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	78.67 247	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	75.42 134	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	69.87 195	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	71.54 181	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	86.80 242	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	87.74 232	76.54 133	88.74 241	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	74.04 144	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	87.13 201	61.40 225	82.71 180	89.71 157	72.19 174	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	70.73 187	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	69.08 201	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	83.87 252	72.52 118	83.82 144	85.15 218	80.27 68	88.75 117	85.45 247	79.95 104	91.90 151	81.92 76	90.80 219	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	67.94 210	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	67.94 210	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	67.82 213	89.80 93	90.49 175	73.28 181	93.51 104	81.88 77	94.89 136	96.04 47

pcd1.5k->3k		38.83 316	41.11 317	32.01 327	93.13 60	0.00 347	0.00 338	91.38 111	0.00 342	0.00 343	0.00 344	89.24 16	0.00 345	0.00 342	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	70.32 191	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	84.01 249	72.76 115	83.91 142	85.18 217	80.44 64	88.75 117	85.49 243	80.08 102	91.92 150	82.02 74	90.85 218	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	71.10 185	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	75.65 259	81.24 270	45.26 319	79.94 228	92.91 58	83.83 33	91.33 68	96.88 10	80.25 101	85.92 252	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	71.90 178	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	71.90 178	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	71.89 180	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	83.25 256	63.66 184	83.50 158	85.07 219	76.06 123	86.55 150	85.10 252	73.41 177	90.25 193	78.15 119	90.67 222	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	72.33 171	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	72.33 171	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	72.33 171	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	83.16 258	63.33 190	81.31 213	90.23 146	69.51 197	90.91 74	90.81 166	74.16 161	92.29 144	80.06 99	90.22 227	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	70.00 194	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	69.27 198	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	86.14 250	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	84.27 243	77.57 81	84.07 135	88.00 181	82.82 42	89.84 92	85.48 244	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	85.59 227	59.66 241	81.47 211	86.02 208	72.85 163	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	84.27 243	73.43 111	84.07 135	85.26 215	80.77 63	88.62 120	85.48 244	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	67.85 212	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	86.74 210	63.97 182	84.56 128	90.31 137	66.22 221	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	86.88 240	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	75.52 131	87.85 131	95.26 42	81.25 93	85.65 256	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	87.20 236	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	16.05 339	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	87.13 201	91.15 3	87.70 79	88.42 172	74.57 140	83.56 198	85.65 241	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	90.75 220	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		70.91 303		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	84.18 247	79.20 69	83.52 155	89.33 163	83.33 35	89.92 90	85.07 254	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	86.38 213	61.05 231	86.83 94	88.27 176	72.43 167	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	86.38 213	61.05 231	86.83 94	88.27 176	72.43 167	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	65.91 224	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	84.18 247	76.90 89	83.52 155	87.94 183	82.18 50	89.19 110	85.07 254	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	85.83 254	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	77.93 252	92.52 71	68.33 205	85.07 170	81.54 294	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										80.56 231			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	73.30 155	80.55 232	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	75.94 257	92.46 76	47.98 314	76.70 262	81.67 240	73.45 150	84.87 174	92.82 108	74.66 156	86.51 245	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	73.53 149	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	69.17 199	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	88.31 227	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	51.29 296	83.28 163	71.97 292	74.04 144	82.23 208	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	80.83 221	82.85 231	76.81 117	85.90 162	94.14 79	74.58 158	86.51 245	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	75.43 132	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	73.15 160	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	73.27 158	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	50.77 302	81.92 200	71.35 299	77.38 105	84.62 178	88.40 207	45.18 310	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	50.77 302	81.92 200	71.35 299	77.38 105	84.62 178	88.40 207	45.18 310	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	50.77 302	81.92 200	71.35 299	77.38 105	84.62 178	88.40 207	45.18 310	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	50.77 302	81.92 200	71.35 299	77.38 105	84.62 178	88.40 207	45.18 310	89.26 211	58.58 253	93.49 170	92.66 136

thres600view7		75.97 229	75.35 229	77.85 238	87.01 206	51.84 293	80.45 223	73.26 284	75.20 135	83.10 202	86.31 237	45.54 303	89.05 215	55.03 277	92.24 198	92.66 136

thres400		75.14 232	74.23 236	77.86 237	86.24 219	52.12 289	79.24 239	73.87 277	73.34 153	81.82 215	84.60 262	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	73.44 151	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	75.27 317	61.08 230	77.49 258	85.07 219	60.78 263	86.55 150	88.68 203	43.14 320	90.25 193	73.69 151	90.67 222	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	82.62 262	57.75 253	82.54 184	91.96 85	71.16 184	82.89 204	92.52 117	77.41 123	90.50 190	80.04 100	87.84 252	92.40 147

diffmvs		79.20 200	79.04 198	79.69 213	78.64 291	58.90 246	81.79 204	87.61 186	65.07 235	73.65 281	89.80 187	73.10 187	87.79 231	75.02 141	86.63 262	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	77.39 253	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		82.76 205		79.20 107	94.80 49		95.32 122	92.27 153

