218	36.15 235	34.18 193	72.40 133	65.72 163	73.41 147	57.11 179

thresconf0.02		49.98 197	53.83 200	45.48 197	56.47 171	49.38 192	52.01 212	36.49 187	63.51 151	28.04 211	49.82 219	36.72 234	32.63 203	64.84 181	60.66 183	67.22 183	51.91 197

tfpn_n400		57.07 165	64.44 159	48.48 183	59.55 151	52.25 177	57.99 188	38.85 166	71.25 95	29.07 208	65.20 162	63.07 196	34.41 189	73.99 107	67.52 141	70.99 167	57.83 175

tfpnconf		57.07 165	64.44 159	48.48 183	59.55 151	52.25 177	57.99 188	38.85 166	71.25 95	29.07 208	65.20 162	63.07 196	34.41 189	73.99 107	67.52 141	70.99 167	57.83 175

tfpnview11		56.69 169	63.86 162	48.33 186	59.46 154	52.35 176	57.85 190	38.80 170	68.21 123	29.07 208	65.20 162	63.07 196	34.36 191	73.21 116	68.72 118	70.44 171	56.28 184

tfpn1000		56.13 176	63.18 169	47.91 188	58.34 167	53.03 174	58.87 178	38.14 174	65.64 141	27.09 213	65.41 161	59.49 208	33.41 200	73.14 117	69.08 116	71.63 160	56.46 183

tfpn_ndepth		51.52 191	57.21 189	44.88 198	54.05 188	52.14 181	53.58 207	37.07 183	55.55 185	24.73 218	47.12 224	56.92 210	28.92 209	69.22 171	64.80 166	70.94 169	54.74 190

conf200view11		56.07 177	61.85 174	49.32 174	58.57 161	56.49 149	58.01 183	40.73 151	53.23 189	30.91 202	56.41 202	66.40 191	34.18 193	73.03 119	68.06 131	73.54 143	59.36 168

thres100view900		53.88 182	59.19 184	47.68 190	58.57 161	52.74 175	54.45 202	38.07 176	53.23 189	31.01 200	56.41 202	66.40 191	32.80 202	65.03 180	64.43 169	71.18 166	56.10 185

tfpnnormal		61.41 142	71.33 131	49.83 168	61.73 134	54.90 166	58.52 180	41.24 142	75.20 72	32.00 196	82.13 67	87.87 95	35.63 183	72.75 126	66.30 162	69.87 176	60.14 163

tfpn200view9		56.07 177	61.85 174	49.34 172	58.57 161	56.48 151	58.01 183	40.72 153	53.23 189	31.01 200	56.41 202	66.40 191	34.18 193	73.02 121	68.06 131	73.53 145	59.35 170

view600		58.47 158	65.42 150	50.36 166	61.04 139	55.84 159	59.33 176	40.34 160	64.46 147	32.31 194	64.78 166	69.85 177	36.46 177	72.46 132	71.31 103	72.68 155	59.26 171

view800		59.22 154	66.23 146	51.03 162	61.99 133	56.71 148	60.53 169	41.20 143	66.26 137	32.46 190	66.68 155	69.93 176	36.77 174	74.52 105	70.00 113	73.24 150	59.56 167

conf0.05thres1000		61.96 138	70.38 136	52.13 150	63.31 127	58.12 136	62.09 164	42.45 121	75.50 71	33.07 186	77.89 103	69.72 180	37.32 171	77.88 94	70.72 108	74.55 137	62.82 156

tfpn		57.74 163	63.03 170	51.58 157	62.87 129	57.28 144	61.53 167	41.99 131	67.67 125	32.52 189	68.13 145	43.08 231	36.94 173	76.07 103	69.31 115	73.62 142	59.68 166

ESAPD		80.30 28	84.42 37	75.49 26	79.20 31	79.76 27	89.40 27	58.51 31	81.15 43	69.56 54	85.14 33	88.71 90	68.92 24	85.26 49	82.30 50	87.35 42	88.64 16

CHOSEN 280x420		40.24 222	44.14 230	35.69 218	32.36 233	23.58 237	50.30 218	21.21 226	40.94 228	18.84 231	32.75 235	48.65 216	48.13 135	59.16 197	55.31 195	43.28 224	48.62 207

CANet		71.07 76	75.09 88	66.39 73	72.57 57	71.53 67	82.38 56	47.10 81	59.81 166	59.81 100	74.97 118	84.37 128	54.25 108	79.89 86	77.64 72	82.25 79	77.40 77

Fast-Effi-MVS+-dtu		63.22 134	65.55 149	60.49 117	61.24 137	64.70 93	74.15 113	53.24 55	51.46 198	49.67 137	58.03 199	78.42 152	48.05 136	72.03 138	71.14 105	76.60 129	63.09 155

Effi-MVS+-dtu		70.10 91	73.76 106	65.82 75	70.23 72	74.92 48	79.47 71	44.49 102	56.98 181	54.34 115	64.26 170	84.78 126	59.97 64	80.96 78	80.38 55	86.44 49	74.05 91

CANet_DTU		61.22 144	67.07 145	54.40 143	59.89 147	63.62 110	70.98 126	36.77 185	50.49 204	47.15 145	62.45 178	80.81 139	37.90 170	71.87 142	70.09 112	73.69 141	70.19 119

MVS_0304		73.74 65	77.16 74	69.74 54	74.24 49	73.47 55	84.70 44	49.62 65	62.26 158	67.27 75	75.87 113	87.57 99	57.49 83	81.20 73	79.50 60	85.10 57	80.27 60

HSP-MVS		79.66 31	84.23 38	74.34 31	78.92 33	81.86 9	90.55 17	60.49 24	80.19 51	69.08 57	85.12 34	90.92 61	62.99 49	81.15 74	78.00 67	83.99 61	92.37 1

TSAR-MVS + MP.		81.23 23	86.13 17	75.52 25	80.74 14	83.22 3	90.55 17	55.12 45	80.87 45	67.62 66	88.01 13	92.38 33	70.61 18	86.64 40	83.10 43	88.51 33	88.67 15

OPM-MVS		81.44 22	85.68 24	76.49 21	79.27 28	78.21 33	89.84 24	58.67 29	85.25 10	76.26 26	85.28 32	92.88 29	66.03 35	87.20 38	85.40 28	88.86 32	85.58 40

ACMMP_Plus		81.79 20	85.72 23	77.21 17	79.15 32	79.68 28	91.62 14	59.66 26	83.55 22	77.74 19	83.72 47	87.34 102	65.36 37	88.61 30	87.56 21	89.73 27	89.58 6

ambc			79.96 60		74.57 48	75.48 45	73.75 119		80.32 50	72.34 37	78.46 100	92.41 32	59.05 72	80.24 85	73.95 92	75.41 133	78.85 69

zzz-MVS		82.61 10	85.04 29	79.79 6	82.59 4	73.90 54	92.42 9	62.39 11	84.54 14	80.21 9	79.86 92	90.74 64	70.63 17	90.01 21	89.71 8	90.48 21	86.49 33

