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		95.70 1	96.40 1	93.61 2	98.67 1	85.39 29	95.54 3	97.36 1	96.97 1	99.04 1	99.05 1	96.61 1	95.92 8	85.07 36	99.27 3	99.54 1

PS-CasMVS		90.06 34	91.92 9	84.47 131	96.56 6	58.83 248	89.04 60	92.74 65	91.40 5	96.12 4	96.06 24	87.23 35	95.57 21	79.42 109	98.74 7	99.00 2

PEN-MVS		90.03 35	91.88 12	84.48 130	96.57 5	58.88 247	88.95 61	93.19 46	91.62 4	96.01 6	96.16 22	87.02 36	95.60 20	78.69 113	98.72 10	98.97 3

CP-MVSNet		89.27 52	90.91 34	84.37 134	96.34 8	58.61 250	88.66 68	92.06 81	90.78 6	95.67 9	95.17 44	81.80 87	95.54 24	79.00 111	98.69 11	98.95 4

WR-MVS_H		89.91 42	91.31 25	85.71 108	96.32 9	62.39 210	89.54 53	93.31 40	90.21 10	95.57 11	95.66 31	81.42 91	95.90 9	80.94 85	98.80 4	98.84 5

DTE-MVSNet		89.98 37	91.91 11	84.21 139	96.51 7	57.84 251	88.93 63	92.84 62	91.92 2	96.16 3	96.23 20	86.95 37	95.99 4	79.05 110	98.57 16	98.80 6

Anonymous20231211		90.14 31	91.88 12	84.92 117	94.75 35	64.47 177	90.13 38	92.97 56	91.68 3	95.35 12	98.79 2	93.19 3	91.76 157	71.67 170	98.40 21	98.52 7

v52		89.97 39	90.60 37	88.07 68	88.69 153	72.01 125	91.35 30	92.64 68	82.22 48	95.97 8	96.31 16	84.82 51	93.98 73	88.59 4	94.83 140	98.23 8

V4		89.97 39	90.60 37	88.07 68	88.69 153	72.01 125	91.35 30	92.64 68	82.22 48	95.98 7	96.31 16	84.80 53	93.98 73	88.59 4	94.83 140	98.23 8

FC-MVSNet-test		85.93 101	87.05 80	82.58 176	92.25 83	56.44 261	85.75 112	93.09 49	77.33 110	91.94 59	94.65 59	74.78 153	93.41 109	75.11 140	98.58 15	97.88 10

v7n		90.13 32	90.96 32	87.65 75	91.95 91	71.06 137	89.99 41	93.05 51	86.53 21	94.29 22	96.27 19	82.69 70	94.08 69	86.25 29	97.63 51	97.82 11

TranMVSNet+NR-MVSNet		87.86 67	88.76 60	85.18 114	94.02 43	64.13 179	84.38 131	91.29 113	84.88 27	92.06 55	93.84 92	86.45 43	93.73 81	73.22 156	98.66 12	97.69 12

DU-MVS		86.80 81	86.99 81	86.21 97	93.24 57	67.02 162	83.16 168	92.21 77	81.73 55	90.92 72	91.97 126	77.20 124	93.99 71	74.16 145	98.35 24	97.61 13

NR-MVSNet		86.00 97	86.22 95	85.34 112	93.24 57	64.56 176	82.21 194	90.46 130	80.99 61	88.42 124	91.97 126	77.56 121	93.85 78	72.46 164	98.65 13	97.61 13

FIs		85.35 108	86.27 94	82.60 175	91.86 94	57.31 255	85.10 120	93.05 51	75.83 128	91.02 71	93.97 84	73.57 174	92.91 132	73.97 148	98.02 39	97.58 15

UniMVSNet_NR-MVSNet		86.84 80	87.06 79	86.17 100	92.86 68	67.02 162	82.55 183	91.56 94	83.08 39	90.92 72	91.82 132	78.25 115	93.99 71	74.16 145	98.35 24	97.49 16

v13		87.31 72	88.10 63	84.94 116	88.84 150	63.75 183	87.85 77	91.47 101	79.12 81	93.72 29	95.82 27	75.20 145	93.58 94	84.76 42	96.16 94	97.48 17

v12		87.15 75	87.91 65	84.84 119	88.69 153	63.52 186	87.58 80	91.46 102	78.74 89	93.57 32	95.66 31	74.94 149	93.57 95	84.50 45	96.08 99	97.43 18

V9		86.96 76	87.70 70	84.74 123	88.52 158	63.27 192	87.31 85	91.45 104	78.28 94	93.43 33	95.45 38	74.59 157	93.57 95	84.23 49	96.01 102	97.38 19

v748		88.91 57	89.82 45	86.19 99	90.06 134	68.53 153	88.81 65	91.48 98	84.36 28	94.19 24	95.98 25	82.52 73	92.67 137	84.30 47	96.67 76	97.37 20

v11		86.96 76	87.78 69	84.51 128	88.50 159	62.60 206	87.21 86	91.63 93	78.08 98	93.40 34	95.56 36	75.07 146	93.57 95	84.46 46	96.08 99	97.36 21

V14		86.75 82	87.46 73	84.62 126	88.35 162	63.00 197	87.02 91	91.42 107	77.78 100	93.27 35	95.23 43	74.22 160	93.56 98	83.95 52	95.93 105	97.31 22

v15		86.56 85	87.25 77	84.51 128	88.15 169	62.72 202	86.72 101	91.40 109	77.38 105	93.11 37	95.00 48	73.93 165	93.55 99	83.67 56	95.86 109	97.26 23

OurMVSNet-221017-0		90.01 36	89.74 46	90.83 33	93.16 59	80.37 59	91.91 27	93.11 48	81.10 60	95.32 13	97.24 6	72.94 188	94.85 48	85.07 36	97.78 46	97.26 23

WR-MVS		83.56 153	84.40 135	81.06 200	93.43 53	54.88 272	78.67 249	85.02 221	81.24 59	90.74 76	91.56 139	72.85 189	91.08 172	68.00 198	98.04 36	97.23 25

TDRefinement		93.52 2	93.39 3	93.88 1	95.94 13	90.26 4	95.70 2	96.46 2	90.58 8	92.86 41	96.29 18	88.16 26	94.17 66	86.07 32	98.48 19	97.22 26

v17		86.32 90	86.95 83	84.44 132	88.00 171	62.62 205	86.74 99	91.48 98	77.17 113	92.74 43	94.56 60	73.74 169	93.53 100	83.27 59	94.87 139	97.18 27

v16		86.24 93	86.85 86	84.43 133	87.96 173	62.59 207	86.73 100	91.48 98	77.17 113	92.67 46	94.55 61	73.63 170	93.52 101	83.26 60	94.16 154	97.17 28

v10		86.54 86	87.10 78	84.84 119	88.16 168	63.28 191	86.64 103	92.20 78	75.42 136	92.81 42	94.50 64	74.05 163	94.06 70	83.88 53	96.28 89	97.17 28

anonymousdsp		89.73 45	88.88 56	92.27 7	89.82 138	86.67 12	90.51 35	90.20 147	69.87 197	95.06 14	96.14 23	84.28 56	93.07 127	87.68 13	96.34 87	97.09 30

v18		85.99 99	86.55 90	84.30 137	87.73 185	62.29 215	86.40 107	91.49 97	76.64 119	92.40 51	94.20 77	73.28 181	93.52 101	82.87 65	93.99 158	97.09 30

test_djsdf		89.62 46	89.01 53	91.45 21	92.36 79	82.98 49	91.98 25	90.08 148	71.54 183	94.28 23	96.54 13	81.57 89	94.27 59	86.26 27	96.49 83	97.09 30

v8		86.22 95	86.83 87	84.36 135	87.82 179	62.35 211	86.42 106	91.33 112	76.78 118	92.73 44	94.48 65	73.41 177	93.72 82	83.10 61	95.41 119	97.01 33

UniMVSNet (Re)		86.87 78	86.98 82	86.55 87	93.11 61	68.48 154	83.80 146	92.87 59	80.37 65	89.61 103	91.81 133	77.72 119	94.18 64	75.00 142	98.53 17	96.99 34

IS-MVSNet		86.66 84	86.82 88	86.17 100	92.05 89	66.87 164	91.21 33	88.64 170	86.30 23	89.60 104	92.59 113	69.22 213	94.91 47	73.89 149	97.89 44	96.72 35

UA-Net		91.49 14	91.53 18	91.39 22	94.98 31	82.95 50	93.52 5	92.79 63	88.22 16	88.53 121	97.64 3	83.45 63	94.55 57	86.02 33	98.60 14	96.67 36

pmmvs6		86.52 87	88.06 64	81.90 185	92.22 85	62.28 216	84.66 126	89.15 165	83.54 34	89.85 91	97.32 4	88.08 28	86.80 244	70.43 179	97.30 60	96.62 37

RPSCF		88.00 65	86.93 84	91.22 27	90.08 132	89.30 6	89.68 48	91.11 118	79.26 79	89.68 96	94.81 57	82.44 74	87.74 234	76.54 133	88.74 243	96.61 38

LTVRE_ROB	86.10 1	93.04 3	93.44 2	91.82 19	93.73 47	85.72 28	96.79 1	95.51 4	88.86 13	95.63 10	96.99 8	84.81 52	93.16 120	91.10 1	97.53 56	96.58 39
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
nrg030		87.85 68	88.49 61	85.91 103	90.07 133	69.73 143	87.86 76	94.20 17	74.04 146	92.70 45	94.66 58	85.88 49	91.50 161	79.72 103	97.32 59	96.50 40

v2v482		84.09 141	84.24 141	83.62 156	87.13 203	61.40 225	82.71 180	89.71 157	72.19 176	89.55 105	91.41 142	70.70 210	93.20 117	81.02 83	93.76 165	96.25 41

PS-MVSNAJss		88.31 62	87.90 66	89.56 51	93.31 55	77.96 78	87.94 75	91.97 84	70.73 189	94.19 24	96.67 11	76.94 130	94.57 55	83.07 62	96.28 89	96.15 42

v1192		84.57 122	84.69 123	84.21 139	87.75 184	62.88 199	83.02 170	91.43 105	69.08 203	89.98 86	90.89 163	72.70 193	93.62 90	82.41 70	94.97 134	96.13 43