FMVSNet2		81.31 179	81.61 175	80.41 205	86.38 213	58.75 249	83.93 141	86.58 203	72.43 167	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	86.17 223	72.21 124	83.76 148	91.43 105	77.24 112	74.39 276	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	73.19 159	80.18 237	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	87.22 199	65.61 171	86.55 105	92.40 73	78.64 90	81.34 223	84.18 265	83.65 61	92.93 130	74.22 144	87.87 251	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	87.13 201	89.54 5	85.05 121	88.42 172	74.57 140	80.60 229	82.98 277	78.49 112	93.98 73	72.04 167	89.77 230	92.00 159

new-patchmatchnet		70.10 269	73.37 242	60.29 315	81.23 271	16.95 342	59.54 321	74.62 273	62.93 246	80.97 224	87.93 218	62.83 237	71.90 305	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	70.25 192	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	61.82 255	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	70.56 188	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	82.89 260	56.89 259	81.76 205	85.77 210	69.04 202	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	79.03 287	64.59 175	66.58 310	75.67 267	73.15 160	88.86 114	88.99 199	66.94 221	81.23 282	64.71 218	88.22 248	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	80.87 227	87.92 219	73.49 176	92.42 141	70.07 180	88.40 242	91.60 168

PCF-MVS	74.62 15	82.15 171	80.92 184	85.84 106	89.43 140	72.30 121	80.53 222	91.82 88	57.36 274	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	76.75 303	73.28 112	87.18 88	77.45 257	76.24 122	68.14 304	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	78.37 248	89.63 158	68.01 207	81.87 213	82.08 289	82.31 76	92.65 138	67.10 202	88.30 247	91.51 171

mvs_anonymous		78.13 205	78.76 200	76.23 256	79.24 285	50.31 308	78.69 246	84.82 224	61.60 259	83.09 203	92.82 108	73.89 167	87.01 237	68.33 197	86.41 265	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

agg_prior1		85.72 104	85.20 111	87.28 81	91.58 101	77.69 79	83.69 150	90.30 139	66.29 220	84.32 188	91.07 156	82.13 78	93.18 118	81.02 83	96.36 86	90.98 174

VNet		79.31 199	80.27 190	76.44 252	87.92 174	53.95 276	75.58 273	84.35 226	74.39 142	82.23 208	90.72 168	72.84 190	84.39 267	60.38 245	93.98 159	90.97 175

Fast-Effi-MVS+-dtu		82.54 166	81.41 177	85.90 104	85.60 226	76.53 94	83.07 169	89.62 159	73.02 162	79.11 244	83.51 271	80.74 97	90.24 195	68.76 192	89.29 233	90.94 176

Patchmtry		76.56 224	77.46 207	73.83 267	79.37 284	46.60 316	82.41 186	76.90 260	73.81 147	85.56 167	92.38 118	48.07 290	83.98 270	63.36 227	95.31 124	90.92 177

Test4		81.31 179	81.13 181	81.88 187	84.89 234	63.05 196	82.37 187	90.50 129	62.75 248	89.00 113	88.29 212	67.55 219	91.68 158	73.55 153	91.24 207	90.89 178

CANet_DTU		77.81 208	77.05 209	80.09 208	81.37 269	59.90 240	83.26 164	88.29 175	69.16 200	67.83 307	83.72 269	60.93 241	89.47 206	69.22 188	89.70 231	90.88 179

train_agg		85.98 100	85.28 110	88.07 68	92.34 80	79.70 66	83.94 139	90.32 135	65.79 225	84.49 184	90.97 159	81.93 83	93.63 86	81.21 80	96.54 80	90.88 179

agg_prior3		85.76 103	84.95 116	88.16 66	92.43 77	79.92 62	83.98 138	90.03 150	65.11 234	83.66 196	90.64 174	81.00 94	93.67 83	81.21 80	96.54 80	90.88 179

114514_t		83.10 161	82.54 164	84.77 122	92.90 65	69.10 152	86.65 102	90.62 127	54.66 286	81.46 220	90.81 166	76.98 129	94.38 58	72.62 163	96.18 93	90.82 182

LCM-MVSNet-Re		83.48 155	85.06 112	78.75 223	85.94 225	55.75 266	80.05 226	94.27 13	76.47 120	96.09 5	94.54 63	83.31 65	89.75 205	59.95 246	94.89 136	90.75 183

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	90.70 184

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	90.68 185

PAPR		78.84 201	78.10 204	81.07 199	85.17 231	60.22 238	82.21 194	90.57 128	62.51 250	75.32 269	84.61 261	74.99 148	92.30 143	59.48 250	88.04 249	90.68 185

test_normal		81.23 183	81.16 180	81.43 194	84.77 236	61.99 218	81.46 212	86.95 201	63.16 245	87.22 138	89.63 190	73.62 171	91.65 159	72.92 161	90.70 221	90.65 187

test9_res														80.83 87	96.45 85	90.57 188

UGNet		82.78 162	81.64 174	86.21 97	86.20 222	76.24 98	86.86 92	85.68 211	77.07 115	73.76 279	92.82 108	69.64 211	91.82 155	69.04 190	93.69 167	90.56 189
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	90.93 215	90.55 190

DELS-MVS		81.44 178	81.25 179	82.03 183	84.27 243	62.87 200	76.47 266	92.49 72	70.97 186	81.64 219	83.83 268	75.03 147	92.70 135	74.29 143	92.22 200	90.51 191
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	90.45 192
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	90.41 193

DI_MVS_plusplus_test		81.27 181	81.26 178	81.29 196	84.98 232	61.65 223	81.98 199	87.25 191	63.56 240	87.56 135	89.60 191	73.62 171	91.83 154	72.20 166	90.59 226	90.38 194