Effi-MVS+		69.04 100	73.01 117	64.40 92	67.20 82	64.83 92	74.87 103	43.97 105	63.33 152	60.90 98	73.06 129	85.79 118	55.61 99	73.58 113	76.41 79	83.84 63	74.09 90

new-patchmatchnet		47.33 203	60.49 182	31.99 225	55.69 178	33.86 226	36.84 236	33.31 200	72.36 87	14.33 236	80.09 91	92.14 35	13.27 232	63.54 185	40.09 226	38.51 228	41.32 220

pmmvs6		64.78 129	75.82 82	51.89 152	62.41 130	57.13 145	60.24 171	45.59 92	82.90 29	34.69 180	84.83 36	93.18 23	36.22 179	76.43 99	71.13 106	72.21 159	65.12 148

pmmvs5		50.64 194	58.01 185	42.05 204	47.01 209	43.67 204	49.27 220	29.43 214	50.77 203	33.83 183	68.69 141	76.16 160	27.82 211	57.53 208	57.07 190	64.95 188	52.18 195

Fast-Effi-MVS+		67.71 117	72.54 123	62.07 111	63.83 114	63.68 108	75.74 94	39.94 161	60.89 163	54.29 116	73.00 130	86.19 117	56.85 87	78.46 92	73.23 95	81.74 83	72.36 106

Anonymous20231211		70.28 88	81.58 50	57.09 132	71.63 60	60.40 132	70.12 131	52.15 60	92.79 1	29.96 207	88.89 11	98.03 1	40.61 165	80.86 79	75.96 82	78.08 117	74.11 89

pmmvs-eth3d		65.36 126	70.09 137	59.85 120	63.05 128	53.61 171	74.29 107	46.45 86	68.14 124	51.45 126	78.83 99	85.78 119	49.87 128	70.44 163	70.45 110	74.00 140	63.38 154

GG-mvs-BLEND		31.54 232	46.27 221	14.37 234	0.07 242	48.65 193	42.97 230	0.08 239	44.04 225	1.21 243	39.77 231	57.94 209	0.15 239	48.19 228	42.82 220	41.70 225	42.46 217

Anonymous20231206		50.28 196	57.94 186	41.35 206	55.45 180	43.65 205	58.06 182	34.12 195	62.02 160	24.25 221	59.33 192	79.80 144	24.49 217	59.55 194	54.28 199	51.74 210	46.94 211

MTAPA										80.26 8		90.53 72

MTMP										82.07 4		91.00 58

gm-plane-assit		56.76 167	57.64 187	55.73 139	66.01 90	55.45 163	74.96 99	30.54 211	73.71 82	56.04 113	81.81 77	30.91 238	43.83 153	58.77 201	54.71 196	63.02 191	48.13 208

train_agg		77.83 39	80.47 58	74.77 28	80.92 13	69.60 71	88.87 32	56.32 38	74.03 81	71.03 44	83.67 48	87.68 97	64.75 41	83.70 57	81.85 53	86.71 46	82.73 49

gg-mvs-nofinetune		56.45 173	61.04 177	51.10 161	63.42 125	49.40 191	53.71 206	52.52 58	74.77 74	46.93 147	77.31 106	53.88 212	26.42 216	62.51 190	57.81 189	63.60 190	51.57 198

MS-PatchMatch		56.31 175	60.22 183	51.73 155	60.53 145	55.53 162	63.41 160	37.18 182	51.34 200	37.44 171	60.53 187	62.19 200	45.52 148	64.25 184	63.17 177	66.33 184	64.56 150

Patchmatch-RL test							2.05 242

tmp_tt				7.47 235	8.89 239	3.32 241	4.35 241	1.14 236	15.58 238	15.76 235	8.50 237	5.90 242	2.00 236	20.02 235	21.51 234	12.70 237

canonicalmvs		66.37 119	74.37 103	57.04 133	65.89 92	65.06 88	62.58 163	42.55 120	76.82 66	46.87 149	67.33 149	86.38 114	45.49 149	76.77 97	71.85 101	78.87 102	76.35 81

anonymousdsp		74.76 58	82.59 45	65.63 77	45.61 214	61.13 127	89.06 30	32.58 204	74.11 80	59.55 101	84.06 44	94.12 18	75.24 3	88.94 27	86.95 25	91.74 7	88.81 13

v144192		70.68 83	74.40 102	66.34 74	65.94 91	64.38 99	77.63 80	45.18 95	69.97 115	70.11 50	82.70 60	90.77 62	59.84 66	71.43 153	68.46 123	79.31 96	73.08 100

v1921920		70.82 80	74.46 100	66.58 71	66.33 88	64.35 102	77.72 79	45.07 96	70.39 105	71.18 43	83.15 54	90.62 68	59.97 64	70.90 158	68.43 127	79.19 97	73.39 97

FC-MVSNet-train		64.87 128	74.76 95	53.33 145	65.24 98	58.05 138	69.69 134	41.92 134	70.99 99	32.62 188	85.75 29	88.23 91	32.10 205	77.61 95	74.41 89	78.43 108	68.25 137

UA-Net		78.65 35	83.96 41	72.46 40	84.87 1	76.15 41	89.06 30	55.70 42	77.25 65	53.14 122	79.73 94	82.09 136	59.69 67	92.21 5	90.93 3	92.32 3	89.36 7

v1192		71.06 77	74.87 91	66.61 70	66.38 87	65.80 81	78.27 75	45.28 94	70.19 112	70.79 48	83.37 51	91.79 40	58.76 73	70.86 160	69.02 117	80.16 90	73.08 100

FC-MVSNet-test		60.28 150	70.83 134	47.96 187	54.69 184	47.12 196	68.06 141	41.68 138	71.42 92	23.73 222	84.70 38	77.41 158	28.92 209	82.33 68	73.08 96	70.68 170	59.77 165

v1144		70.45 86	74.50 99	65.73 76	65.74 93	64.88 90	77.33 82	44.16 103	70.59 104	69.63 53	83.15 54	91.42 49	57.79 77	71.29 157	68.53 122	79.72 93	71.63 115

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	0.00 244	0.00 240	0.00 239	0.00 238	0.00 242	0.00 239

HFP-MVS		82.37 12	86.28 15	77.81 16	79.94 26	80.96 18	91.13 16	63.30 4	84.04 19	71.81 38	82.39 65	89.59 83	69.16 23	89.08 26	88.83 14	91.49 13	89.10 10

v148		64.92 127	70.58 135	58.32 127	59.89 147	57.09 146	66.04 147	35.27 190	69.11 119	60.66 99	79.57 96	90.93 60	53.91 109	69.81 168	62.22 180	74.14 138	65.31 147