EI-MVSNet-UG-set		85.04 112	84.44 133	86.85 83	83.87 254	72.52 118	83.82 144	85.15 218	80.27 68	88.75 117	85.45 249	79.95 104	91.90 151	81.92 76	90.80 221	96.13 43

v1921920		84.23 136	84.37 139	83.79 148	87.64 189	61.71 219	82.91 173	91.20 116	67.94 212	90.06 82	90.34 177	72.04 202	93.59 91	82.32 72	94.91 135	96.07 45

v1240		84.30 133	84.51 132	83.65 155	87.65 188	61.26 228	82.85 174	91.54 95	67.94 212	90.68 77	90.65 172	71.71 205	93.64 85	82.84 67	94.78 142	96.07 45

v144192		84.24 135	84.41 134	83.71 154	87.59 190	61.57 224	82.95 172	91.03 120	67.82 215	89.80 93	90.49 175	73.28 181	93.51 104	81.88 77	94.89 136	96.04 47

pcd1.5k->3k		38.83 318	41.11 319	32.01 329	93.13 60	0.00 349	0.00 340	91.38 111	0.00 344	0.00 345	0.00 346	89.24 16	0.00 347	0.00 344	96.24 92	96.02 48

v1144		84.54 125	84.72 121	84.00 143	87.67 187	62.55 208	82.97 171	90.93 122	70.32 193	89.80 93	90.99 158	73.50 175	93.48 105	81.69 78	94.65 148	95.97 49

EI-MVSNet-Vis-set		85.12 110	84.53 131	86.88 82	84.01 251	72.76 115	83.91 142	85.18 217	80.44 64	88.75 117	85.49 245	80.08 102	91.92 150	82.02 74	90.85 220	95.97 49

HPM-MVS_fast		92.50 5	92.54 5	92.37 5	95.93 14	85.81 27	92.99 11	94.23 16	85.21 24	92.51 48	95.13 45	90.65 11	95.34 32	88.06 10	98.15 34	95.95 51

v7		84.81 117	85.00 114	84.23 138	88.15 169	63.27 192	83.79 147	91.39 110	71.10 187	90.07 81	91.28 143	74.04 164	93.63 86	81.48 79	93.67 168	95.79 52

ANet_high		83.17 160	85.68 104	75.65 261	81.24 272	45.26 321	79.94 230	92.91 58	83.83 33	91.33 68	96.88 10	80.25 101	85.92 254	68.89 191	95.89 107	95.76 53

v1141		84.16 138	84.38 136	83.52 160	87.32 196	61.70 221	82.79 176	89.74 154	71.90 180	89.64 98	91.12 152	72.68 194	93.10 123	80.39 95	93.80 163	95.75 54

divwei89l23v2f112		84.16 138	84.38 136	83.52 160	87.32 196	61.70 221	82.79 176	89.74 154	71.90 180	89.64 98	91.12 152	72.68 194	93.10 123	80.40 93	93.81 162	95.75 54

v1		84.16 138	84.38 136	83.52 160	87.33 195	61.71 219	82.79 176	89.73 156	71.89 182	89.64 98	91.11 154	72.72 191	93.10 123	80.40 93	93.79 164	95.75 54

IterMVS-LS		84.73 119	84.98 115	83.96 145	87.35 194	63.66 184	83.25 165	89.88 153	76.06 123	89.62 101	92.37 121	73.40 179	92.52 140	78.16 118	94.77 144	95.69 57
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
EI-MVSNet		82.61 164	82.42 166	83.20 166	83.25 258	63.66 184	83.50 158	85.07 219	76.06 123	86.55 150	85.10 254	73.41 177	90.25 193	78.15 119	90.67 224	95.68 58

EPP-MVSNet		85.47 107	85.04 113	86.77 84	91.52 104	69.37 146	91.63 28	87.98 182	81.51 58	87.05 144	91.83 131	66.18 225	95.29 33	70.75 174	96.89 69	95.64 59

v1neww		84.43 127	84.66 125	83.75 150	87.81 180	62.34 212	83.59 151	90.27 143	72.33 173	89.93 88	91.22 145	73.28 181	93.29 112	80.25 97	93.25 179	95.62 60

v7new		84.43 127	84.66 125	83.75 150	87.81 180	62.34 212	83.59 151	90.27 143	72.33 173	89.93 88	91.22 145	73.28 181	93.29 112	80.25 97	93.25 179	95.62 60

v6		84.43 127	84.66 125	83.75 150	87.81 180	62.34 212	83.59 151	90.26 145	72.33 173	89.94 87	91.19 149	73.30 180	93.29 112	80.26 96	93.26 178	95.62 60

V42		83.47 156	83.37 152	83.75 150	83.16 260	63.33 190	81.31 213	90.23 146	69.51 199	90.91 74	90.81 166	74.16 161	92.29 144	80.06 99	90.22 229	95.62 60

ACMH+	77.89 11	90.73 25	91.50 19	88.44 62	93.00 63	76.26 97	89.65 49	95.55 3	87.72 18	93.89 27	94.94 50	91.62 5	93.44 107	78.35 115	98.76 5	95.61 64

mvs_tets		89.78 44	89.27 51	91.30 24	93.51 50	84.79 36	89.89 44	90.63 126	70.00 196	94.55 18	96.67 11	87.94 29	93.59 91	84.27 48	95.97 103	95.52 65

OMC-MVS		88.19 63	87.52 72	90.19 44	91.94 93	81.68 53	87.49 83	93.17 47	76.02 125	88.64 119	91.22 145	84.24 57	93.37 110	77.97 121	97.03 66	95.52 65

SixPastTwentyTwo		87.20 74	87.45 74	86.45 89	92.52 74	69.19 151	87.84 78	88.05 179	81.66 56	94.64 17	96.53 14	65.94 226	94.75 50	83.02 64	96.83 72	95.41 67

jajsoiax		89.41 49	88.81 58	91.19 28	93.38 54	84.72 37	89.70 46	90.29 142	69.27 200	94.39 20	96.38 15	86.02 48	93.52 101	83.96 51	95.92 106	95.34 68

HPM-MVS		92.13 6	92.20 7	91.91 15	95.58 23	84.67 38	93.51 6	94.85 9	82.88 41	91.77 61	93.94 90	90.55 13	95.73 17	88.50 8	98.23 31	95.33 69

Baseline_NR-MVSNet		84.00 145	85.90 100	78.29 230	91.47 106	53.44 280	82.29 190	87.00 200	79.06 83	89.55 105	95.72 30	77.20 124	86.14 252	72.30 165	98.51 18	95.28 70

3Dnovator+	83.92 2	89.97 39	89.66 47	90.92 32	91.27 110	81.66 54	91.25 32	94.13 22	88.89 12	88.83 116	94.26 74	77.55 122	95.86 12	84.88 39	95.87 108	95.24 71

LPG-MVS_test		91.47 16	91.68 15	90.82 34	94.75 35	81.69 51	90.00 39	94.27 13	82.35 46	93.67 30	94.82 54	91.18 6	95.52 25	85.36 34	98.73 8	95.23 72

LGP-MVS_train				90.82 34	94.75 35	81.69 51		94.27 13	82.35 46	93.67 30	94.82 54	91.18 6	95.52 25	85.36 34	98.73 8	95.23 72

Regformer-4		86.41 88	85.71 103	88.52 61	84.27 245	77.57 81	84.07 135	88.00 181	82.82 42	89.84 92	85.48 246	82.06 79	92.77 134	83.83 55	91.04 210	95.22 74

MP-MVS-pluss		90.81 24	91.08 29	89.99 46	95.97 12	79.88 63	88.13 73	94.51 11	75.79 129	92.94 38	94.96 49	88.36 20	95.01 44	90.70 2	98.40 21	95.09 75
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
COLMAP_ROB	83.01 3	91.97 8	91.95 8	92.04 10	93.68 48	86.15 18	93.37 8	95.10 7	90.28 9	92.11 53	95.03 47	89.75 15	94.93 46	79.95 101	98.27 29	95.04 76
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
v148		82.31 168	82.48 165	81.81 191	85.59 229	59.66 241	81.47 211	86.02 208	72.85 165	88.05 128	90.65 172	70.73 209	90.91 178	75.15 139	91.79 202	94.87 77

ACMP	79.16 10	90.54 29	90.60 37	90.35 41	94.36 40	80.98 57	89.16 59	94.05 23	79.03 84	92.87 40	93.74 93	90.60 12	95.21 39	82.87 65	98.76 5	94.87 77
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
Regformer-3		85.06 111	84.67 124	86.22 95	84.27 245	73.43 111	84.07 135	85.26 215	80.77 63	88.62 120	85.48 246	80.56 99	90.39 192	81.99 75	91.04 210	94.85 79

K. test v3		85.14 109	84.73 119	86.37 90	91.13 115	69.63 145	85.45 116	76.68 263	84.06 32	92.44 50	96.99 8	62.03 238	94.65 52	80.58 91	93.24 181	94.83 80

TSAR-MVS + MP.		88.14 64	87.82 68	89.09 57	95.72 19	76.74 91	92.49 20	91.19 117	67.85 214	86.63 149	94.84 53	79.58 106	95.96 7	87.62 14	94.50 150	94.56 81

testing_2		84.36 130	84.64 128	83.50 163	86.74 212	63.97 182	84.56 128	90.31 137	66.22 223	91.62 63	94.55 61	75.88 140	91.95 149	77.02 131	94.89 136	94.56 81

ACMMP		91.91 9	91.87 14	92.03 11	95.53 24	85.91 22	93.35 9	94.16 20	82.52 45	92.39 52	94.14 79	89.15 17	95.62 19	87.35 19	98.24 30	94.56 81
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
ITE_SJBPF				90.11 45	90.72 123	84.97 33		90.30 139	81.56 57	90.02 83	91.20 148	82.40 75	90.81 181	73.58 152	94.66 147	94.56 81

LS3D		90.60 28	90.34 40	91.38 23	89.03 147	84.23 42	93.58 4	94.68 10	90.65 7	90.33 79	93.95 89	84.50 55	95.37 31	80.87 86	95.50 118	94.53 85

HQP_MVS		87.75 70	87.43 75	88.70 60	93.45 51	76.42 95	89.45 56	93.61 31	79.44 77	86.55 150	92.95 105	74.84 151	95.22 37	80.78 88	95.83 110	94.46 86

plane_prior5								93.61 31					95.22 37	80.78 88	95.83 110	94.46 86

TransMVSNet (Re)		84.02 144	85.74 102	78.85 221	91.00 117	55.20 271	82.29 190	87.26 190	79.65 74	88.38 126	95.52 37	83.00 67	86.88 242	67.97 199	96.60 78	94.45 88

pm-mvs1		83.69 150	84.95 116	79.91 209	90.04 136	59.66 241	82.43 185	87.44 187	75.52 133	87.85 131	95.26 42	81.25 93	85.65 258	68.74 193	96.04 101	94.42 89