DP-MVS Recon		84.05 143	83.22 153	86.52 88	91.73 96	75.27 101	83.23 167	92.40 73	72.04 175	82.04 211	88.33 211	77.91 118	93.95 76	66.17 210	95.12 129	90.34 195

semantic-postprocess				84.34 136	83.93 250	69.66 144		81.09 243	72.43 167	86.47 156	90.19 181	57.56 262	93.15 122	77.45 125	86.39 266	90.22 196

agg_prior2														79.68 104	96.16 94	90.22 196

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	90.22 196

HyFIR lowres test		75.12 234	72.66 248	82.50 179	91.44 107	65.19 172	72.47 290	87.31 189	46.79 322	80.29 235	84.30 264	52.70 279	92.10 148	51.88 291	86.73 261	90.22 196

PVSNet_BlendedMVS		78.80 202	77.84 205	81.65 192	84.43 239	63.41 187	79.49 235	90.44 131	61.70 258	75.43 267	87.07 229	69.11 214	91.44 164	60.68 243	92.24 198	90.11 200

MVS_111021_HR		84.63 120	84.34 140	85.49 111	90.18 131	75.86 99	79.23 241	87.13 195	73.35 152	85.56 167	89.34 195	83.60 62	90.50 190	76.64 132	94.05 157	90.09 201

GA-MVS		75.83 230	74.61 231	79.48 218	81.87 265	59.25 245	73.42 288	82.88 230	68.68 204	79.75 238	81.80 291	50.62 283	89.46 207	66.85 205	85.64 271	89.72 202

MG-MVS		80.32 192	80.94 183	78.47 228	88.18 166	52.62 287	82.29 190	85.01 222	72.01 176	79.24 243	92.54 116	69.36 212	93.36 111	70.65 176	89.19 236	89.45 203

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	68.17 206	76.32 259	86.33 235	73.12 186	92.61 139	61.40 239	90.02 229	89.44 204
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	76.99 246	88.48 160	56.93 257	84.70 125	86.06 207	68.95 203	80.78 228	93.08 100	75.30 144	84.62 265	56.78 265	90.90 216	89.43 205

tfpn200view9		74.86 238	74.23 236	76.74 251	86.24 219	52.12 289	79.24 239	73.87 277	73.34 153	81.82 215	84.60 262	46.02 297	88.80 219	51.98 289	90.99 212	89.31 206

3Dnovator	80.37 7	84.80 118	84.71 122	85.06 115	86.36 216	74.71 104	88.77 66	90.00 151	75.65 130	84.96 171	93.17 99	74.06 162	91.19 169	78.28 117	91.09 208	89.29 207

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	81.73 281	66.84 206	92.29 196	89.11 208

CMPMVS	59.41 20	75.12 234	73.57 240	79.77 210	75.84 309	67.22 160	81.21 216	82.18 234	50.78 311	76.50 256	87.66 222	55.20 273	82.99 275	62.17 232	90.64 225	89.09 209
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MVSFormer		82.23 170	81.57 176	84.19 141	85.54 228	69.26 148	91.98 25	90.08 148	71.54 181	76.23 260	85.07 254	58.69 256	94.27 59	86.26 27	88.77 239	89.03 210

jason		77.42 211	75.75 225	82.43 181	87.10 204	69.27 147	77.99 251	81.94 238	51.47 306	77.84 248	85.07 254	60.32 245	89.00 216	70.74 175	89.27 235	89.03 210
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	74.73 138	85.66 164	86.06 239	72.56 197	92.69 136	75.44 138	95.21 126	89.01 212

QAPM		82.59 165	82.59 163	82.58 176	86.44 211	66.69 165	89.94 43	90.36 134	67.97 209	84.94 173	92.58 115	72.71 192	92.18 145	70.63 177	87.73 253	88.85 213

LF4IMVS		82.75 163	81.93 172	85.19 113	82.08 263	80.15 61	85.53 115	88.76 168	68.01 207	85.58 166	87.75 220	71.80 204	86.85 241	74.02 147	93.87 161	88.58 214

MVS_111021_LR		84.28 134	83.76 148	85.83 107	89.23 144	83.07 48	80.99 218	83.56 227	72.71 165	86.07 158	89.07 198	81.75 88	86.19 249	77.11 129	93.36 174	88.24 215

EG-PatchMatch MVS		84.08 142	84.11 142	83.98 144	92.22 85	72.61 117	82.20 196	87.02 199	72.63 166	88.86 114	91.02 157	78.52 111	91.11 171	73.41 155	91.09 208	88.21 216

lupinMVS		76.37 226	74.46 234	82.09 182	85.54 228	69.26 148	76.79 260	80.77 245	50.68 313	76.23 260	82.82 281	58.69 256	88.94 217	69.85 181	88.77 239	88.07 217

cascas		76.29 227	74.81 230	80.72 204	84.47 238	62.94 198	73.89 285	87.34 188	55.94 280	75.16 271	76.53 315	63.97 231	91.16 170	65.00 217	90.97 214	88.06 218

TAMVS		78.08 206	76.36 219	83.23 165	90.62 124	72.87 114	79.08 242	80.01 249	61.72 257	81.35 222	86.92 230	63.96 232	88.78 221	50.61 292	93.01 186	88.04 219

PVSNet_Blended_VisFu		81.55 177	80.49 188	84.70 125	91.58 101	73.24 113	84.21 132	91.67 92	62.86 247	80.94 225	87.16 227	67.27 220	92.87 133	69.82 182	88.94 238	87.99 220

FMVSNet5		72.10 256	71.69 256	73.32 268	81.57 268	53.02 283	76.77 261	78.37 253	63.31 243	76.37 257	91.85 129	36.68 330	78.98 289	47.87 305	92.45 194	87.95 221