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	0.00 244	0.00 240	0.00 239	0.00 238	0.00 242	0.00 239

v748		71.27 74	79.41 61	61.76 113	60.62 144	61.73 124	68.46 139	40.71 154	80.76 47	61.02 97	87.12 18	95.00 13	59.62 68	80.67 81	70.67 109	80.14 91	79.93 62

v7n		74.47 60	81.06 54	66.77 68	66.98 84	67.10 74	76.76 84	45.88 91	81.98 36	67.43 71	88.38 12	95.67 10	61.38 57	80.76 80	73.49 94	82.21 80	80.06 61

v1141		68.97 104	73.38 110	63.83 97	64.11 111	62.97 117	74.96 99	41.52 139	70.29 106	67.36 73	82.47 63	91.37 51	56.59 88	71.43 153	66.49 160	78.41 109	68.61 134

v1neww		68.32 111	72.82 118	63.07 104	63.73 116	63.12 113	74.23 108	40.99 145	67.21 130	64.83 88	82.09 69	90.20 74	56.49 94	71.86 143	66.61 152	78.14 113	68.65 130

DI_MVS_plusplus_trai		63.43 133	67.54 143	58.63 124	62.34 131	58.06 137	65.75 151	42.15 127	63.05 153	53.28 121	75.88 112	75.92 161	50.18 125	68.04 174	64.20 170	78.07 119	67.65 139

v7new		68.32 111	72.82 118	63.07 104	63.73 116	63.12 113	74.23 108	40.99 145	67.21 130	64.83 88	82.09 69	90.20 74	56.49 94	71.86 143	66.61 152	78.14 113	68.65 130

HPM-MVS++		80.44 27	82.57 46	77.96 15	81.99 7	72.76 58	90.48 20	61.31 14	80.85 46	77.90 18	81.93 74	87.01 107	68.20 28	84.15 53	85.27 30	87.85 39	86.00 36

XVS					80.47 19	81.29 12	93.33 3			77.45 20		90.19 76				91.52 11

v1240		70.94 79	74.52 98	66.76 69	66.54 86	64.40 97	77.76 78	45.29 93	70.05 114	71.45 41	83.36 53	90.96 59	60.37 61	70.50 162	68.68 119	79.14 98	73.68 95

v18		67.99 116	72.63 122	62.57 110	63.32 126	63.64 109	73.58 121	42.07 128	64.75 146	62.64 95	81.36 80	89.01 88	56.02 97	71.57 149	66.41 161	77.80 123	71.69 114

pm-mvs1		61.97 137	72.01 127	50.25 167	60.64 143	55.23 164	58.67 179	42.44 122	74.40 77	33.63 184	81.03 82	89.86 80	34.87 184	72.93 125	67.95 137	71.28 163	62.65 157

X-MVStestdata					80.47 19	81.29 12	93.33 3			77.45 20		90.19 76				91.52 11

v17		68.55 108	73.23 114	63.08 103	63.67 119	63.84 106	74.05 114	42.28 125	66.34 136	63.93 91	81.91 75	89.83 81	56.50 92	71.97 140	66.55 156	78.08 117	72.18 108

v16		68.33 110	73.03 116	62.86 108	63.57 121	63.83 107	73.98 115	42.30 124	65.58 142	62.94 93	81.82 76	89.37 85	56.36 96	71.91 141	66.52 157	77.99 120	72.17 109

divwei89l23v2f112		68.97 104	73.38 110	63.83 97	64.11 111	62.97 117	74.96 99	41.52 139	70.29 106	67.39 72	82.47 63	91.37 51	56.59 88	71.42 156	66.50 159	78.40 111	68.62 132

v15		69.80 97	74.53 97	64.27 93	64.30 108	64.15 105	75.40 97	43.12 119	70.71 103	66.98 80	83.41 50	91.43 48	57.21 86	72.48 131	66.84 151	78.62 106	72.72 104

v13		70.58 84	75.49 84	64.87 85	64.66 103	64.58 94	76.18 87	43.69 109	72.34 88	67.65 65	84.36 39	92.01 38	58.05 75	73.57 114	67.06 145	78.96 101	74.48 88

v12		70.39 87	75.25 85	64.73 86	64.60 105	64.47 95	76.00 88	43.55 112	71.92 90	67.51 68	84.15 43	91.88 39	57.83 76	73.32 115	67.00 146	78.87 102	74.02 92

X-MVS		81.61 21	84.73 33	77.97 13	80.31 22	81.29 12	93.53 2	62.50 10	81.41 40	77.45 20	72.04 133	90.19 76	62.50 52	90.57 13	88.87 13	91.54 10	88.73 14

v8		68.77 106	73.50 108	63.26 100	63.74 115	64.47 95	74.22 112	42.07 128	67.30 129	64.89 85	82.08 71	90.23 73	56.50 92	71.85 146	66.57 155	78.14 113	72.02 110

v7		69.81 96	73.94 104	65.00 84	65.33 95	65.07 87	76.60 85	43.66 110	67.36 128	67.25 76	82.76 58	90.57 69	57.70 79	71.69 147	68.63 120	79.44 94	71.52 116

v6		68.32 111	72.82 118	63.07 104	63.73 116	63.11 115	74.23 108	40.99 145	67.21 130	64.86 87	82.11 68	90.19 76	56.51 91	71.86 143	66.61 152	78.14 113	68.66 129

v11		70.10 91	74.82 92	64.58 88	64.83 101	64.39 98	75.89 90	43.18 118	71.34 94	67.75 64	84.19 40	91.75 41	57.23 85	71.46 152	66.85 150	78.60 107	73.78 93

v52		73.95 62	81.43 53	65.22 81	54.85 182	63.32 111	78.90 72	38.00 177	80.00 54	68.32 62	87.02 20	94.98 15	68.14 30	84.11 54	75.63 83	83.12 69	84.96 44

V14		69.99 94	74.77 94	64.41 91	64.39 107	64.25 104	75.59 95	43.25 116	71.12 98	67.14 79	83.65 49	91.58 44	57.40 84	72.75 126	66.90 149	78.70 105	73.15 99

v10		70.25 89	74.59 96	65.19 83	65.32 97	66.46 79	76.60 85	44.84 99	67.38 127	67.21 77	82.75 59	90.56 70	57.70 79	71.69 147	68.63 120	79.44 94	74.67 87

V4		73.95 62	81.44 52	65.22 81	54.86 181	63.31 112	78.89 73	38.00 177	80.03 53	68.29 63	87.02 20	95.00 13	68.15 29	84.11 54	75.62 84	83.12 69	84.95 45

v2v482		69.01 101	73.39 109	63.89 95	63.86 113	62.99 116	75.26 98	42.05 130	70.22 110	68.46 61	82.64 61	91.61 43	55.38 100	70.89 159	66.93 148	78.30 112	68.48 136

v1		68.98 102	73.38 110	63.84 96	64.12 110	62.97 117	74.95 102	41.52 139	70.28 108	67.47 70	82.49 62	91.37 51	56.59 88	71.43 153	66.51 158	78.41 109	68.62 132

V42		65.79 121	72.11 126	58.42 126	51.89 193	58.69 135	73.80 118	34.50 191	65.40 143	57.10 108	79.54 97	89.09 87	57.51 82	71.98 139	67.83 138	75.70 131	72.26 107