SteuartSystems-ACMMP		91.16 22	91.36 22	90.55 37	93.91 46	80.97 58	91.49 29	93.48 35	82.82 42	92.60 47	93.97 84	88.19 24	96.29 3	87.61 15	98.20 33	94.39 90
Skip Steuart: Steuart Systems R&D Blog.
VPA-MVSNet		83.47 156	84.73 119	79.69 213	90.29 129	57.52 254	81.30 215	88.69 169	76.29 121	87.58 134	94.44 66	80.60 98	87.20 238	66.60 208	96.82 73	94.34 91

XVS		91.54 12	91.36 22	92.08 8	95.64 21	86.25 16	92.64 15	93.33 38	85.07 25	89.99 84	94.03 82	86.57 41	95.80 13	87.35 19	97.62 52	94.20 92

X-MVStestdata		85.04 112	82.70 159	92.08 8	95.64 21	86.25 16	92.64 15	93.33 38	85.07 25	89.99 84	16.05 341	86.57 41	95.80 13	87.35 19	97.62 52	94.20 92

APD-MVS_3200maxsize		92.05 7	92.24 6	91.48 20	93.02 62	85.17 31	92.47 21	95.05 8	87.65 19	93.21 36	94.39 71	90.09 14	95.08 42	86.67 24	97.60 54	94.18 94

AllTest		87.97 66	87.40 76	89.68 47	91.59 98	83.40 45	89.50 54	95.44 5	79.47 75	88.00 129	93.03 101	82.66 71	91.47 162	70.81 172	96.14 96	94.16 95

TestCases				89.68 47	91.59 98	83.40 45		95.44 5	79.47 75	88.00 129	93.03 101	82.66 71	91.47 162	70.81 172	96.14 96	94.16 95

OPM-MVS		89.80 43	89.97 42	89.27 54	94.76 34	79.86 64	86.76 97	92.78 64	78.78 87	92.51 48	93.64 94	88.13 27	93.84 80	84.83 41	97.55 55	94.10 97

Effi-MVS+-dtu		85.82 102	83.38 151	93.14 3	87.13 203	91.15 3	87.70 79	88.42 172	74.57 142	83.56 198	85.65 243	78.49 112	94.21 63	72.04 167	92.88 188	94.05 98

ACMMPR		91.49 14	91.35 24	91.92 14	95.74 18	85.88 24	92.58 18	93.25 45	81.99 51	91.40 67	94.17 78	87.51 34	95.87 10	87.74 11	97.76 47	93.99 99

XVG-OURS-SEG-HR		89.59 47	89.37 50	90.28 42	94.47 39	85.95 21	86.84 93	93.91 25	80.07 70	86.75 147	93.26 97	93.64 2	90.93 176	84.60 44	90.75 222	93.97 100

PGM-MVS		91.20 21	90.95 33	91.93 13	95.67 20	85.85 25	90.00 39	93.90 26	80.32 67	91.74 62	94.41 68	88.17 25	95.98 5	86.37 25	97.99 41	93.96 101

lessismore_v0				85.95 102	91.10 116	70.99 138		70.91 305		91.79 60	94.42 67	61.76 239	92.93 130	79.52 108	93.03 185	93.93 102

region2R		91.44 17	91.30 26	91.87 16	95.75 17	85.90 23	92.63 17	93.30 41	81.91 53	90.88 75	94.21 76	87.75 30	95.87 10	87.60 16	97.71 50	93.83 103

Regformer-2		86.74 83	86.08 98	88.73 59	84.18 249	79.20 69	83.52 155	89.33 163	83.33 35	89.92 90	85.07 256	83.23 66	93.16 120	83.39 57	92.72 191	93.83 103

GBi-Net		82.02 173	82.07 169	81.85 188	86.38 215	61.05 231	86.83 94	88.27 176	72.43 169	86.00 159	95.64 33	63.78 233	90.68 185	65.95 211	93.34 175	93.82 105

test1		82.02 173	82.07 169	81.85 188	86.38 215	61.05 231	86.83 94	88.27 176	72.43 169	86.00 159	95.64 33	63.78 233	90.68 185	65.95 211	93.34 175	93.82 105

FMVSNet1		84.55 123	85.45 108	81.85 188	90.27 130	61.05 231	86.83 94	88.27 176	78.57 91	89.66 97	95.64 33	75.43 142	90.68 185	69.09 189	95.33 121	93.82 105

VDDNet		84.35 132	85.39 109	81.25 197	95.13 28	59.32 244	85.42 117	81.11 242	86.41 22	87.41 137	96.21 21	73.61 173	90.61 188	66.33 209	96.85 70	93.81 108

CDPH-MVS		86.17 96	85.54 106	88.05 71	92.25 83	75.45 100	83.85 143	92.01 82	65.91 226	86.19 157	91.75 135	83.77 60	94.98 45	77.43 126	96.71 75	93.73 109

abl_6		93.02 4	93.16 4	92.60 4	94.73 38	88.99 7	93.26 10	94.19 19	89.11 11	94.43 19	95.27 41	91.86 4	95.09 41	87.54 18	98.02 39	93.71 110

Regformer-1		86.00 97	85.50 107	87.49 77	84.18 249	76.90 89	83.52 155	87.94 183	82.18 50	89.19 110	85.07 256	82.28 77	91.89 152	82.40 71	92.72 191	93.69 111

XVG-ACMP-BASELINE		89.98 37	89.84 44	90.41 39	94.91 33	84.50 41	89.49 55	93.98 24	79.68 73	92.09 54	93.89 91	83.80 59	93.10 123	82.67 69	98.04 36	93.64 112

MIMVSNet1		83.63 152	84.59 129	80.74 202	94.06 42	62.77 201	82.72 179	84.53 225	77.57 103	90.34 78	95.92 26	76.88 136	85.83 256	61.88 233	97.42 57	93.62 113

XVG-OURS		89.18 53	88.83 57	90.23 43	94.28 41	86.11 20	85.91 109	93.60 33	80.16 69	89.13 112	93.44 96	83.82 58	90.98 174	83.86 54	95.30 125	93.60 114

CLD-MVS		83.18 159	82.64 161	84.79 121	89.05 146	67.82 159	77.93 254	92.52 71	68.33 207	85.07 170	81.54 296	82.06 79	92.96 128	69.35 185	97.91 43	93.57 115
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
HQP4-MVS										80.56 233			94.61 53			93.56 116

HQP-MVS		84.61 121	84.06 143	86.27 93	91.19 111	70.66 139	84.77 122	92.68 66	73.30 157	80.55 234	90.17 183	72.10 199	94.61 53	77.30 127	94.47 151	93.56 116

VDD-MVS		84.23 136	84.58 130	83.20 166	91.17 114	65.16 173	83.25 165	84.97 223	79.79 71	87.18 139	94.27 73	74.77 154	90.89 179	69.24 186	96.54 80	93.55 118

VPNet		80.25 193	81.68 173	75.94 259	92.46 76	47.98 316	76.70 264	81.67 240	73.45 152	84.87 174	92.82 108	74.66 156	86.51 247	61.66 236	96.85 70	93.33 119

ACMMP_Plus		90.65 26	91.07 30	89.42 52	95.93 14	79.54 68	89.95 42	93.68 30	77.65 101	91.97 58	94.89 51	88.38 19	95.45 28	89.27 3	97.87 45	93.27 120

DeepC-MVS	82.31 4	89.15 54	89.08 52	89.37 53	93.64 49	79.07 70	88.54 69	94.20 17	73.53 151	89.71 95	94.82 54	85.09 50	95.77 15	84.17 50	98.03 38	93.26 121
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
TAPA-MVS	77.73 12	85.71 105	84.83 118	88.37 63	88.78 152	79.72 65	87.15 89	93.50 34	69.17 201	85.80 163	89.56 192	80.76 96	92.13 146	73.21 160	95.51 117	93.25 122
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMH	76.49 14	89.34 51	91.14 28	83.96 145	92.50 75	70.36 141	89.55 51	93.84 27	81.89 54	94.70 16	95.44 39	90.69 10	88.31 229	83.33 58	98.30 28	93.20 123
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MP-MVS		91.14 23	90.91 34	91.83 18	96.18 10	86.88 11	92.20 22	93.03 54	82.59 44	88.52 122	94.37 72	86.74 38	95.41 30	86.32 26	98.21 32	93.19 124

mPP-MVS		91.69 10	91.47 20	92.37 5	96.04 11	88.48 8	92.72 14	92.60 70	83.09 38	91.54 64	94.25 75	87.67 33	95.51 27	87.21 23	98.11 35	93.12 125

Vis-MVSNet (Re-imp)		77.82 207	77.79 206	77.92 236	88.82 151	51.29 298	83.28 163	71.97 294	74.04 146	82.23 210	89.78 188	57.38 263	89.41 209	57.22 263	95.41 119	93.05 126

tfpnnormal		81.79 176	82.95 157	78.31 229	88.93 149	55.40 267	80.83 223	82.85 231	76.81 117	85.90 162	94.14 79	74.58 158	86.51 247	66.82 207	95.68 116	93.01 127

APDe-MVS		91.22 20	91.92 9	89.14 56	92.97 64	78.04 77	92.84 12	94.14 21	83.33 35	93.90 26	95.73 29	88.77 18	96.41 1	87.60 16	97.98 42	92.98 128

HFP-MVS		91.30 18	91.39 21	91.02 29	95.43 25	84.66 39	92.58 18	93.29 43	81.99 51	91.47 65	93.96 86	88.35 21	95.56 22	87.74 11	97.74 48	92.85 129