CDS-MVSNet		77.32 212	75.40 227	83.06 168	89.00 148	72.48 119	77.90 253	82.17 235	60.81 262	78.94 245	83.49 272	59.30 253	88.76 222	54.64 280	92.37 195	87.93 222
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	80.86 220	79.67 250	55.68 281	84.69 177	90.31 180	60.91 242	85.42 257	62.20 231	91.59 204	87.88 223

test20.03		73.75 245	74.59 233	71.22 281	81.11 272	51.12 298	70.15 298	72.10 291	70.42 189	80.28 236	91.50 140	64.21 230	74.72 301	46.96 310	94.58 149	87.82 224

BH-RMVSNet		80.53 190	80.22 191	81.49 193	87.19 200	66.21 167	77.79 254	86.23 205	74.21 143	83.69 194	88.50 205	73.25 185	90.75 182	63.18 229	87.90 250	87.52 225

IterMVS		76.91 216	76.34 220	78.64 225	80.91 274	64.03 180	76.30 267	79.03 251	64.88 237	83.11 201	89.16 196	59.90 249	84.46 266	68.61 195	85.15 277	87.42 226
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	84.42 241	68.22 156	88.50 70	89.48 161	66.92 216	81.80 217	91.86 128	72.59 196	90.16 198	71.19 171	91.25 206	87.40 227

1112_ss		74.82 239	73.74 238	78.04 234	89.57 139	60.04 239	76.49 265	87.09 198	54.31 287	73.66 280	79.80 303	60.25 246	86.76 243	58.37 257	84.15 285	87.32 228

Test_1112_low_res		73.90 244	73.08 244	76.35 253	90.35 128	55.95 262	73.40 289	86.17 206	50.70 312	73.14 282	85.94 240	58.31 258	85.90 253	56.51 266	83.22 289	87.20 229

UnsupCasMVSNet_eth		71.63 259	72.30 253	69.62 285	76.47 305	52.70 286	70.03 299	80.97 244	59.18 268	79.36 242	88.21 213	60.50 243	69.12 312	58.33 259	77.62 314	87.04 230

testgi		72.36 253	74.61 231	65.59 300	80.56 278	42.82 327	68.29 302	73.35 283	66.87 217	81.84 214	89.93 185	72.08 201	66.92 319	46.05 312	92.54 193	87.01 231

xiu_mvs_v1_base_debu		80.84 187	80.14 192	82.93 171	88.31 163	71.73 130	79.53 232	87.17 192	65.43 229	79.59 239	82.73 283	76.94 130	90.14 199	73.22 156	88.33 243	86.90 232

xiu_mvs_v1_base		80.84 187	80.14 192	82.93 171	88.31 163	71.73 130	79.53 232	87.17 192	65.43 229	79.59 239	82.73 283	76.94 130	90.14 199	73.22 156	88.33 243	86.90 232

xiu_mvs_v1_base_debi		80.84 187	80.14 192	82.93 171	88.31 163	71.73 130	79.53 232	87.17 192	65.43 229	79.59 239	82.73 283	76.94 130	90.14 199	73.22 156	88.33 243	86.90 232

MSDG		80.06 197	79.99 195	80.25 206	83.91 251	68.04 157	77.51 257	89.19 164	77.65 101	81.94 212	83.45 273	76.37 138	86.31 248	63.31 228	86.59 263	86.41 235

OpenMVS_ROB	70.19 17	77.77 209	77.46 207	78.71 224	84.39 242	61.15 229	81.18 217	82.52 232	62.45 252	83.34 200	87.37 226	66.20 224	88.66 224	64.69 219	85.02 278	86.32 236

TinyColmap		81.25 182	82.34 167	77.99 235	85.33 230	60.68 235	82.32 189	88.33 174	71.26 183	86.97 145	92.22 125	77.10 127	86.98 239	62.37 230	95.17 128	86.31 237

CHOSEN 1792x2688		72.45 252	70.56 262	78.13 232	90.02 137	63.08 195	68.72 301	83.16 228	42.99 331	75.92 263	85.46 246	57.22 265	85.18 260	49.87 296	81.67 298	86.14 238

YYNet1		70.06 270	70.44 263	68.90 288	73.76 323	53.42 281	58.99 325	67.20 315	58.42 270	87.10 141	85.39 249	59.82 250	67.32 316	59.79 247	83.50 288	85.96 239

EPNet_dtu		72.87 249	71.33 260	77.49 244	77.72 297	60.55 236	82.35 188	75.79 265	66.49 219	58.39 334	81.06 297	53.68 277	85.98 251	53.55 283	92.97 187	85.95 240
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MDA-MVSNet_test_wron		70.05 271	70.44 263	68.88 289	73.84 322	53.47 279	58.93 326	67.28 314	58.43 269	87.09 142	85.40 248	59.80 251	67.25 317	59.66 249	83.54 287	85.92 241

XXY-MVS		74.44 242	76.19 221	69.21 287	84.61 237	52.43 288	71.70 293	77.18 258	60.73 264	80.60 229	90.96 161	75.44 141	69.35 311	56.13 268	88.33 243	85.86 242

tpmp4_e23		69.43 274	67.33 281	75.72 258	78.53 292	52.75 284	82.13 198	74.91 270	49.23 319	66.37 310	84.17 266	41.28 324	88.67 223	49.73 297	79.63 305	85.75 243