V9		70.20 90	75.02 89	64.58 88	64.49 106	64.36 100	75.80 93	43.40 113	71.53 91	67.35 74	83.95 46	91.73 42	57.63 81	73.04 118	66.96 147	78.79 104	73.61 96

SD-MVS		82.13 17	86.80 8	76.67 20	80.36 21	80.66 22	89.48 26	56.93 33	82.50 32	67.55 67	87.05 19	91.40 50	72.84 7	88.66 28	88.32 16	92.85 2	89.04 11

GA-MVS		60.73 148	64.24 161	56.64 137	59.38 157	57.45 143	65.07 152	36.65 186	57.39 178	58.17 105	73.43 127	69.10 184	47.38 138	64.47 183	63.63 175	73.19 152	64.22 151

MSLP-MVS++		76.66 52	82.32 47	70.06 50	70.51 69	80.27 25	79.77 69	55.58 43	77.79 62	63.09 92	67.25 151	89.50 84	71.01 15	88.10 33	85.74 27	80.39 88	87.56 25

APDe-MVS		81.08 25	86.12 18	75.20 27	79.25 29	80.91 19	90.38 22	57.05 32	85.83 8	66.07 83	87.34 17	91.27 54	69.45 21	85.99 44	82.55 44	88.98 31	88.95 12

TSAR-MVS + COLMAP		75.85 53	81.06 54	69.77 53	71.15 62	76.90 38	82.93 52	52.43 59	79.25 59	70.13 49	82.78 57	87.00 108	60.02 63	80.30 83	79.61 59	81.95 82	81.61 55

CVMVSNet		60.45 149	63.72 164	56.63 138	54.82 183	53.75 169	68.41 140	41.95 133	55.07 186	48.03 141	58.08 198	68.67 185	55.09 102	69.14 172	68.34 128	71.51 161	72.97 103

TSAR-MVS + ACMM		81.20 24	86.92 6	74.52 29	77.60 37	82.29 5	84.41 46	62.95 8	82.99 28	64.03 90	87.71 14	89.17 86	71.98 11	88.19 32	88.10 17	86.18 51	89.95 5

pmmvs4		61.12 145	64.61 157	57.04 133	60.88 140	52.15 180	70.59 129	44.82 100	61.35 162	46.91 148	72.08 132	73.27 169	46.79 145	65.06 179	67.76 139	72.28 157	60.58 162

EU-MVSNet		59.77 151	66.07 147	52.42 149	47.81 205	51.86 182	62.98 162	32.28 206	62.08 159	47.10 146	59.94 190	83.42 134	53.08 115	70.06 167	63.19 176	71.26 165	71.96 111

test-LLR		46.01 207	45.06 226	47.11 193	59.39 155	36.72 220	51.28 214	40.95 148	36.41 234	34.45 181	46.14 226	47.02 220	38.00 168	51.78 221	48.53 212	58.60 196	48.84 204

TESTMET0.1,1		41.79 218	45.06 226	37.97 213	31.32 234	36.72 220	51.28 214	14.17 233	36.41 234	34.45 181	46.14 226	47.02 220	38.00 168	51.78 221	48.53 212	58.60 196	48.84 204

test-mter		44.18 214	47.60 219	40.18 210	33.20 231	39.03 213	55.28 199	13.91 234	39.07 232	36.63 174	48.09 223	49.52 215	41.12 164	54.55 215	50.91 208	60.97 194	52.03 196

ACMMPR		83.94 4	87.20 3	80.14 4	81.04 12	81.92 8	92.57 8	63.14 5	84.35 17	79.45 13	83.37 51	92.04 37	72.82 8	90.66 12	88.96 12	91.80 6	89.13 9

testgi		51.94 190	61.37 176	40.94 207	58.38 165	47.03 197	65.88 148	30.49 213	70.87 102	22.64 224	57.53 201	87.59 98	18.30 224	63.01 186	54.32 198	49.93 214	49.27 202

test20.03		53.49 185	60.95 178	44.78 200	64.73 102	47.25 195	61.58 166	43.30 115	65.86 139	22.85 223	66.87 154	79.85 143	22.99 218	62.38 191	56.95 191	53.25 207	47.46 209

thres600view7		58.87 156	65.91 148	50.66 164	61.27 136	56.32 152	59.88 173	40.63 157	64.88 145	32.10 195	64.82 165	69.83 178	36.72 176	72.99 123	72.55 98	73.34 148	59.97 164

1111		39.71 225	44.86 229	33.71 223	50.45 197	28.51 233	55.07 200	34.43 192	62.60 154	17.59 232	62.60 176	28.17 239	14.69 229	54.19 216	41.91 223	30.02 233	36.03 226

.test1245		31.52 233	33.91 234	28.73 228	50.45 197	28.51 233	55.07 200	34.43 192	62.60 154	17.59 232	62.60 176	28.17 239	14.69 229	54.19 216	0.54 236	0.15 240	0.77 237

ADS-MVSNet		40.61 221	46.31 220	33.96 222	40.70 222	30.42 232	40.42 233	33.44 198	58.01 173	30.87 204	63.05 174	54.48 211	22.67 219	44.35 232	39.23 230	35.64 231	34.64 227

MP-MVS		83.50 5	86.11 19	80.45 3	82.58 5	80.60 23	92.68 5	63.48 3	81.43 39	80.21 9	81.95 73	90.76 63	72.86 6	90.14 19	89.30 11	90.92 19	88.59 19
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		0.47 235	0.69 235	0.21 237	0.17 241	0.17 243	0.35 243	0.16 237	0.66 239	0.18 244	1.05 239	0.99 243	0.27 238	0.62 238	0.54 236	0.15 240	0.77 237

thres400		57.25 164	63.73 163	49.70 170	60.19 146	54.95 165	58.16 181	39.60 163	62.42 156	31.98 198	62.33 179	69.20 182	35.96 181	70.07 166	68.03 135	72.28 157	59.12 172

test123		0.53 234	0.60 236	0.46 236	0.22 240	0.25 242	0.33 244	0.13 238	0.66 239	1.37 242	1.10 238	0.00 244	0.43 237	0.68 237	0.61 235	0.26 239	0.88 236

thres200		56.35 174	62.36 172	49.34 172	58.87 160	56.32 152	55.91 196	40.63 157	58.51 168	31.34 199	58.81 197	67.31 186	35.96 181	72.99 123	65.51 165	73.34 148	57.07 180

test0.0.03 1		45.40 209	49.55 213	40.57 209	59.39 155	44.36 203	53.37 208	40.95 148	47.14 217	19.23 229	45.49 228	60.24 206	19.24 222	54.82 214	51.98 203	51.21 212	42.82 216

test12356		39.53 226	49.18 216	28.26 229	32.93 232	33.64 227	48.68 223	15.96 231	46.26 222	16.21 234	46.46 225	79.07 147	17.13 225	58.60 202	48.30 215	38.67 227	31.96 229

testus		41.61 219	50.54 208	31.20 227	38.11 228	38.92 214	49.10 221	17.60 229	48.25 216	25.05 216	41.45 230	79.34 145	13.18 233	58.28 204	47.10 217	44.17 221	40.41 221

pmmvs3		46.64 205	54.13 199	37.90 214	31.23 235	40.68 210	49.83 219	15.34 232	46.31 221	36.34 175	53.15 214	74.40 167	36.36 178	58.43 203	56.64 192	58.32 198	49.29 201

testmv		44.91 212	54.17 198	34.11 220	41.52 220	37.93 217	54.27 203	23.09 222	53.61 188	22.14 227	53.89 211	84.00 132	16.41 227	60.64 193	50.29 210	47.20 216	38.83 224