#test#		90.49 30	90.31 41	91.02 29	95.43 25	84.66 39	90.65 34	93.29 43	77.00 116	91.47 65	93.96 86	88.35 21	95.56 22	84.88 39	97.74 48	92.85 129

test_prior3		86.31 91	86.31 93	86.32 91	90.59 125	71.99 127	83.37 161	92.85 60	75.43 134	84.58 182	91.57 137	81.92 85	94.17 66	79.54 106	96.97 67	92.80 131

test_prior				86.32 91	90.59 125	71.99 127		92.85 60					94.17 66			92.80 131

PHI-MVS		86.38 89	85.81 101	88.08 67	88.44 161	77.34 84	89.35 58	93.05 51	73.15 162	84.76 176	87.70 221	78.87 110	94.18 64	80.67 90	96.29 88	92.73 133

ambc				82.98 169	90.55 127	64.86 174	88.20 71	89.15 165		89.40 108	93.96 86	71.67 206	91.38 168	78.83 112	96.55 79	92.71 134

alignmvs		83.94 147	83.98 145	83.80 147	87.80 183	67.88 158	84.54 129	91.42 107	73.27 160	88.41 125	87.96 216	72.33 198	90.83 180	76.02 135	94.11 155	92.69 135

view600		76.79 217	76.54 214	77.56 240	87.91 175	50.77 304	81.92 200	71.35 301	77.38 105	84.62 178	88.40 207	45.18 312	89.26 211	58.58 253	93.49 170	92.66 136

view800		76.79 217	76.54 214	77.56 240	87.91 175	50.77 304	81.92 200	71.35 301	77.38 105	84.62 178	88.40 207	45.18 312	89.26 211	58.58 253	93.49 170	92.66 136

conf0.05thres1000		76.79 217	76.54 214	77.56 240	87.91 175	50.77 304	81.92 200	71.35 301	77.38 105	84.62 178	88.40 207	45.18 312	89.26 211	58.58 253	93.49 170	92.66 136

tfpn		76.79 217	76.54 214	77.56 240	87.91 175	50.77 304	81.92 200	71.35 301	77.38 105	84.62 178	88.40 207	45.18 312	89.26 211	58.58 253	93.49 170	92.66 136

thres600view7		75.97 229	75.35 229	77.85 238	87.01 208	51.84 295	80.45 225	73.26 284	75.20 137	83.10 204	86.31 239	45.54 303	89.05 215	55.03 277	92.24 198	92.66 136

thres400		75.14 234	74.23 238	77.86 237	86.24 221	52.12 289	79.24 241	73.87 277	73.34 155	81.82 217	84.60 264	46.02 297	88.80 219	51.98 289	90.99 212	92.66 136

CNVR-MVS		87.81 69	87.68 71	88.21 65	92.87 66	77.30 86	85.25 118	91.23 115	77.31 111	87.07 143	91.47 141	82.94 68	94.71 51	84.67 43	96.27 91	92.62 142

CP-MVS		91.67 11	91.58 17	91.96 12	95.29 27	87.62 9	93.38 7	93.36 36	83.16 37	91.06 70	94.00 83	88.26 23	95.71 18	87.28 22	98.39 23	92.55 143

canonicalmvs		85.50 106	86.14 97	83.58 157	87.97 172	67.13 161	87.55 81	94.32 12	73.44 153	88.47 123	87.54 224	86.45 43	91.06 173	75.76 136	93.76 165	92.54 144

MVSTER		77.09 214	75.70 226	81.25 197	75.27 319	61.08 230	77.49 260	85.07 219	60.78 265	86.55 150	88.68 203	43.14 322	90.25 193	73.69 151	90.67 224	92.42 145

ACMM	79.39 9	90.65 26	90.99 31	89.63 49	95.03 30	83.53 44	89.62 50	93.35 37	79.20 80	93.83 28	93.60 95	90.81 9	92.96 128	85.02 38	98.45 20	92.41 146
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MVS_Test		82.47 167	83.22 153	80.22 207	82.62 264	57.75 253	82.54 184	91.96 85	71.16 186	82.89 206	92.52 117	77.41 123	90.50 190	80.04 100	87.84 254	92.40 147

diffmvs		79.20 200	79.04 198	79.69 213	78.64 293	58.90 246	81.79 204	87.61 186	65.07 237	73.65 283	89.80 187	73.10 187	87.79 233	75.02 141	86.63 264	92.38 148

MVS_0304		84.88 116	83.96 146	87.64 76	87.43 193	74.83 103	84.18 133	93.30 41	77.48 104	77.39 255	88.46 206	74.53 159	95.74 16	78.09 120	94.75 146	92.36 149

NCCC		87.36 71	86.87 85	88.83 58	92.32 82	78.84 73	86.58 104	91.09 119	78.77 88	84.85 175	90.89 163	80.85 95	95.29 33	81.14 82	95.32 122	92.34 150

MPTG		91.27 19	91.26 27	91.29 25	96.59 3	86.29 14	88.94 62	91.81 89	84.07 30	92.00 56	94.40 69	86.63 39	95.28 35	88.59 4	98.31 26	92.30 151

MTAPA		91.52 13	91.60 16	91.29 25	96.59 3	86.29 14	92.02 24	91.81 89	84.07 30	92.00 56	94.40 69	86.63 39	95.28 35	88.59 4	98.31 26	92.30 151

test12				86.57 86	90.74 122	72.63 116		90.69 124		82.76 207		79.20 107	94.80 49		95.32 122	92.27 153

FMVSNet2		81.31 179	81.61 175	80.41 205	86.38 215	58.75 249	83.93 141	86.58 203	72.43 169	87.65 133	92.98 103	63.78 233	90.22 196	66.86 204	93.92 160	92.27 153

CANet		83.79 149	82.85 158	86.63 85	86.17 225	72.21 124	83.76 148	91.43 105	77.24 112	74.39 278	87.45 225	75.36 143	95.42 29	77.03 130	92.83 189	92.25 155

F-COLMAP		84.97 115	83.42 150	89.63 49	92.39 78	83.40 45	88.83 64	91.92 86	73.19 161	80.18 239	89.15 197	77.04 128	93.28 115	65.82 215	92.28 197	92.21 156

Effi-MVS+		83.90 148	84.01 144	83.57 158	87.22 201	65.61 171	86.55 105	92.40 73	78.64 90	81.34 225	84.18 267	83.65 61	92.93 130	74.22 144	87.87 253	92.17 157

Vis-MVSNet		86.86 79	86.58 89	87.72 73	92.09 87	77.43 83	87.35 84	92.09 80	78.87 86	84.27 191	94.05 81	78.35 114	93.65 84	80.54 92	91.58 205	92.08 158
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
mvs-test1		84.55 123	82.12 168	91.84 17	87.13 203	89.54 5	85.05 121	88.42 172	74.57 142	80.60 231	82.98 279	78.49 112	93.98 73	72.04 167	89.77 232	92.00 159

new-patchmatchnet		70.10 271	73.37 244	60.29 317	81.23 273	16.95 344	59.54 323	74.62 273	62.93 248	80.97 226	87.93 218	62.83 237	71.90 307	55.24 275	95.01 133	92.00 159

DeepPCF-MVS	81.24 5	87.28 73	86.21 96	90.49 38	91.48 105	84.90 34	83.41 160	92.38 75	70.25 194	89.35 109	90.68 170	82.85 69	94.57 55	79.55 105	95.95 104	92.00 159

MCST-MVS		84.36 130	83.93 147	85.63 109	91.59 98	71.58 134	83.52 155	92.13 79	61.82 257	83.96 192	89.75 189	79.93 105	93.46 106	78.33 116	94.34 153	91.87 162

test_0402		88.65 58	89.58 49	85.88 105	92.55 73	72.22 123	84.01 137	89.44 162	88.63 14	94.38 21	95.77 28	86.38 45	93.59 91	79.84 102	95.21 126	91.82 163

DeepC-MVS_fast	80.27 8	86.23 94	85.65 105	87.96 72	91.30 108	76.92 88	87.19 87	91.99 83	70.56 190	84.96 171	90.69 169	80.01 103	95.14 40	78.37 114	95.78 112	91.82 163
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
FMVSNet3		78.80 202	78.55 202	79.57 216	82.89 262	56.89 259	81.76 205	85.77 210	69.04 204	86.00 159	90.44 176	51.75 281	90.09 202	65.95 211	93.34 175	91.72 165

CPTT-MVS		89.39 50	88.98 55	90.63 36	95.09 29	86.95 10	92.09 23	92.30 76	79.74 72	87.50 136	92.38 118	81.42 91	93.28 115	83.07 62	97.24 61	91.67 166

MDA-MVSNet-bldmvs		77.47 210	76.90 211	79.16 219	79.03 289	64.59 175	66.58 312	75.67 267	73.15 162	88.86 114	88.99 199	66.94 221	81.23 284	64.71 218	88.22 250	91.64 167

PAPM_NR		83.23 158	83.19 155	83.33 164	90.90 119	65.98 168	88.19 72	90.78 123	78.13 97	80.87 229	87.92 219	73.49 176	92.42 141	70.07 180	88.40 244	91.60 168

PCF-MVS	74.62 15	82.15 171	80.92 184	85.84 106	89.43 140	72.30 121	80.53 224	91.82 88	57.36 276	87.81 132	89.92 186	77.67 120	93.63 86	58.69 252	95.08 130	91.58 169
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
EPNet		80.37 191	78.41 203	86.23 94	76.75 305	73.28 112	87.18 88	77.45 257	76.24 122	68.14 306	88.93 200	65.41 228	93.85 78	69.47 184	96.12 98	91.55 170
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Fast-Effi-MVS+		81.04 184	80.57 185	82.46 180	87.50 191	63.22 194	78.37 250	89.63 158	68.01 209	81.87 215	82.08 291	82.31 76	92.65 138	67.10 202	88.30 249	91.51 171

mvs_anonymous		78.13 205	78.76 200	76.23 258	79.24 287	50.31 310	78.69 248	84.82 224	61.60 261	83.09 205	92.82 108	73.89 167	87.01 239	68.33 197	86.41 267	91.37 172

SD-MVS		88.96 55	89.88 43	86.22 95	91.63 97	77.07 87	89.82 45	93.77 29	78.90 85	92.88 39	92.29 122	86.11 47	90.22 196	86.24 30	97.24 61	91.36 173

conf200view11		75.62 232	75.05 230	77.34 245	87.27 198	51.88 292	81.07 218	73.26 284	75.68 130	83.25 201	86.37 235	45.54 303	88.80 219	51.98 289	90.99 212	91.34 174

agg_prior1		85.72 104	85.20 111	87.28 81	91.58 101	77.69 79	83.69 150	90.30 139	66.29 222	84.32 188	91.07 156	82.13 78	93.18 118	81.02 83	96.36 86	90.98 175

VNet		79.31 199	80.27 190	76.44 254	87.92 174	53.95 276	75.58 275	84.35 226	74.39 144	82.23 210	90.72 168	72.84 190	84.39 269	60.38 245	93.98 159	90.97 176

Fast-Effi-MVS+-dtu		82.54 166	81.41 177	85.90 104	85.60 228	76.53 94	83.07 169	89.62 159	73.02 164	79.11 246	83.51 273	80.74 97	90.24 195	68.76 192	89.29 235	90.94 177

Patchmtry		76.56 224	77.46 207	73.83 269	79.37 286	46.60 318	82.41 186	76.90 260	73.81 149	85.56 167	92.38 118	48.07 290	83.98 272	63.36 227	95.31 124	90.92 178

Test4		81.31 179	81.13 181	81.88 187	84.89 236	63.05 196	82.37 187	90.50 129	62.75 250	89.00 113	88.29 212	67.55 219	91.68 158	73.55 153	91.24 207	90.89 179