原ACMM1				84.60 127	92.81 70	74.01 108		91.50 96	62.59 249	82.73 206	90.67 171	76.53 137	94.25 61	69.24 186	95.69 115	85.55 244

pmmvs4		74.92 237	72.98 246	80.73 203	84.95 233	71.71 133	76.23 268	77.59 256	52.83 295	77.73 251	86.38 234	56.35 266	84.97 261	57.72 262	87.05 259	85.51 245

MAR-MVS		80.24 194	78.74 201	84.73 124	86.87 209	78.18 76	85.75 112	87.81 184	65.67 228	77.84 248	78.50 307	73.79 168	90.53 189	61.59 238	90.87 217	85.49 246
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	76.34 254	83.46 254	57.20 256	80.02 227	88.04 180	52.14 301	83.65 197	91.25 144	63.24 236	86.65 244	54.66 279	94.11 155	85.17 247

HY-MVS	64.64 18	73.03 248	72.47 252	74.71 263	83.36 255	54.19 274	82.14 197	81.96 236	56.76 279	69.57 300	86.21 238	60.03 247	84.83 264	49.58 298	82.65 294	85.11 248

MVP-Stereo		75.81 231	73.51 241	82.71 174	89.35 141	73.62 109	80.06 225	85.20 216	60.30 265	73.96 278	87.94 217	57.89 260	89.45 208	52.02 288	74.87 319	85.06 249
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
IB-MVS	62.13 19	71.64 258	68.97 272	79.66 215	80.80 277	62.26 217	73.94 284	76.90 260	63.27 244	68.63 303	76.79 313	33.83 333	91.84 153	59.28 251	87.26 257	84.88 250
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		70.73 264	70.07 267	72.72 274	77.03 302	52.73 285	74.14 282	75.65 268	50.36 315	72.17 288	85.37 250	55.42 272	80.67 284	52.86 286	87.59 255	84.77 251

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	84.75 252

无先验							82.81 175	85.62 212	58.09 271				91.41 166	67.95 200		84.48 253

PAPM		71.77 257	70.06 268	76.92 247	86.39 212	53.97 275	76.62 263	86.62 202	53.44 292	63.97 321	84.73 260	57.79 261	92.34 142	39.65 322	81.33 301	84.45 254

PVSNet_Blended		76.49 225	75.40 227	79.76 211	84.43 239	63.41 187	75.14 276	90.44 131	57.36 274	75.43 267	78.30 308	69.11 214	91.44 164	60.68 243	87.70 254	84.42 255

LP		69.42 275	68.30 277	72.77 273	71.48 334	56.84 260	73.66 287	74.84 271	63.52 241	70.95 296	83.35 275	49.55 287	77.15 293	57.13 264	70.21 327	84.33 256

thres200		72.34 254	71.55 258	74.70 264	83.48 253	51.60 294	75.02 277	73.71 280	70.14 193	78.56 246	80.57 298	46.20 295	88.20 228	46.99 309	89.29 233	84.32 257

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	81.65 218	87.16 227	83.40 64	94.24 62	61.69 235	94.76 145	84.21 258

EU-MVSNet		75.12 234	74.43 235	77.18 245	83.11 259	59.48 243	85.71 114	82.43 233	39.76 334	85.64 165	88.76 201	44.71 316	87.88 230	73.86 150	85.88 269	84.16 259

CR-MVSNet		74.00 243	73.04 245	76.85 249	79.58 280	62.64 203	82.58 181	76.90 260	50.50 314	75.72 265	92.38 118	48.07 290	84.07 268	68.72 194	82.91 292	83.85 260

RPMNet		76.06 228	75.79 223	76.85 249	79.58 280	62.64 203	82.58 181	71.75 296	74.80 137	75.72 265	92.59 113	48.69 288	84.07 268	73.48 154	82.91 292	83.85 260

MDTV_nov1_ep13_2view						27.60 338	70.76 295		46.47 324	61.27 324		45.20 308		49.18 299		83.75 262

旧先验1					91.97 90	71.77 129		81.78 239			91.84 130	73.92 166			93.65 169	83.61 263

N_pmnet		70.20 267	68.80 274	74.38 265	80.91 274	84.81 35	59.12 324	76.45 264	55.06 284	75.31 270	82.36 286	55.74 269	54.82 336	47.02 308	87.24 258	83.52 264

ADS-MVSNet2		65.87 290	63.64 295	72.55 276	73.16 327	56.92 258	67.10 308	74.81 272	49.74 316	66.04 312	82.97 278	46.71 292	77.26 291	42.29 317	69.96 329	83.46 265

ADS-MVSNet		61.90 297	62.19 299	61.03 314	73.16 327	36.42 333	67.10 308	61.75 327	49.74 316	66.04 312	82.97 278	46.71 292	63.21 330	42.29 317	69.96 329	83.46 265

CostFormer		69.98 272	68.68 275	73.87 266	77.14 300	50.72 306	79.26 238	74.51 275	51.94 303	70.97 295	84.75 259	45.16 314	87.49 233	55.16 276	79.23 309	83.40 267

PS-MVSNAJ		77.04 215	76.53 218	78.56 226	87.09 205	61.40 225	75.26 275	87.13 195	61.25 260	74.38 277	77.22 312	76.94 130	90.94 175	64.63 220	84.83 281	83.35 268

xiu_mvs_v2_base		77.19 213	76.75 212	78.52 227	87.01 206	61.30 227	75.55 274	87.12 197	61.24 261	74.45 275	78.79 306	77.20 124	90.93 176	64.62 221	84.80 282	83.32 269