EMVS		43.85 215	49.91 211	36.77 217	45.46 215	32.70 228	44.09 229	25.33 219	57.88 174	26.62 214	58.99 196	61.14 204	42.77 158	70.26 164	38.52 231	36.38 230	29.87 232

E-PMN		43.83 216	49.81 212	36.84 216	46.09 213	31.86 230	42.77 231	25.85 217	57.76 176	25.53 215	55.50 206	62.47 199	43.77 154	70.78 161	39.51 228	37.04 229	30.79 231

test2356		35.97 228	39.61 232	31.71 226	38.85 224	34.29 225	45.78 226	22.27 224	38.89 233	22.59 225	37.67 233	37.07 233	16.57 226	50.72 224	45.45 218	44.20 220	33.19 228

test1235678		44.92 211	54.19 197	34.11 220	41.53 219	37.95 216	54.27 203	23.09 222	53.64 187	22.14 227	53.92 210	84.05 131	16.41 227	60.66 192	50.30 209	47.20 216	38.84 223

PGM-MVS		83.03 7	85.67 25	79.95 5	80.69 16	81.09 15	92.40 10	63.06 6	79.38 58	80.21 9	80.31 88	91.44 47	71.75 12	90.46 15	88.53 15	91.57 9	88.50 20

MCST-MVS		73.84 64	77.44 72	69.63 55	73.75 54	74.73 49	81.38 62	48.58 71	74.77 74	69.16 56	71.97 134	86.20 116	59.50 69	78.51 91	74.06 91	85.42 56	81.85 53

MVS_Test		62.58 135	67.46 144	56.89 135	59.52 153	55.90 158	64.94 154	38.83 169	57.08 180	56.55 112	76.53 108	84.49 127	47.45 137	66.95 176	62.01 181	74.04 139	69.27 127

MDA-MVSNet-bldmvs		62.46 136	72.13 125	51.19 160	34.32 230	56.10 155	68.65 138	38.85 166	69.05 121	49.50 138	78.17 101	85.43 120	51.32 118	86.67 39	67.40 143	64.46 189	62.08 158

CDPH-MVS		77.22 47	81.05 56	72.75 39	77.29 39	77.46 36	86.36 40	54.02 52	73.00 86	69.75 52	77.78 105	88.90 89	61.31 59	84.09 56	82.54 45	87.79 40	83.57 46

diffmvs		59.30 152	64.79 156	52.90 148	54.48 186	50.17 188	64.98 153	36.44 188	60.16 165	50.33 133	76.51 109	74.56 165	44.99 150	62.52 189	62.37 179	66.18 186	67.22 140

PMMVS2		34.11 231	48.55 217	17.26 233	25.45 237	20.72 238	35.08 237	16.26 230	58.71 167	4.16 241	59.22 195	78.40 153	3.65 235	57.24 210	38.31 232	18.94 236	27.28 234

PM-MVS		65.66 123	71.25 132	59.14 122	58.92 159	54.88 167	73.66 120	38.55 173	66.12 138	49.91 136	69.87 137	86.97 109	60.61 60	76.30 100	74.75 88	73.19 152	69.83 121

PS-CasMVS		77.46 44	85.80 22	67.73 62	81.24 9	72.88 57	80.63 66	61.28 15	84.14 18	50.53 131	92.13 3	96.76 2	50.12 126	91.02 9	84.46 32	82.60 77	79.19 66

UniMVSNet_NR-MVSNet		70.82 80	77.44 72	63.11 102	71.75 59	66.02 80	73.93 116	55.00 47	70.90 100	46.77 150	86.68 24	91.54 45	46.91 143	81.07 76	76.32 80	84.28 59	69.54 123

PEN-MVS		77.06 48	85.05 28	67.74 61	82.29 6	72.59 61	80.86 64	61.03 19	84.66 12	50.08 135	92.19 2	96.59 4	49.12 130	89.83 22	82.35 48	83.06 71	77.14 79

TransMVSNet (Re)		63.49 132	73.86 105	51.39 158	64.26 109	56.07 157	61.17 168	42.23 126	78.81 60	34.80 178	85.94 26	90.63 67	34.35 192	72.73 128	67.98 136	71.50 162	64.84 149

DTE-MVSNet		77.28 45	84.87 32	68.42 58	82.94 3	72.70 60	81.60 60	61.78 12	85.03 11	51.40 128	92.11 4	96.00 6	49.42 129	89.73 23	82.52 46	83.39 68	75.98 83

DU-MVS		71.03 78	77.92 69	62.98 107	70.81 64	65.48 84	73.93 116	56.76 34	69.95 116	46.77 150	85.70 30	93.49 20	46.91 143	83.47 59	77.82 70	82.72 75	69.54 123

UniMVSNet (Re)		71.29 73	78.14 67	63.30 99	70.29 71	66.57 77	75.98 89	54.74 49	70.20 111	46.20 153	85.08 35	93.21 22	48.19 134	82.50 67	78.33 65	84.40 58	71.08 117

CP-MVSNet		77.01 49	85.04 29	67.65 63	81.16 11	72.72 59	80.54 67	61.18 16	82.09 35	50.41 132	90.81 6	95.89 7	50.03 127	90.86 10	84.30 35	82.56 78	78.65 72

WR-MVS_H		77.56 42	85.88 21	67.86 60	80.54 17	74.32 51	83.23 50	61.78 12	83.47 23	47.46 144	91.81 5	95.84 8	50.50 123	90.44 16	84.37 33	83.63 64	80.89 59

WR-MVS		78.32 37	86.09 20	69.25 57	76.22 44	72.33 65	85.71 42	59.02 27	86.66 7	51.41 127	92.91 1	96.76 2	53.09 114	90.21 18	85.30 29	90.05 24	78.46 73

NR-MVSNet		68.66 107	76.15 79	59.93 119	65.49 94	65.48 84	74.42 105	56.76 34	69.95 116	45.38 156	85.70 30	91.13 55	34.68 185	74.52 105	76.75 77	82.83 74	69.49 125

Baseline_NR-MVSNet		68.15 115	75.12 87	60.02 118	70.81 64	55.67 161	75.88 91	53.40 53	71.25 95	43.96 160	85.88 28	92.68 30	45.76 147	83.47 59	68.34 128	70.34 175	68.58 135