CANet_DTU		77.81 208	77.05 209	80.09 208	81.37 271	59.90 240	83.26 164	88.29 175	69.16 202	67.83 309	83.72 271	60.93 241	89.47 206	69.22 188	89.70 233	90.88 180

train_agg		85.98 100	85.28 110	88.07 68	92.34 80	79.70 66	83.94 139	90.32 135	65.79 227	84.49 184	90.97 159	81.93 83	93.63 86	81.21 80	96.54 80	90.88 180

agg_prior3		85.76 103	84.95 116	88.16 66	92.43 77	79.92 62	83.98 138	90.03 150	65.11 236	83.66 196	90.64 174	81.00 94	93.67 83	81.21 80	96.54 80	90.88 180

114514_t		83.10 161	82.54 164	84.77 122	92.90 65	69.10 152	86.65 102	90.62 127	54.66 288	81.46 222	90.81 166	76.98 129	94.38 58	72.62 163	96.18 93	90.82 183

LCM-MVSNet-Re		83.48 155	85.06 112	78.75 223	85.94 227	55.75 266	80.05 228	94.27 13	76.47 120	96.09 5	94.54 63	83.31 65	89.75 205	59.95 246	94.89 136	90.75 184

DP-MVS		88.60 60	89.01 53	87.36 80	91.30 108	77.50 82	87.55 81	92.97 56	87.95 17	89.62 101	92.87 107	84.56 54	93.89 77	77.65 122	96.62 77	90.70 185

LFMVS		80.15 196	80.56 186	78.89 220	89.19 145	55.93 263	85.22 119	73.78 279	82.96 40	84.28 190	92.72 112	57.38 263	90.07 203	63.80 224	95.75 113	90.68 186

PAPR		78.84 201	78.10 204	81.07 199	85.17 233	60.22 238	82.21 194	90.57 128	62.51 252	75.32 271	84.61 263	74.99 148	92.30 143	59.48 250	88.04 251	90.68 186

test_normal		81.23 183	81.16 180	81.43 194	84.77 238	61.99 218	81.46 212	86.95 201	63.16 247	87.22 138	89.63 190	73.62 171	91.65 159	72.92 161	90.70 223	90.65 188

test9_res														80.83 87	96.45 85	90.57 189

UGNet		82.78 162	81.64 174	86.21 97	86.20 224	76.24 98	86.86 92	85.68 211	77.07 115	73.76 281	92.82 108	69.64 211	91.82 155	69.04 190	93.69 167	90.56 190
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
HSP-MVS		88.63 59	87.84 67	91.02 29	95.76 16	86.14 19	92.75 13	91.01 121	78.43 92	89.16 111	92.25 124	72.03 203	96.36 2	88.21 9	90.93 217	90.55 191

DELS-MVS		81.44 178	81.25 179	82.03 183	84.27 245	62.87 200	76.47 268	92.49 72	70.97 188	81.64 221	83.83 270	75.03 147	92.70 135	74.29 143	92.22 200	90.51 192
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
APD-MVS		89.54 48	89.63 48	89.26 55	92.57 72	81.34 56	90.19 37	93.08 50	80.87 62	91.13 69	93.19 98	86.22 46	95.97 6	82.23 73	97.18 63	90.45 193
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
CSCG		86.26 92	86.47 91	85.60 110	90.87 120	74.26 107	87.98 74	91.85 87	80.35 66	89.54 107	88.01 215	79.09 108	92.13 146	75.51 137	95.06 131	90.41 194

DI_MVS_plusplus_test		81.27 181	81.26 178	81.29 196	84.98 234	61.65 223	81.98 199	87.25 191	63.56 242	87.56 135	89.60 191	73.62 171	91.83 154	72.20 166	90.59 228	90.38 195

DP-MVS Recon		84.05 143	83.22 153	86.52 88	91.73 96	75.27 101	83.23 167	92.40 73	72.04 177	82.04 213	88.33 211	77.91 118	93.95 76	66.17 210	95.12 129	90.34 196

semantic-postprocess				84.34 136	83.93 252	69.66 144		81.09 243	72.43 169	86.47 156	90.19 181	57.56 262	93.15 122	77.45 125	86.39 268	90.22 197

agg_prior2														79.68 104	96.16 94	90.22 197

HPM-MVS++		88.93 56	88.45 62	90.38 40	94.92 32	85.85 25	89.70 46	91.27 114	78.20 95	86.69 148	92.28 123	80.36 100	95.06 43	86.17 31	96.49 83	90.22 197

HyFIR lowres test		75.12 236	72.66 250	82.50 179	91.44 107	65.19 172	72.47 292	87.31 189	46.79 324	80.29 237	84.30 266	52.70 279	92.10 148	51.88 293	86.73 263	90.22 197

PVSNet_BlendedMVS		78.80 202	77.84 205	81.65 192	84.43 241	63.41 187	79.49 237	90.44 131	61.70 260	75.43 269	87.07 229	69.11 214	91.44 164	60.68 243	92.24 198	90.11 201

MVS_111021_HR		84.63 120	84.34 140	85.49 111	90.18 131	75.86 99	79.23 243	87.13 195	73.35 154	85.56 167	89.34 195	83.60 62	90.50 190	76.64 132	94.05 157	90.09 202

GA-MVS		75.83 230	74.61 233	79.48 218	81.87 267	59.25 245	73.42 290	82.88 230	68.68 206	79.75 240	81.80 293	50.62 283	89.46 207	66.85 205	85.64 273	89.72 203

MG-MVS		80.32 192	80.94 183	78.47 228	88.18 166	52.62 287	82.29 190	85.01 222	72.01 178	79.24 245	92.54 116	69.36 212	93.36 111	70.65 176	89.19 238	89.45 204

PLC	73.85 16	82.09 172	80.31 189	87.45 78	90.86 121	80.29 60	85.88 110	90.65 125	68.17 208	76.32 261	86.33 237	73.12 186	92.61 139	61.40 239	90.02 231	89.44 205
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
ab-mvs		79.67 198	80.56 186	76.99 247	88.48 160	56.93 257	84.70 125	86.06 207	68.95 205	80.78 230	93.08 100	75.30 144	84.62 267	56.78 265	90.90 218	89.43 206

thres100view900		75.45 233	75.05 230	76.66 253	87.27 198	51.88 292	81.07 218	73.26 284	75.68 130	83.25 201	86.37 235	45.54 303	88.80 219	51.98 289	90.99 212	89.31 207

tfpn200view9		74.86 240	74.23 238	76.74 252	86.24 221	52.12 289	79.24 241	73.87 277	73.34 155	81.82 217	84.60 264	46.02 297	88.80 219	51.98 289	90.99 212	89.31 207

3Dnovator	80.37 7	84.80 118	84.71 122	85.06 115	86.36 218	74.71 104	88.77 66	90.00 151	75.65 132	84.96 171	93.17 99	74.06 162	91.19 169	78.28 117	91.09 208	89.29 209

CNLPA		83.55 154	83.10 156	84.90 118	89.34 142	83.87 43	84.54 129	88.77 167	79.09 82	83.54 199	88.66 204	74.87 150	81.73 283	66.84 206	92.29 196	89.11 210

CMPMVS	59.41 20	75.12 236	73.57 242	79.77 210	75.84 311	67.22 160	81.21 216	82.18 234	50.78 313	76.50 258	87.66 222	55.20 273	82.99 277	62.17 232	90.64 227	89.09 211
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MVSFormer		82.23 170	81.57 176	84.19 141	85.54 230	69.26 148	91.98 25	90.08 148	71.54 183	76.23 262	85.07 256	58.69 256	94.27 59	86.26 27	88.77 241	89.03 212

jason		77.42 211	75.75 225	82.43 181	87.10 206	69.27 147	77.99 253	81.94 238	51.47 308	77.84 250	85.07 256	60.32 245	89.00 216	70.74 175	89.27 237	89.03 212
jason: jason.
TSAR-MVS + GP.		83.95 146	82.69 160	87.72 73	89.27 143	81.45 55	83.72 149	81.58 241	74.73 140	85.66 164	86.06 241	72.56 197	92.69 136	75.44 138	95.21 126	89.01 214

QAPM		82.59 165	82.59 163	82.58 176	86.44 213	66.69 165	89.94 43	90.36 134	67.97 211	84.94 173	92.58 115	72.71 192	92.18 145	70.63 177	87.73 255	88.85 215

LF4IMVS		82.75 163	81.93 172	85.19 113	82.08 265	80.15 61	85.53 115	88.76 168	68.01 209	85.58 166	87.75 220	71.80 204	86.85 243	74.02 147	93.87 161	88.58 216

MVS_111021_LR		84.28 134	83.76 148	85.83 107	89.23 144	83.07 48	80.99 220	83.56 227	72.71 167	86.07 158	89.07 198	81.75 88	86.19 251	77.11 129	93.36 174	88.24 217

EG-PatchMatch MVS		84.08 142	84.11 142	83.98 144	92.22 85	72.61 117	82.20 196	87.02 199	72.63 168	88.86 114	91.02 157	78.52 111	91.11 171	73.41 155	91.09 208	88.21 218

lupinMVS		76.37 226	74.46 236	82.09 182	85.54 230	69.26 148	76.79 262	80.77 245	50.68 315	76.23 262	82.82 283	58.69 256	88.94 217	69.85 181	88.77 241	88.07 219

cascas		76.29 227	74.81 232	80.72 204	84.47 240	62.94 198	73.89 287	87.34 188	55.94 282	75.16 273	76.53 317	63.97 231	91.16 170	65.00 217	90.97 216	88.06 220

TAMVS		78.08 206	76.36 219	83.23 165	90.62 124	72.87 114	79.08 244	80.01 249	61.72 259	81.35 224	86.92 230	63.96 232	88.78 223	50.61 294	93.01 186	88.04 221

PVSNet_Blended_VisFu		81.55 177	80.49 188	84.70 125	91.58 101	73.24 113	84.21 132	91.67 92	62.86 249	80.94 227	87.16 227	67.27 220	92.87 133	69.82 182	88.94 240	87.99 222

FMVSNet5		72.10 258	71.69 258	73.32 270	81.57 270	53.02 283	76.77 263	78.37 253	63.31 245	76.37 259	91.85 129	36.68 332	78.98 291	47.87 307	92.45 194	87.95 223

CDS-MVSNet		77.32 212	75.40 227	83.06 168	89.00 148	72.48 119	77.90 255	82.17 235	60.81 264	78.94 247	83.49 274	59.30 253	88.76 224	54.64 280	92.37 195	87.93 224
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
pmmvs-eth3d		78.42 204	77.04 210	82.57 178	87.44 192	74.41 106	80.86 222	79.67 250	55.68 283	84.69 177	90.31 180	60.91 242	85.42 259	62.20 231	91.59 204	87.88 225

test20.03		73.75 247	74.59 235	71.22 283	81.11 274	51.12 300	70.15 300	72.10 293	70.42 191	80.28 238	91.50 140	64.21 230	74.72 303	46.96 312	94.58 149	87.82 226