PatchmatchNet		69.71 273	68.83 273	72.33 277	77.66 298	53.60 278	79.29 237	69.99 306	57.66 273	72.53 285	82.93 280	46.45 294	80.08 288	60.91 242	72.09 324	83.31 270
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
Anonymous20231206		71.38 261	71.88 255	69.88 282	86.31 217	54.37 273	70.39 297	74.62 273	52.57 297	76.73 255	88.76 201	59.94 248	72.06 304	44.35 315	93.23 182	83.23 271

tpm		67.95 280	68.08 279	67.55 295	78.74 290	43.53 325	75.60 272	67.10 318	54.92 285	72.23 287	88.10 214	42.87 321	75.97 296	52.21 287	80.95 304	83.15 272

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	83.13 273
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
tpm2		68.45 279	66.83 283	73.30 269	78.93 288	48.50 311	79.76 229	71.76 295	47.50 321	69.92 299	83.60 270	42.07 323	88.40 225	48.44 303	79.51 306	83.01 274

TR-MVS		76.77 221	75.79 223	79.72 212	86.10 224	65.79 170	77.14 259	83.02 229	65.20 233	81.40 221	82.10 288	66.30 223	90.73 184	55.57 272	85.27 274	82.65 275

1314		73.22 246	72.56 251	75.20 260	80.41 279	57.84 251	81.64 208	85.36 214	51.68 304	73.10 283	76.65 314	61.45 240	85.19 259	63.54 225	79.21 310	82.59 276

WTY-MVS		67.91 281	68.35 276	66.58 298	80.82 276	48.12 313	65.96 311	72.60 287	53.67 291	71.20 293	81.68 293	58.97 255	69.06 313	48.57 301	81.67 298	82.55 277

MIMVSNet		71.09 262	71.59 257	69.57 286	87.23 198	50.07 309	78.91 243	71.83 294	60.20 266	71.26 292	91.76 134	55.08 274	76.09 295	41.06 320	87.02 260	82.54 278

BH-untuned		80.96 185	80.99 182	80.84 201	88.55 157	68.23 155	80.33 224	88.46 171	72.79 164	86.55 150	86.76 231	74.72 155	91.77 156	61.79 234	88.99 237	82.52 279

API-MVS		82.28 169	82.61 162	81.30 195	86.29 218	69.79 142	88.71 67	87.67 185	78.42 93	82.15 210	84.15 267	77.98 116	91.59 160	65.39 216	92.75 190	82.51 280

Gipuma		84.44 126	86.33 92	78.78 222	84.20 246	73.57 110	89.55 51	90.44 131	84.24 29	84.38 186	94.89 51	76.35 139	80.40 285	76.14 134	96.80 74	82.36 281
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
testmv		70.47 266	70.70 261	69.77 284	86.22 221	53.89 277	67.32 307	71.91 293	63.32 242	78.16 247	89.47 193	56.12 268	73.10 302	36.43 328	87.33 256	82.33 282

DWT-MVSNet_test		66.43 286	64.37 291	72.63 275	74.86 320	50.86 301	76.52 264	72.74 286	54.06 289	65.50 314	68.30 330	32.13 335	84.84 263	61.63 237	73.59 320	82.19 283

PatchT		70.52 265	72.76 247	63.79 306	79.38 283	33.53 335	77.63 255	65.37 321	73.61 148	71.77 289	92.79 111	44.38 317	75.65 298	64.53 222	85.37 273	82.18 284

tpmvs		70.16 268	69.56 270	71.96 279	74.71 321	48.13 312	79.63 230	75.45 269	65.02 236	70.26 297	81.88 290	45.34 307	85.68 255	58.34 258	75.39 318	82.08 285

wuykxyi23d		88.46 61	88.80 59	87.44 79	90.96 118	93.03 1	85.85 111	81.96 236	74.58 139	98.58 2	97.29 5	87.73 31	87.31 235	82.84 67	99.41 1	81.99 286

1121		80.86 186	79.81 196	84.02 142	93.93 45	78.70 74	81.64 208	80.18 247	55.43 283	83.67 195	91.15 150	71.29 207	91.41 166	67.95 200	93.06 184	81.96 287

新几何1				82.95 170	93.96 44	78.56 75		80.24 246	55.45 282	83.93 193	91.08 155	71.19 208	88.33 226	65.84 214	93.07 183	81.95 288

Patchmatch-test1		72.75 250	72.61 249	73.19 270	81.62 267	55.86 264	78.89 244	71.37 298	61.73 256	74.93 272	82.15 287	60.46 244	81.80 279	59.68 248	82.63 296	81.92 289

PatchFormer-LS_test		67.91 281	66.49 287	72.17 278	75.29 316	51.85 292	75.68 270	73.62 282	57.23 276	68.64 301	68.13 331	42.19 322	82.76 276	64.06 223	73.51 321	81.89 290

Patchmatch-test		65.91 289	67.38 280	61.48 312	75.51 313	43.21 326	68.84 300	63.79 323	62.48 251	72.80 284	83.42 274	44.89 315	59.52 333	48.27 304	86.45 264	81.70 291

1111		61.71 298	63.77 294	55.55 321	78.05 294	25.74 339	60.62 318	67.52 311	66.09 222	74.68 273	86.50 232	16.00 345	59.22 334	38.79 323	85.65 270	81.70 291

UnsupCasMVSNet_bld		69.21 277	69.68 269	67.82 294	79.42 282	51.15 297	67.82 306	75.79 265	54.15 288	77.47 252	85.36 251	59.26 254	70.64 307	48.46 302	79.35 308	81.66 293