TranMVSNet+NR-MVSNet		71.66 70	79.23 64	62.83 109	72.54 58	65.64 82	74.77 104	55.27 44	75.91 70	45.50 155	89.55 9	94.25 16	45.96 146	82.74 65	77.03 75	82.96 72	69.48 126

TSAR-MVS + GP.		73.42 66	76.31 77	70.05 51	77.15 40	71.13 68	81.59 61	54.11 51	69.84 118	58.65 104	66.20 157	78.77 151	65.29 39	83.65 58	83.14 42	83.54 66	81.47 56

abl_6				65.41 78	69.37 75	74.02 53	82.50 55	47.39 79	66.39 135	56.63 111	60.61 186	82.76 135	53.68 111			82.92 73	78.39 74

mPP-MVS					82.97 2							92.12 36

DWT-MVSNet_training		48.57 202	47.93 218	49.31 176	51.79 194	48.05 194	61.84 165	34.33 194	41.94 227	43.42 162	50.35 216	34.74 237	47.30 139	52.62 220	52.08 202	57.20 201	55.74 186

testpf		41.44 220	38.52 233	44.85 199	46.17 212	38.68 215	60.29 170	43.31 114	24.28 236	35.09 177	39.52 232	34.84 236	32.39 204	43.79 233	39.89 227	51.88 209	48.65 206

SixPastTwentyTwo		77.24 46	83.65 42	69.78 52	65.14 100	64.85 91	77.44 81	47.74 77	82.76 30	68.52 60	87.65 15	93.31 21	71.68 13	89.49 24	82.41 47	88.14 36	85.05 43

LGP-MVS_train		82.91 8	86.50 12	78.72 9	78.72 34	81.03 16	89.78 25	61.16 17	80.15 52	80.44 6	84.83 36	94.19 17	70.52 19	90.70 11	87.19 23	91.71 8	87.37 26

EPNet_dtu		56.63 170	60.77 180	51.80 153	55.47 179	44.63 201	69.83 133	38.74 171	50.27 205	47.64 142	58.01 200	72.27 170	33.71 198	68.60 173	67.72 140	65.39 187	63.86 152
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x2688		52.99 187	56.91 190	48.42 185	47.32 206	50.10 189	64.18 157	33.85 196	45.46 223	36.95 173	55.20 208	66.49 190	51.20 119	59.28 196	59.81 185	57.01 202	61.99 159

EPNet		66.87 118	68.89 139	64.53 90	73.97 52	61.13 127	78.46 74	61.03 19	56.78 182	53.41 120	66.91 152	70.91 173	43.49 155	76.08 102	76.68 78	76.81 125	73.73 94
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
APD-MVS		80.60 26	84.63 34	75.91 23	81.22 10	81.48 10	90.49 19	58.81 28	77.54 64	67.49 69	85.90 27	89.82 82	69.43 22	86.08 43	83.80 38	88.01 38	87.77 23
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
LP		49.44 200	55.77 193	42.05 204	38.31 227	42.61 207	51.74 213	36.31 189	58.35 169	40.36 169	68.52 143	60.77 205	37.08 172	58.27 205	51.76 205	48.51 215	50.13 199

CNVR-MVS		77.79 41	81.57 51	73.38 36	78.37 36	75.91 42	87.97 35	55.11 46	79.41 57	70.98 45	74.70 121	86.43 113	61.77 55	85.10 50	83.73 39	86.10 53	85.68 39

NCCC		77.82 40	80.72 57	74.43 30	79.24 30	75.72 44	88.06 34	56.36 37	79.61 56	73.22 34	67.75 147	87.05 106	63.09 48	85.62 45	84.00 37	86.62 47	85.30 42

CP-MVS		84.06 3	86.79 9	80.86 2	81.81 8	79.66 29	92.67 6	64.48 1	83.13 26	82.32 3	80.89 84	92.97 28	72.51 9	91.74 6	90.02 6	91.40 17	89.14 8

NP-MVS									71.39 93

EG-PatchMatch MVS		71.50 72	76.82 75	65.30 79	70.74 67	66.50 78	74.23 108	43.25 116	72.02 89	59.11 102	79.85 93	86.88 110	63.95 44	80.29 84	75.25 87	80.51 87	76.98 80

tpm cat1		50.98 192	51.28 206	50.62 165	55.74 177	49.92 190	63.13 161	38.12 175	52.38 197	47.61 143	60.11 189	44.51 227	44.86 152	51.31 223	47.49 216	54.25 206	53.24 193

SteuartSystems-ACMMP		82.16 16	85.55 26	78.21 11	80.48 18	79.28 30	92.65 7	61.03 19	80.55 49	77.00 23	81.80 78	90.71 65	68.73 26	90.25 17	87.94 18	89.36 28	88.30 22
Skip Steuart: Steuart Systems R&D Blog.
tpmp4_e23		55.21 180	55.01 196	55.44 141	61.24 137	53.77 168	69.57 135	43.81 106	55.88 184	51.16 129	60.15 188	45.66 225	44.99 150	59.13 200	53.13 201	61.88 192	57.35 178

CostFormer		52.59 189	55.14 195	49.61 171	52.72 189	50.40 185	66.28 146	33.78 197	52.85 195	43.43 161	66.30 156	51.37 214	41.78 162	54.92 213	51.18 206	59.68 195	58.98 173

CR-MVSNet		53.82 183	55.40 194	51.98 151	51.57 195	50.23 186	45.00 227	44.97 97	46.90 218	52.60 123	67.91 146	46.99 222	48.37 132	59.15 198	59.53 186	69.38 178	57.07 180

Patchmtry						37.73 218	45.00 227	44.97 97		52.60 123

PatchT		50.55 195	53.55 202	47.05 195	37.59 229	42.26 208	50.55 217	37.56 180	46.37 220	52.60 123	66.91 152	43.54 229	48.37 132	59.15 198	59.53 186	55.62 204	57.07 180

tpmrst		43.31 217	46.14 222	40.02 211	47.05 208	36.48 223	48.01 225	32.17 207	49.50 209	37.26 172	63.66 172	47.04 219	31.98 206	42.00 234	40.55 225	43.64 223	43.75 215

tpm		46.67 204	49.20 215	43.72 201	49.60 201	36.60 222	53.93 205	26.84 216	52.70 196	58.05 106	69.04 140	47.96 218	30.06 208	48.33 227	42.76 221	43.88 222	47.01 210

DELS-MVS		65.54 125	71.79 129	58.24 128	59.68 149	65.55 83	70.99 125	38.69 172	62.29 157	49.27 139	75.03 117	81.42 137	50.93 120	73.71 112	71.35 102	79.90 92	73.20 98
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		50.92 193	50.32 209	51.62 156	50.25 199	50.23 186	59.16 177	46.70 85	46.90 218	42.39 164	48.97 221	37.23 232	41.78 162	57.30 209	56.18 193	69.44 177	55.43 187

no-one		64.33 131	73.23 114	53.94 144	38.32 226	50.78 184	56.78 194	27.44 215	61.95 161	56.77 110	64.60 167	93.12 25	71.12 14	81.91 70	77.19 74	73.20 151	83.04 48