BH-RMVSNet		80.53 190	80.22 191	81.49 193	87.19 202	66.21 167	77.79 256	86.23 205	74.21 145	83.69 194	88.50 205	73.25 185	90.75 182	63.18 229	87.90 252	87.52 227

IterMVS		76.91 216	76.34 220	78.64 225	80.91 276	64.03 180	76.30 269	79.03 251	64.88 239	83.11 203	89.16 196	59.90 249	84.46 268	68.61 195	85.15 279	87.42 228
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
OpenMVS	76.72 13	81.98 175	82.00 171	81.93 184	84.42 243	68.22 156	88.50 70	89.48 161	66.92 218	81.80 219	91.86 128	72.59 196	90.16 198	71.19 171	91.25 206	87.40 229

1112_ss		74.82 241	73.74 240	78.04 234	89.57 139	60.04 239	76.49 267	87.09 198	54.31 289	73.66 282	79.80 305	60.25 246	86.76 245	58.37 257	84.15 287	87.32 230

Test_1112_low_res		73.90 246	73.08 246	76.35 255	90.35 128	55.95 262	73.40 291	86.17 206	50.70 314	73.14 284	85.94 242	58.31 258	85.90 255	56.51 266	83.22 291	87.20 231

UnsupCasMVSNet_eth		71.63 261	72.30 255	69.62 287	76.47 307	52.70 286	70.03 301	80.97 244	59.18 270	79.36 244	88.21 213	60.50 243	69.12 314	58.33 259	77.62 316	87.04 232

testgi		72.36 255	74.61 233	65.59 302	80.56 280	42.82 329	68.29 304	73.35 283	66.87 219	81.84 216	89.93 185	72.08 201	66.92 321	46.05 314	92.54 193	87.01 233

xiu_mvs_v1_base_debu		80.84 187	80.14 192	82.93 171	88.31 163	71.73 130	79.53 234	87.17 192	65.43 231	79.59 241	82.73 285	76.94 130	90.14 199	73.22 156	88.33 245	86.90 234

xiu_mvs_v1_base		80.84 187	80.14 192	82.93 171	88.31 163	71.73 130	79.53 234	87.17 192	65.43 231	79.59 241	82.73 285	76.94 130	90.14 199	73.22 156	88.33 245	86.90 234

xiu_mvs_v1_base_debi		80.84 187	80.14 192	82.93 171	88.31 163	71.73 130	79.53 234	87.17 192	65.43 231	79.59 241	82.73 285	76.94 130	90.14 199	73.22 156	88.33 245	86.90 234

MSDG		80.06 197	79.99 195	80.25 206	83.91 253	68.04 157	77.51 259	89.19 164	77.65 101	81.94 214	83.45 275	76.37 138	86.31 250	63.31 228	86.59 265	86.41 237

OpenMVS_ROB	70.19 17	77.77 209	77.46 207	78.71 224	84.39 244	61.15 229	81.18 217	82.52 232	62.45 254	83.34 200	87.37 226	66.20 224	88.66 226	64.69 219	85.02 280	86.32 238

TinyColmap		81.25 182	82.34 167	77.99 235	85.33 232	60.68 235	82.32 189	88.33 174	71.26 185	86.97 145	92.22 125	77.10 127	86.98 241	62.37 230	95.17 128	86.31 239

CHOSEN 1792x2688		72.45 254	70.56 264	78.13 232	90.02 137	63.08 195	68.72 303	83.16 228	42.99 333	75.92 265	85.46 248	57.22 265	85.18 262	49.87 298	81.67 300	86.14 240

YYNet1		70.06 272	70.44 265	68.90 290	73.76 325	53.42 281	58.99 327	67.20 317	58.42 272	87.10 141	85.39 251	59.82 250	67.32 318	59.79 247	83.50 290	85.96 241

EPNet_dtu		72.87 251	71.33 262	77.49 244	77.72 299	60.55 236	82.35 188	75.79 265	66.49 221	58.39 336	81.06 299	53.68 277	85.98 253	53.55 283	92.97 187	85.95 242
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MDA-MVSNet_test_wron		70.05 273	70.44 265	68.88 291	73.84 324	53.47 279	58.93 328	67.28 316	58.43 271	87.09 142	85.40 250	59.80 251	67.25 319	59.66 249	83.54 289	85.92 243

XXY-MVS		74.44 244	76.19 221	69.21 289	84.61 239	52.43 288	71.70 295	77.18 258	60.73 266	80.60 231	90.96 161	75.44 141	69.35 313	56.13 268	88.33 245	85.86 244

tpmp4_e23		69.43 276	67.33 283	75.72 260	78.53 294	52.75 284	82.13 198	74.91 270	49.23 321	66.37 312	84.17 268	41.28 326	88.67 225	49.73 299	79.63 307	85.75 245

原ACMM1				84.60 127	92.81 70	74.01 108		91.50 96	62.59 251	82.73 208	90.67 171	76.53 137	94.25 61	69.24 186	95.69 115	85.55 246

pmmvs4		74.92 239	72.98 248	80.73 203	84.95 235	71.71 133	76.23 270	77.59 256	52.83 297	77.73 253	86.38 234	56.35 266	84.97 263	57.72 262	87.05 261	85.51 247

MAR-MVS		80.24 194	78.74 201	84.73 124	86.87 211	78.18 76	85.75 112	87.81 184	65.67 230	77.84 250	78.50 309	73.79 168	90.53 189	61.59 238	90.87 219	85.49 248
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
USDC		76.63 222	76.73 213	76.34 256	83.46 256	57.20 256	80.02 229	88.04 180	52.14 303	83.65 197	91.25 144	63.24 236	86.65 246	54.66 279	94.11 155	85.17 249

HY-MVS	64.64 18	73.03 250	72.47 254	74.71 265	83.36 257	54.19 274	82.14 197	81.96 236	56.76 281	69.57 302	86.21 240	60.03 247	84.83 266	49.58 300	82.65 296	85.11 250

MVP-Stereo		75.81 231	73.51 243	82.71 174	89.35 141	73.62 109	80.06 227	85.20 216	60.30 267	73.96 280	87.94 217	57.89 260	89.45 208	52.02 288	74.87 321	85.06 251
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
IB-MVS	62.13 19	71.64 260	68.97 274	79.66 215	80.80 279	62.26 217	73.94 286	76.90 260	63.27 246	68.63 305	76.79 315	33.83 335	91.84 153	59.28 251	87.26 259	84.88 252
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
pmmvs5		70.73 266	70.07 269	72.72 276	77.03 304	52.73 285	74.14 284	75.65 268	50.36 317	72.17 290	85.37 252	55.42 272	80.67 286	52.86 286	87.59 257	84.77 253

MSLP-MVS++		85.00 114	86.03 99	81.90 185	91.84 95	71.56 135	86.75 98	93.02 55	75.95 126	87.12 140	89.39 194	77.98 116	89.40 210	77.46 124	94.78 142	84.75 254

无先验							82.81 175	85.62 212	58.09 273				91.41 166	67.95 200		84.48 255

PAPM		71.77 259	70.06 270	76.92 248	86.39 214	53.97 275	76.62 265	86.62 202	53.44 294	63.97 323	84.73 262	57.79 261	92.34 142	39.65 324	81.33 303	84.45 256

PVSNet_Blended		76.49 225	75.40 227	79.76 211	84.43 241	63.41 187	75.14 278	90.44 131	57.36 276	75.43 269	78.30 310	69.11 214	91.44 164	60.68 243	87.70 256	84.42 257

LP		69.42 277	68.30 279	72.77 275	71.48 336	56.84 260	73.66 289	74.84 271	63.52 243	70.95 298	83.35 277	49.55 287	77.15 295	57.13 264	70.21 329	84.33 258

thres200		72.34 256	71.55 260	74.70 266	83.48 255	51.60 296	75.02 279	73.71 280	70.14 195	78.56 248	80.57 300	46.20 295	88.20 230	46.99 311	89.29 235	84.32 259

AdaColmap		83.66 151	83.69 149	83.57 158	90.05 135	72.26 122	86.29 108	90.00 151	78.19 96	81.65 220	87.16 227	83.40 64	94.24 62	61.69 235	94.76 145	84.21 260

EU-MVSNet		75.12 236	74.43 237	77.18 246	83.11 261	59.48 243	85.71 114	82.43 233	39.76 336	85.64 165	88.76 201	44.71 318	87.88 232	73.86 150	85.88 271	84.16 261

CR-MVSNet		74.00 245	73.04 247	76.85 250	79.58 282	62.64 203	82.58 181	76.90 260	50.50 316	75.72 267	92.38 118	48.07 290	84.07 270	68.72 194	82.91 294	83.85 262

RPMNet		76.06 228	75.79 223	76.85 250	79.58 282	62.64 203	82.58 181	71.75 298	74.80 139	75.72 267	92.59 113	48.69 288	84.07 270	73.48 154	82.91 294	83.85 262

MDTV_nov1_ep13_2view						27.60 340	70.76 297		46.47 326	61.27 326		45.20 310		49.18 301		83.75 264

旧先验1					91.97 90	71.77 129		81.78 239			91.84 130	73.92 166			93.65 169	83.61 265

N_pmnet		70.20 269	68.80 276	74.38 267	80.91 276	84.81 35	59.12 326	76.45 264	55.06 286	75.31 272	82.36 288	55.74 269	54.82 338	47.02 310	87.24 260	83.52 266

ADS-MVSNet2		65.87 292	63.64 297	72.55 278	73.16 329	56.92 258	67.10 310	74.81 272	49.74 318	66.04 314	82.97 280	46.71 292	77.26 293	42.29 319	69.96 331	83.46 267

ADS-MVSNet		61.90 299	62.19 301	61.03 316	73.16 329	36.42 335	67.10 310	61.75 329	49.74 318	66.04 314	82.97 280	46.71 292	63.21 332	42.29 319	69.96 331	83.46 267

CostFormer		69.98 274	68.68 277	73.87 268	77.14 302	50.72 308	79.26 240	74.51 275	51.94 305	70.97 297	84.75 261	45.16 316	87.49 235	55.16 276	79.23 311	83.40 269

PS-MVSNAJ		77.04 215	76.53 218	78.56 226	87.09 207	61.40 225	75.26 277	87.13 195	61.25 262	74.38 279	77.22 314	76.94 130	90.94 175	64.63 220	84.83 283	83.35 270

xiu_mvs_v2_base		77.19 213	76.75 212	78.52 227	87.01 208	61.30 227	75.55 276	87.12 197	61.24 263	74.45 277	78.79 308	77.20 124	90.93 176	64.62 221	84.80 284	83.32 271