PVSNet	58.17 21	66.41 287	65.63 289	68.75 290	81.96 264	49.88 310	62.19 317	72.51 289	51.03 309	68.04 305	75.34 319	50.84 282	74.77 299	45.82 313	82.96 290	81.60 294

Patchmatch-RL test		74.48 240	73.68 239	76.89 248	84.83 235	66.54 166	72.29 291	69.16 310	57.70 272	86.76 146	86.33 235	45.79 302	82.59 277	69.63 183	90.65 224	81.54 295

test0.0.03 1		64.66 293	64.36 292	65.57 301	75.03 319	46.89 315	64.69 313	61.58 329	62.43 253	71.18 294	77.54 309	43.41 318	68.47 314	40.75 321	82.65 294	81.35 296

test-LLR		67.21 283	66.74 284	68.63 291	76.45 306	55.21 269	67.89 303	67.14 316	62.43 253	65.08 317	72.39 323	43.41 318	69.37 309	61.00 240	84.89 279	81.31 297

test-mter		65.00 292	63.79 293	68.63 291	76.45 306	55.21 269	67.89 303	67.14 316	50.98 310	65.08 317	72.39 323	28.27 340	69.37 309	61.00 240	84.89 279	81.31 297

test222					93.31 55	76.54 92	79.38 236	77.79 255	52.59 296	82.36 207	90.84 165	66.83 222			91.69 203	81.25 299

sss		66.92 284	67.26 282	65.90 299	77.23 299	51.10 299	64.79 312	71.72 297	52.12 302	70.13 298	80.18 300	57.96 259	65.36 326	50.21 293	81.01 303	81.25 299

tpm cat1		66.76 285	65.21 290	71.42 280	77.09 301	50.62 307	78.01 250	73.68 281	44.89 327	68.64 301	79.00 305	45.51 304	82.42 278	49.91 295	70.15 328	81.23 301

CVMVSNet		72.62 251	71.41 259	76.28 255	83.25 256	60.34 237	83.50 158	79.02 252	37.77 335	76.33 258	85.10 252	49.60 286	87.41 234	70.54 178	77.54 315	81.08 302

tpmrst		66.28 288	66.69 285	65.05 304	72.82 330	39.33 330	78.20 249	70.69 304	53.16 294	67.88 306	80.36 299	48.18 289	74.75 300	58.13 260	70.79 326	81.08 302

testdata				79.54 217	92.87 66	72.34 120		80.14 248	59.91 267	85.47 169	91.75 135	67.96 218	85.24 258	68.57 196	92.18 201	81.06 304

PM-MVS		80.20 195	79.00 199	83.78 149	88.17 167	86.66 13	81.31 213	66.81 319	69.64 196	88.33 127	90.19 181	64.58 229	83.63 273	71.99 169	90.03 228	81.06 304

no-one		71.52 260	70.43 265	74.81 262	78.45 293	63.41 187	57.73 327	77.03 259	51.46 307	77.17 254	90.33 178	54.96 275	80.35 286	47.41 306	99.29 2	80.68 306

EPMVS		62.47 294	62.63 298	62.01 308	70.63 335	38.74 331	74.76 278	52.86 338	53.91 290	67.71 308	80.01 301	39.40 328	66.60 321	55.54 273	68.81 333	80.68 306

JIA-IIPM		69.41 276	66.64 286	77.70 239	73.19 326	71.24 136	75.67 271	65.56 320	70.42 189	65.18 316	92.97 104	33.64 334	83.06 274	53.52 284	69.61 331	78.79 308

BH-w/o		76.57 223	76.07 222	78.10 233	86.88 208	65.92 169	77.63 255	86.33 204	65.69 227	80.89 226	79.95 302	68.97 216	90.74 183	53.01 285	85.25 275	77.62 309

TESTMET0.1,1		61.29 301	60.32 305	64.19 305	72.06 331	51.30 295	67.89 303	62.09 325	45.27 326	60.65 326	69.01 326	27.93 341	64.74 327	56.31 267	81.65 300	76.53 310

testus		62.33 296	63.03 296	60.20 316	78.78 289	40.74 328	59.14 322	69.80 307	49.26 318	71.41 291	74.72 321	52.33 280	63.52 328	29.84 335	82.01 297	76.36 311

gg-mvs-nofinetune		68.96 278	69.11 271	68.52 293	76.12 308	45.32 318	83.59 151	55.88 336	86.68 20	64.62 320	97.01 7	30.36 337	83.97 271	44.78 314	82.94 291	76.26 312

dp		60.70 305	60.29 306	61.92 310	72.04 332	38.67 332	70.83 294	64.08 322	51.28 308	60.75 325	77.28 311	36.59 331	71.58 306	47.41 306	62.34 335	75.52 313

MS-PatchMatch		70.93 263	70.22 266	73.06 272	81.85 266	62.50 209	73.82 286	77.90 254	52.44 298	75.92 263	81.27 295	55.67 270	81.75 280	55.37 274	77.70 313	74.94 314