MVSTER		53.08 186	56.39 191	49.21 179	47.19 207	51.08 183	60.14 172	31.74 208	40.63 229	38.97 170	55.78 205	46.74 223	42.47 159	67.29 175	62.99 178	74.73 136	70.23 118

CPTT-MVS		82.32 14	85.00 31	79.19 7	80.73 15	80.86 21	91.68 13	62.59 9	82.55 31	75.53 29	73.88 123	92.28 34	73.74 5	90.07 20	87.65 20	90.87 20	87.74 24

GBi-Net		56.54 171	63.26 167	48.70 181	55.88 174	57.61 140	57.26 191	41.75 135	49.06 211	32.37 191	61.81 182	67.02 187	34.58 186	72.33 134	68.45 124	70.38 172	66.56 143

PVSNet_Blended_VisFu		70.70 82	73.62 107	67.28 66	63.53 123	72.96 56	77.97 76	52.10 61	63.65 149	62.66 94	71.14 136	73.46 168	63.55 47	79.35 89	75.34 86	83.90 62	79.43 64

PVSNet_BlendedMVS		61.75 140	65.07 154	57.87 130	56.27 172	60.99 129	65.81 149	43.75 107	51.27 201	54.08 117	62.12 180	78.84 149	50.67 121	71.49 150	63.91 172	76.64 127	66.86 141

PVSNet_Blended		61.75 140	65.07 154	57.87 130	56.27 172	60.99 129	65.81 149	43.75 107	51.27 201	54.08 117	62.12 180	78.84 149	50.67 121	71.49 150	63.91 172	76.64 127	66.86 141

FMVSNet5		39.83 224	45.08 225	33.71 223	39.24 223	39.56 211	48.77 222	23.55 221	39.45 230	24.55 219	33.73 234	44.57 226	20.97 221	58.27 205	54.23 200	45.16 219	45.77 212

test1		56.54 171	63.26 167	48.70 181	55.88 174	57.61 140	57.26 191	41.75 135	49.06 211	32.37 191	61.81 182	67.02 187	34.58 186	72.33 134	68.45 124	70.38 172	66.56 143

new_pmnet		35.76 230	45.64 223	24.22 232	38.59 225	25.83 235	31.87 238	19.24 228	49.06 211	9.01 238	54.34 209	64.73 195	12.46 234	49.21 226	44.91 219	34.17 232	31.41 230

FMVSNet3		54.77 181	60.73 181	47.81 189	54.29 187	56.88 147	55.89 197	41.75 135	49.06 211	32.37 191	61.81 182	67.02 187	33.67 199	62.88 187	61.96 182	68.88 180	65.53 146

dps		49.71 198	51.97 204	47.07 194	52.37 192	47.00 198	53.02 210	40.52 159	44.91 224	41.23 168	64.55 168	44.27 228	40.12 166	57.71 207	51.97 204	55.14 205	53.41 192

FMVSNet2		57.80 162	65.39 151	48.94 180	55.88 174	57.61 140	57.26 191	42.37 123	58.21 170	33.19 185	68.36 144	75.55 162	34.58 186	66.91 177	64.55 168	70.38 172	66.56 143

FMVSNet1		61.92 139	71.36 130	50.90 163	57.67 169	59.29 134	59.48 175	44.14 104	70.24 109	34.72 179	75.45 116	84.94 123	36.75 175	72.33 134	68.45 124	72.66 156	68.83 128

N_pmnet		39.50 227	51.01 207	26.09 231	44.48 217	25.59 236	40.20 234	21.49 225	64.20 148	7.98 239	73.86 124	76.67 159	13.66 231	50.17 225	36.69 233	28.71 234	29.86 233

UGNet		65.61 124	74.79 93	54.91 142	54.54 185	68.20 73	70.97 127	48.21 74	67.14 134	41.67 167	74.15 122	80.65 141	36.10 180	79.39 88	77.99 68	77.95 121	76.01 82
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		58.09 160	63.54 166	51.74 154	50.13 200	46.56 200	66.95 144	33.41 199	63.52 150	58.77 103	74.84 119	84.10 130	43.12 156	65.95 178	54.69 197	58.04 199	55.13 188

MDTV_nov1_ep13		49.60 199	51.57 205	47.31 191	46.28 211	44.61 202	59.82 174	30.96 209	48.80 215	50.20 134	59.26 194	52.38 213	38.56 167	56.20 211	49.70 211	58.04 199	50.01 200

MIMVSNet1		56.72 168	68.69 140	42.76 203	46.70 210	42.81 206	69.13 136	30.52 212	81.01 44	32.00 196	74.82 120	91.10 56	26.83 214	73.98 109	64.72 167	51.40 211	52.38 194

MIMVSNet		45.83 208	53.46 203	36.94 215	45.38 216	39.50 212	52.20 211	30.68 210	57.09 179	24.53 220	55.22 207	71.54 171	21.74 220	55.81 212	51.08 207	47.11 218	43.96 214

IterMVS-LS		65.76 122	70.85 133	59.81 121	65.33 95	57.78 139	64.63 156	48.02 76	65.65 140	51.05 130	81.31 81	77.47 157	54.94 104	69.46 169	69.36 114	74.90 135	74.95 86
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet		57.90 161	63.57 165	51.28 159	62.30 132	53.17 173	64.70 155	51.61 62	57.41 177	32.75 187	63.73 171	70.53 174	27.12 212	72.49 129	73.02 97	69.22 179	54.68 191
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
IterMVS		59.24 153	64.45 158	53.16 146	50.98 196	61.29 126	66.51 145	32.85 202	58.17 171	46.31 152	72.58 131	70.23 175	54.26 107	64.81 182	60.24 184	68.04 182	63.81 153
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MVS_111021_LR		71.60 71	75.21 86	67.38 64	67.42 81	62.44 121	81.73 59	46.24 88	70.89 101	66.80 81	73.19 128	84.98 122	60.09 62	81.94 69	77.77 71	82.00 81	75.29 85

HQP-MVS		75.81 54	78.91 65	72.18 41	77.41 38	75.38 46	84.75 43	53.35 54	76.12 69	73.32 33	69.48 138	88.07 92	57.76 78	79.42 87	78.44 63	86.48 48	85.50 41

QAPM		66.36 120	72.76 121	58.90 123	59.57 150	65.01 89	64.05 159	41.17 144	73.09 85	56.82 109	69.42 139	77.78 155	55.07 103	73.00 122	72.07 100	76.71 126	78.96 68

Vis-MVSNet		69.95 95	77.69 70	60.91 116	60.67 142	66.71 75	77.94 77	48.58 71	69.10 120	45.78 154	80.21 90	83.58 133	53.41 113	82.92 64	80.11 57	79.08 99	81.21 57
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet		44.56 213	45.52 224	43.44 202	40.98 221	31.03 231	39.52 235	36.96 184	42.80 226	44.37 159	53.80 212	60.04 207	41.85 161	47.97 229	41.08 224	56.99 203	41.95 218