PatchmatchNet		69.71 275	68.83 275	72.33 279	77.66 300	53.60 278	79.29 239	69.99 308	57.66 275	72.53 287	82.93 282	46.45 294	80.08 290	60.91 242	72.09 326	83.31 272
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
Anonymous20231206		71.38 263	71.88 257	69.88 284	86.31 219	54.37 273	70.39 299	74.62 273	52.57 299	76.73 257	88.76 201	59.94 248	72.06 306	44.35 317	93.23 182	83.23 273

tpm		67.95 282	68.08 281	67.55 297	78.74 292	43.53 327	75.60 274	67.10 320	54.92 287	72.23 289	88.10 214	42.87 323	75.97 298	52.21 287	80.95 306	83.15 274

PMVS	80.48 6	90.08 33	90.66 36	88.34 64	96.71 2	92.97 2	90.31 36	89.57 160	88.51 15	90.11 80	95.12 46	90.98 8	88.92 218	77.55 123	97.07 65	83.13 275
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
tpm2		68.45 281	66.83 285	73.30 271	78.93 290	48.50 313	79.76 231	71.76 297	47.50 323	69.92 301	83.60 272	42.07 325	88.40 227	48.44 305	79.51 308	83.01 276

TR-MVS		76.77 221	75.79 223	79.72 212	86.10 226	65.79 170	77.14 261	83.02 229	65.20 235	81.40 223	82.10 290	66.30 223	90.73 184	55.57 272	85.27 276	82.65 277

1314		73.22 248	72.56 253	75.20 262	80.41 281	57.84 251	81.64 208	85.36 214	51.68 306	73.10 285	76.65 316	61.45 240	85.19 261	63.54 225	79.21 312	82.59 278

WTY-MVS		67.91 283	68.35 278	66.58 300	80.82 278	48.12 315	65.96 313	72.60 289	53.67 293	71.20 295	81.68 295	58.97 255	69.06 315	48.57 303	81.67 300	82.55 279

MIMVSNet		71.09 264	71.59 259	69.57 288	87.23 200	50.07 311	78.91 245	71.83 296	60.20 268	71.26 294	91.76 134	55.08 274	76.09 297	41.06 322	87.02 262	82.54 280

BH-untuned		80.96 185	80.99 182	80.84 201	88.55 157	68.23 155	80.33 226	88.46 171	72.79 166	86.55 150	86.76 231	74.72 155	91.77 156	61.79 234	88.99 239	82.52 281

API-MVS		82.28 169	82.61 162	81.30 195	86.29 220	69.79 142	88.71 67	87.67 185	78.42 93	82.15 212	84.15 269	77.98 116	91.59 160	65.39 216	92.75 190	82.51 282

Gipuma		84.44 126	86.33 92	78.78 222	84.20 248	73.57 110	89.55 51	90.44 131	84.24 29	84.38 186	94.89 51	76.35 139	80.40 287	76.14 134	96.80 74	82.36 283
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
testmv		70.47 268	70.70 263	69.77 286	86.22 223	53.89 277	67.32 309	71.91 295	63.32 244	78.16 249	89.47 193	56.12 268	73.10 304	36.43 330	87.33 258	82.33 284

DWT-MVSNet_test		66.43 288	64.37 293	72.63 277	74.86 322	50.86 303	76.52 266	72.74 288	54.06 291	65.50 316	68.30 332	32.13 337	84.84 265	61.63 237	73.59 322	82.19 285

PatchT		70.52 267	72.76 249	63.79 308	79.38 285	33.53 337	77.63 257	65.37 323	73.61 150	71.77 291	92.79 111	44.38 319	75.65 300	64.53 222	85.37 275	82.18 286

tpmvs		70.16 270	69.56 272	71.96 281	74.71 323	48.13 314	79.63 232	75.45 269	65.02 238	70.26 299	81.88 292	45.34 309	85.68 257	58.34 258	75.39 320	82.08 287

wuykxyi23d		88.46 61	88.80 59	87.44 79	90.96 118	93.03 1	85.85 111	81.96 236	74.58 141	98.58 2	97.29 5	87.73 31	87.31 237	82.84 67	99.41 1	81.99 288

1121		80.86 186	79.81 196	84.02 142	93.93 45	78.70 74	81.64 208	80.18 247	55.43 285	83.67 195	91.15 150	71.29 207	91.41 166	67.95 200	93.06 184	81.96 289

新几何1				82.95 170	93.96 44	78.56 75		80.24 246	55.45 284	83.93 193	91.08 155	71.19 208	88.33 228	65.84 214	93.07 183	81.95 290

Patchmatch-test1		72.75 252	72.61 251	73.19 272	81.62 269	55.86 264	78.89 246	71.37 300	61.73 258	74.93 274	82.15 289	60.46 244	81.80 281	59.68 248	82.63 298	81.92 291

PatchFormer-LS_test		67.91 283	66.49 289	72.17 280	75.29 318	51.85 294	75.68 272	73.62 282	57.23 278	68.64 303	68.13 333	42.19 324	82.76 278	64.06 223	73.51 323	81.89 292

Patchmatch-test		65.91 291	67.38 282	61.48 314	75.51 315	43.21 328	68.84 302	63.79 325	62.48 253	72.80 286	83.42 276	44.89 317	59.52 335	48.27 306	86.45 266	81.70 293

1111		61.71 300	63.77 296	55.55 323	78.05 296	25.74 341	60.62 320	67.52 313	66.09 224	74.68 275	86.50 232	16.00 347	59.22 336	38.79 325	85.65 272	81.70 293

UnsupCasMVSNet_bld		69.21 279	69.68 271	67.82 296	79.42 284	51.15 299	67.82 308	75.79 265	54.15 290	77.47 254	85.36 253	59.26 254	70.64 309	48.46 304	79.35 310	81.66 295

PVSNet	58.17 21	66.41 289	65.63 291	68.75 292	81.96 266	49.88 312	62.19 319	72.51 291	51.03 311	68.04 307	75.34 321	50.84 282	74.77 301	45.82 315	82.96 292	81.60 296

Patchmatch-RL test		74.48 242	73.68 241	76.89 249	84.83 237	66.54 166	72.29 293	69.16 312	57.70 274	86.76 146	86.33 237	45.79 302	82.59 279	69.63 183	90.65 226	81.54 297

test0.0.03 1		64.66 295	64.36 294	65.57 303	75.03 321	46.89 317	64.69 315	61.58 331	62.43 255	71.18 296	77.54 311	43.41 320	68.47 316	40.75 323	82.65 296	81.35 298

test-LLR		67.21 285	66.74 286	68.63 293	76.45 308	55.21 269	67.89 305	67.14 318	62.43 255	65.08 319	72.39 325	43.41 320	69.37 311	61.00 240	84.89 281	81.31 299

test-mter		65.00 294	63.79 295	68.63 293	76.45 308	55.21 269	67.89 305	67.14 318	50.98 312	65.08 319	72.39 325	28.27 342	69.37 311	61.00 240	84.89 281	81.31 299

test222					93.31 55	76.54 92	79.38 238	77.79 255	52.59 298	82.36 209	90.84 165	66.83 222			91.69 203	81.25 301

sss		66.92 286	67.26 284	65.90 301	77.23 301	51.10 301	64.79 314	71.72 299	52.12 304	70.13 300	80.18 302	57.96 259	65.36 328	50.21 295	81.01 305	81.25 301

tpm cat1		66.76 287	65.21 292	71.42 282	77.09 303	50.62 309	78.01 252	73.68 281	44.89 329	68.64 303	79.00 307	45.51 306	82.42 280	49.91 297	70.15 330	81.23 303

CVMVSNet		72.62 253	71.41 261	76.28 257	83.25 258	60.34 237	83.50 158	79.02 252	37.77 337	76.33 260	85.10 254	49.60 286	87.41 236	70.54 178	77.54 317	81.08 304

tpmrst		66.28 290	66.69 287	65.05 306	72.82 332	39.33 332	78.20 251	70.69 306	53.16 296	67.88 308	80.36 301	48.18 289	74.75 302	58.13 260	70.79 328	81.08 304

testdata				79.54 217	92.87 66	72.34 120		80.14 248	59.91 269	85.47 169	91.75 135	67.96 218	85.24 260	68.57 196	92.18 201	81.06 306

PM-MVS		80.20 195	79.00 199	83.78 149	88.17 167	86.66 13	81.31 213	66.81 321	69.64 198	88.33 127	90.19 181	64.58 229	83.63 275	71.99 169	90.03 230	81.06 306

no-one		71.52 262	70.43 267	74.81 264	78.45 295	63.41 187	57.73 329	77.03 259	51.46 309	77.17 256	90.33 178	54.96 275	80.35 288	47.41 308	99.29 2	80.68 308

EPMVS		62.47 296	62.63 300	62.01 310	70.63 337	38.74 333	74.76 280	52.86 340	53.91 292	67.71 310	80.01 303	39.40 330	66.60 323	55.54 273	68.81 335	80.68 308

JIA-IIPM		69.41 278	66.64 288	77.70 239	73.19 328	71.24 136	75.67 273	65.56 322	70.42 191	65.18 318	92.97 104	33.64 336	83.06 276	53.52 284	69.61 333	78.79 310

BH-w/o		76.57 223	76.07 222	78.10 233	86.88 210	65.92 169	77.63 257	86.33 204	65.69 229	80.89 228	79.95 304	68.97 216	90.74 183	53.01 285	85.25 277	77.62 311

TESTMET0.1,1		61.29 303	60.32 307	64.19 307	72.06 333	51.30 297	67.89 305	62.09 327	45.27 328	60.65 328	69.01 328	27.93 343	64.74 329	56.31 267	81.65 302	76.53 312

testus		62.33 298	63.03 298	60.20 318	78.78 291	40.74 330	59.14 324	69.80 309	49.26 320	71.41 293	74.72 323	52.33 280	63.52 330	29.84 337	82.01 299	76.36 313

gg-mvs-nofinetune		68.96 280	69.11 273	68.52 295	76.12 310	45.32 320	83.59 151	55.88 338	86.68 20	64.62 322	97.01 7	30.36 339	83.97 273	44.78 316	82.94 293	76.26 314

dp		60.70 307	60.29 308	61.92 312	72.04 334	38.67 334	70.83 296	64.08 324	51.28 310	60.75 327	77.28 313	36.59 333	71.58 308	47.41 308	62.34 337	75.52 315

MS-PatchMatch		70.93 265	70.22 268	73.06 274	81.85 268	62.50 209	73.82 288	77.90 254	52.44 300	75.92 265	81.27 297	55.67 270	81.75 282	55.37 274	77.70 315	74.94 316