HyFIR lowres test		59.15 155	62.28 173	55.49 140	52.42 191	62.59 120	71.76 123	39.74 162	50.25 206	41.92 165	62.88 175	69.16 183	55.85 98	62.77 188	67.18 144	71.27 164	61.11 161

EPMVS		40.11 223	44.96 228	34.44 219	41.55 218	32.65 229	41.74 232	32.39 205	49.89 208	24.83 217	64.44 169	46.38 224	26.57 215	44.75 231	39.47 229	39.59 226	37.16 225

TAMVS		46.64 205	53.62 201	38.49 212	49.56 202	36.87 219	53.16 209	25.76 218	56.33 183	22.55 226	60.72 185	61.80 202	27.12 212	59.50 195	58.33 188	52.79 208	41.82 219

IS_MVSNet		68.20 114	74.41 101	60.96 115	68.55 77	64.36 100	71.47 124	48.33 73	70.11 113	43.30 163	80.90 83	74.54 166	47.19 141	81.25 71	77.97 69	86.94 45	71.76 113

RPSCF		77.56 42	84.51 36	69.46 56	65.17 99	74.36 50	79.74 70	47.45 78	84.01 20	72.89 35	77.89 103	90.67 66	65.14 40	88.25 31	89.74 7	86.38 50	86.64 32

Vis-MVSNet (Re-imp)		60.99 146	67.78 142	53.06 147	64.66 103	53.49 172	67.40 142	49.52 66	68.55 122	28.00 212	79.53 98	71.41 172	33.08 201	75.30 104	71.28 104	75.69 132	54.91 189

MVS_111021_HR		72.37 68	76.12 80	68.00 59	68.55 77	64.30 103	82.93 52	48.98 69	74.25 78	65.39 84	73.59 126	84.11 129	59.48 70	82.61 66	78.38 64	82.66 76	75.59 84

CSCG		76.95 50	82.08 48	70.97 44	73.32 55	78.35 32	81.08 63	47.19 80	83.47 23	69.82 51	80.44 87	87.19 105	64.59 42	81.01 77	77.26 73	89.83 26	86.84 30

PatchMatch-RL		60.96 147	63.00 171	58.57 125	59.16 158	52.18 179	67.38 143	41.99 131	57.85 175	48.16 140	53.55 213	69.77 179	59.47 71	73.73 110	72.49 99	75.27 134	61.44 160

TDRefinement		86.29 1	90.77 1	81.06 1	75.10 47	83.76 2	93.79 1	61.08 18	89.57 2	86.19 1	90.06 7	93.01 27	76.72 2	94.71 1	92.72 1	93.47 1	91.56 2

USDC		68.53 109	71.82 128	64.68 87	63.53 123	61.87 123	70.12 131	46.98 82	77.89 61	76.58 24	68.55 142	86.88 110	50.50 123	73.73 110	65.62 164	80.39 88	68.21 138

EPP-MVSNet		69.51 98	76.17 78	61.74 114	68.38 79	66.60 76	71.77 122	46.98 82	73.60 83	41.79 166	82.06 72	69.65 181	52.51 117	83.41 61	79.94 58	89.02 30	77.94 75

PMMVS		45.37 210	49.29 214	40.79 208	27.75 236	35.07 224	50.88 216	19.88 227	39.27 231	35.78 176	50.11 217	61.29 203	42.04 160	54.13 218	55.95 194	68.43 181	49.19 203

ACMMP		83.17 6	86.75 10	79.01 8	80.11 24	82.01 7	92.29 11	60.35 25	82.20 34	78.32 16	80.59 86	93.14 24	70.67 16	91.30 8	89.36 10	92.30 4	88.62 17
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		76.67 51	81.72 49	70.77 47	70.75 66	76.68 39	86.14 41	46.11 89	81.82 37	74.68 31	76.37 110	86.23 115	62.92 51	85.28 48	83.29 41	84.02 60	82.40 51

PatchmatchNet		48.67 201	50.10 210	46.99 196	48.29 203	41.00 209	55.54 198	38.94 165	51.38 199	45.15 158	63.22 173	48.45 217	42.83 157	53.80 219	48.50 214	51.19 213	44.37 213
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS		75.17 57	78.37 66	71.43 42	71.13 63	72.46 63	82.28 57	50.55 63	73.39 84	79.05 15	73.65 125	87.50 100	61.98 53	81.10 75	78.48 62	83.60 65	81.99 52

OMC-MVS		79.95 30	85.28 27	73.74 35	72.95 56	80.10 26	87.87 36	48.13 75	84.62 13	79.42 14	80.27 89	92.49 31	64.14 43	87.25 37	85.11 31	89.92 25	87.10 29

AdaColmap		74.73 59	77.57 71	71.40 43	76.90 42	75.76 43	84.54 45	53.08 56	76.20 68	66.64 82	66.06 158	78.16 154	61.32 58	85.37 47	82.20 51	85.95 55	79.27 65

DeepMVS_CX						8.52 240	9.75 240	3.19 235	16.70 237	5.02 240	23.06 236	19.33 241	18.69 223	13.75 236		11.34 238	25.07 235

TinyColmap		71.85 69	76.11 81	66.87 67	66.07 89	65.34 86	74.35 106	49.30 68	79.93 55	75.93 28	75.66 115	87.74 96	54.72 105	80.66 82	70.42 111	80.85 86	73.02 102

MAR-MVS		70.00 93	72.28 124	67.34 65	69.89 73	72.57 62	80.09 68	49.49 67	60.28 164	69.03 58	59.29 193	80.79 140	54.68 106	78.39 93	76.00 81	80.87 85	78.67 71
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		68.98 102	73.31 113	63.92 94	67.08 83	68.27 72	75.41 96	40.77 150	67.61 126	64.89 85	75.75 114	78.96 148	53.70 110	76.72 98	73.95 92	81.71 84	71.93 112

LS3D		79.33 33	84.03 40	73.84 33	75.37 46	78.09 34	83.30 49	52.94 57	84.42 16	76.01 27	84.16 42	87.44 101	65.34 38	86.30 41	82.08 52	90.09 23	85.70 38

CLD-MVS		71.24 75	78.12 68	63.20 101	74.03 51	71.60 66	82.82 54	32.91 201	74.23 79	69.32 55	79.65 95	91.54 45	47.02 142	81.22 72	79.01 61	73.09 154	69.63 122
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS		70.46 85	74.89 90	65.28 80	69.09 76	61.42 125	77.07 83	46.92 84	76.73 67	53.53 119	67.33 149	75.07 163	67.23 31	83.41 61	81.54 54	77.86 122	78.73 70

Gipuma		73.40 67	79.27 62	66.55 72	63.64 120	59.35 133	70.28 130	45.92 90	83.79 21	71.78 39	84.04 45	93.07 26	68.69 27	87.90 34	76.76 76	78.98 100	69.96 120
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015

High-resolution multi-view benchmark