MVS		73.21 249	72.59 252	75.06 263	80.97 275	60.81 234	81.64 208	85.92 209	46.03 327	71.68 292	77.54 311	68.47 217	89.77 204	55.70 271	85.39 274	74.60 317

test2356		56.69 310	55.15 314	61.32 315	73.20 327	44.11 325	54.95 331	62.52 326	48.75 322	62.45 325	68.42 330	21.10 346	65.67 327	26.86 339	78.08 314	74.19 318

test1235678		65.57 293	65.73 290	65.06 305	82.84 263	50.90 302	62.90 317	69.26 310	57.17 279	72.36 288	83.04 278	46.02 297	70.10 310	32.79 335	85.24 278	74.19 318

pmmvs3		62.47 296	60.02 309	69.80 285	71.58 335	64.00 181	70.52 298	58.44 335	39.77 335	66.05 313	75.84 318	27.10 344	72.28 305	46.15 313	84.77 285	73.11 320

PMMVS2		55.64 313	59.27 310	44.74 328	64.30 342	12.32 345	40.60 337	49.79 343	53.19 295	65.06 321	84.81 260	53.60 278	49.76 340	32.68 336	89.41 234	72.15 321

PatchMatch-RL		74.48 242	73.22 245	78.27 231	87.70 186	85.26 30	75.92 271	70.09 307	64.34 241	76.09 264	81.25 298	65.87 227	78.07 292	53.86 282	83.82 288	71.48 322

GG-mvs-BLEND				67.16 298	73.36 326	46.54 319	84.15 134	55.04 339		58.64 335	61.95 338	29.93 340	83.87 274	38.71 328	76.92 318	71.07 323

MVE	40.22 23	51.82 316	50.47 318	55.87 321	62.66 343	51.91 291	31.61 339	39.28 345	40.65 334	50.76 340	74.98 322	56.24 267	44.67 342	33.94 334	64.11 336	71.04 324
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
new_pmnet		55.69 312	57.66 311	49.76 325	75.47 316	30.59 338	59.56 322	51.45 342	43.62 332	62.49 324	75.48 319	40.96 328	49.15 341	37.39 329	72.52 324	69.55 325

DSMNet-mixed		60.98 306	61.61 303	59.09 320	72.88 331	45.05 323	74.70 281	46.61 344	26.20 339	65.34 317	90.32 179	55.46 271	63.12 333	41.72 321	81.30 304	69.09 326

CHOSEN 280x420		59.08 308	56.52 313	66.76 299	76.51 306	64.39 178	49.62 336	59.00 333	43.86 331	55.66 339	68.41 331	35.55 334	68.21 317	43.25 318	76.78 319	67.69 327

test12356		54.91 314	57.14 312	48.22 327	75.83 312	17.47 343	52.31 335	69.20 311	51.66 307	60.11 329	75.40 320	29.77 341	62.62 334	27.64 338	72.37 325	64.59 328

EMVS		61.10 305	60.81 305	61.99 311	65.96 340	55.86 264	53.10 334	58.97 334	67.06 216	56.89 338	63.33 336	40.98 327	67.03 320	54.79 278	86.18 270	63.08 329

E-PMN		61.59 302	61.62 302	61.49 313	66.81 338	55.40 267	53.77 333	60.34 332	66.80 220	58.90 334	65.50 335	40.48 329	66.12 325	55.72 270	86.25 269	62.95 330

PMMVS		61.65 301	60.38 306	65.47 304	65.40 341	69.26 148	63.97 316	61.73 330	36.80 338	60.11 329	68.43 329	59.42 252	66.35 324	48.97 302	78.57 313	60.81 331

wuyk23d		75.13 235	79.30 197	62.63 309	75.56 313	75.18 102	80.89 221	73.10 287	75.06 138	94.76 15	95.32 40	87.73 31	52.85 339	34.16 333	97.11 64	59.85 332

PVSNet_0	51.08 22	56.10 311	54.97 315	59.48 319	75.12 320	53.28 282	55.16 330	61.89 328	44.30 330	59.16 332	62.48 337	54.22 276	65.91 326	35.40 332	47.01 338	59.25 333

FPMVS		72.29 257	72.00 256	73.14 273	88.63 156	85.00 32	74.65 282	67.39 315	71.94 179	77.80 252	87.66 222	50.48 284	75.83 299	49.95 296	79.51 308	58.58 334

MVS-HIRNet		61.16 304	62.92 299	55.87 321	79.09 288	35.34 336	71.83 294	57.98 337	46.56 325	59.05 333	91.14 151	49.95 285	76.43 296	38.74 327	71.92 327	55.84 335

PNet_i23d		52.13 315	51.24 317	54.79 324	75.56 313	45.26 321	54.54 332	52.55 341	66.95 217	57.19 337	65.82 334	13.15 349	63.40 331	36.39 331	39.04 340	55.71 336

testpf		58.55 309	61.58 304	49.48 326	66.03 339	40.05 331	74.40 283	58.07 336	64.72 240	59.36 331	72.67 324	22.76 345	66.92 321	67.07 203	69.15 334	41.46 337

DeepMVS_CX				24.13 331	32.95 344	29.49 339		21.63 348	12.07 340	37.95 341	45.07 339	30.84 338	19.21 343	17.94 341	33.06 341	23.69 338

tmp_tt		20.25 320	24.50 321	7.49 332	4.47 345	8.70 346	34.17 338	25.16 347	1.00 341	32.43 342	18.49 340	39.37 331	9.21 344	21.64 340	43.75 339	4.57 339

test123		6.27 323	8.08 324	0.84 333	1.11 347	0.57 347	62.90 317	0.82 349	0.54 342	1.07 344	2.75 345	1.26 350	0.30 345	1.04 342	1.26 344	1.66 340

.test1245		48.02 317	54.41 316	28.84 330	78.05 296	25.74 341	60.62 320	67.52 313	66.09 224	74.68 275	86.50 232	16.00 347	59.22 336	38.79 325	1.47 342	1.55 341

testmvs		5.91 324	7.65 325	0.72 334	1.20 346	0.37 348	59.14 324	0.67 350	0.49 343	1.11 343	2.76 344	0.94 351	0.24 346	1.02 343	1.47 342	1.55 341

cdsmvs_eth3d_5k		20.81 319	27.75 320	0.00 335	0.00 348	0.00 349	0.00 340	85.44 213	0.00 344	0.00 345	82.82 283	81.46 90	0.00 347	0.00 344	0.00 345	0.00 343

pcd_1.5k_mvsjas		6.41 322	8.55 323	0.00 335	0.00 348	0.00 349	0.00 340	0.00 351	0.00 344	0.00 345	0.00 346	76.94 130	0.00 347	0.00 344	0.00 345	0.00 343

sosnet-low-res		0.00 325	0.00 326	0.00 335	0.00 348	0.00 349	0.00 340	0.00 351	0.00 344	0.00 345	0.00 346	0.00 352	0.00 347	0.00 344	0.00 345	0.00 343

sosnet		0.00 325	0.00 326	0.00 335	0.00 348	0.00 349	0.00 340	0.00 351	0.00 344	0.00 345	0.00 346	0.00 352	0.00 347	0.00 344	0.00 345	0.00 343

uncertanet		0.00 325	0.00 326	0.00 335	0.00 348	0.00 349	0.00 340	0.00 351	0.00 344	0.00 345	0.00 346	0.00 352	0.00 347	0.00 344	0.00 345	0.00 343

Regformer		0.00 325	0.00 326	0.00 335	0.00 348	0.00 349	0.00 340	0.00 351	0.00 344	0.00 345	0.00 346	0.00 352	0.00 347	0.00 344	0.00 345	0.00 343

ab-mvs-re		6.65 321	8.87 322	0.00 335	0.00 348	0.00 349	0.00 340	0.00 351	0.00 344	0.00 345	79.80 305	0.00 352	0.00 347	0.00 344	0.00 345	0.00 343

uanet		0.00 325	0.00 326	0.00 335	0.00 348	0.00 349	0.00 340	0.00 351	0.00 344	0.00 345	0.00 346	0.00 352	0.00 347	0.00 344	0.00 345	0.00 343

ESAPD								93.79 28

sam_mvs1												46.11 296

sam_mvs												45.92 301

MTGPA								91.81 89

test_post1							78.85 247				3.13 342	45.19 311	80.13 289	58.11 261

test_post											3.10 343	45.43 307	77.22 294

patchmatchnet-post											81.71 294	45.93 300	87.01 239

MTMP								33.14 346

gm-plane-assit					75.42 317	44.97 324			52.17 301		72.36 327		87.90 231	54.10 281

TEST9					92.34 80	79.70 66	83.94 139	90.32 135	65.41 234	84.49 184	90.97 159	82.03 81	93.63 86

test_8					92.09 87	78.87 72	83.82 144	90.31 137	65.79 227	84.36 187	90.96 161	81.93 83	93.44 107

agg_prior					91.58 101	77.69 79		90.30 139		84.32 188			93.18 118

test_prior4						78.97 71	84.59 127

test_prior2							83.37 161		75.43 134	84.58 182	91.57 137	81.92 85		79.54 106	96.97 67

旧先验2							81.73 206		56.88 280	86.54 155			84.90 264	72.81 162

新几何2							81.72 207

原ACMM2							82.26 193

testdata2													86.43 249	63.52 226

segment_acmp												81.94 82

testdata1							79.62 233		73.95 148

plane_prior7					93.45 51	77.31 85

plane_prior6					92.61 71	76.54 92						74.84 151

plane_prior4											92.95 105

plane_prior3						76.85 90			77.79 99	86.55 150

plane_prior2							89.45 56		79.44 77

plane_prior1					92.83 69

plane_prior						76.42 95	87.15 89		75.94 127						95.03 132

n2								0.00 351

nn								0.00 351

door-mid								74.45 276

test11								91.46 102

door								72.57 290

HQP5-MVS						70.66 139

HQP-NCC					91.19 111		84.77 122		73.30 157	80.55 234

ACMP_Plane					91.19 111		84.77 122		73.30 157	80.55 234

BP-MVS														77.30 127

HQP3-MVS								92.68 66							94.47 151

HQP2-MVS												72.10 199

NP-MVS					91.95 91	74.55 105					90.17 183

MDTV_nov1_ep13			68.29 280		78.03 298	43.87 326	74.12 285	72.22 292	52.17 301	67.02 311	85.54 244	45.36 308	80.85 285	55.73 269	84.42 286

ACMMP++_ref															95.74 114

ACMMP++															97.35 58

Test By Simon												79.09 108

High-resolution multi-view benchmark