MVS		73.21 247	72.59 250	75.06 261	80.97 273	60.81 234	81.64 208	85.92 209	46.03 325	71.68 290	77.54 309	68.47 217	89.77 204	55.70 271	85.39 272	74.60 315

test2356		56.69 308	55.15 312	61.32 313	73.20 325	44.11 323	54.95 329	62.52 324	48.75 320	62.45 323	68.42 328	21.10 344	65.67 325	26.86 337	78.08 312	74.19 316

test1235678		65.57 291	65.73 288	65.06 303	82.84 261	50.90 300	62.90 315	69.26 308	57.17 277	72.36 286	83.04 276	46.02 297	70.10 308	32.79 333	85.24 276	74.19 316

pmmvs3		62.47 294	60.02 307	69.80 283	71.58 333	64.00 181	70.52 296	58.44 333	39.77 333	66.05 311	75.84 316	27.10 342	72.28 303	46.15 311	84.77 283	73.11 318

PMMVS2		55.64 311	59.27 308	44.74 326	64.30 340	12.32 343	40.60 335	49.79 341	53.19 293	65.06 319	84.81 258	53.60 278	49.76 338	32.68 334	89.41 232	72.15 319

PatchMatch-RL		74.48 240	73.22 243	78.27 231	87.70 186	85.26 30	75.92 269	70.09 305	64.34 239	76.09 262	81.25 296	65.87 227	78.07 290	53.86 282	83.82 286	71.48 320

GG-mvs-BLEND				67.16 296	73.36 324	46.54 317	84.15 134	55.04 337		58.64 333	61.95 336	29.93 338	83.87 272	38.71 326	76.92 316	71.07 321

MVE	40.22 23	51.82 314	50.47 316	55.87 319	62.66 341	51.91 291	31.61 337	39.28 343	40.65 332	50.76 338	74.98 320	56.24 267	44.67 340	33.94 332	64.11 334	71.04 322
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
new_pmnet		55.69 310	57.66 309	49.76 323	75.47 314	30.59 336	59.56 320	51.45 340	43.62 330	62.49 322	75.48 317	40.96 326	49.15 339	37.39 327	72.52 322	69.55 323

DSMNet-mixed		60.98 304	61.61 301	59.09 318	72.88 329	45.05 321	74.70 279	46.61 342	26.20 337	65.34 315	90.32 179	55.46 271	63.12 331	41.72 319	81.30 302	69.09 324

CHOSEN 280x420		59.08 306	56.52 311	66.76 297	76.51 304	64.39 178	49.62 334	59.00 331	43.86 329	55.66 337	68.41 329	35.55 332	68.21 315	43.25 316	76.78 317	67.69 325

test12356		54.91 312	57.14 310	48.22 325	75.83 310	17.47 341	52.31 333	69.20 309	51.66 305	60.11 327	75.40 318	29.77 339	62.62 332	27.64 336	72.37 323	64.59 326

EMVS		61.10 303	60.81 303	61.99 309	65.96 338	55.86 264	53.10 332	58.97 332	67.06 214	56.89 336	63.33 334	40.98 325	67.03 318	54.79 278	86.18 268	63.08 327

E-PMN		61.59 300	61.62 300	61.49 311	66.81 336	55.40 267	53.77 331	60.34 330	66.80 218	58.90 332	65.50 333	40.48 327	66.12 323	55.72 270	86.25 267	62.95 328

PMMVS		61.65 299	60.38 304	65.47 302	65.40 339	69.26 148	63.97 314	61.73 328	36.80 336	60.11 327	68.43 327	59.42 252	66.35 322	48.97 300	78.57 311	60.81 329

wuyk23d		75.13 233	79.30 197	62.63 307	75.56 311	75.18 102	80.89 219	73.10 285	75.06 136	94.76 15	95.32 40	87.73 31	52.85 337	34.16 331	97.11 64	59.85 330

PVSNet_0	51.08 22	56.10 309	54.97 313	59.48 317	75.12 318	53.28 282	55.16 328	61.89 326	44.30 328	59.16 330	62.48 335	54.22 276	65.91 324	35.40 330	47.01 336	59.25 331

FPMVS		72.29 255	72.00 254	73.14 271	88.63 156	85.00 32	74.65 280	67.39 313	71.94 177	77.80 250	87.66 222	50.48 284	75.83 297	49.95 294	79.51 306	58.58 332

MVS-HIRNet		61.16 302	62.92 297	55.87 319	79.09 286	35.34 334	71.83 292	57.98 335	46.56 323	59.05 331	91.14 151	49.95 285	76.43 294	38.74 325	71.92 325	55.84 333

PNet_i23d		52.13 313	51.24 315	54.79 322	75.56 311	45.26 319	54.54 330	52.55 339	66.95 215	57.19 335	65.82 332	13.15 347	63.40 329	36.39 329	39.04 338	55.71 334

testpf		58.55 307	61.58 302	49.48 324	66.03 337	40.05 329	74.40 281	58.07 334	64.72 238	59.36 329	72.67 322	22.76 343	66.92 319	67.07 203	69.15 332	41.46 335

DeepMVS_CX				24.13 329	32.95 342	29.49 337		21.63 346	12.07 338	37.95 339	45.07 337	30.84 336	19.21 341	17.94 339	33.06 339	23.69 336

tmp_tt		20.25 318	24.50 319	7.49 330	4.47 343	8.70 344	34.17 336	25.16 345	1.00 339	32.43 340	18.49 338	39.37 329	9.21 342	21.64 338	43.75 337	4.57 337

test123		6.27 321	8.08 322	0.84 331	1.11 345	0.57 345	62.90 315	0.82 347	0.54 340	1.07 342	2.75 343	1.26 348	0.30 343	1.04 340	1.26 342	1.66 338

.test1245		48.02 315	54.41 314	28.84 328	78.05 294	25.74 339	60.62 318	67.52 311	66.09 222	74.68 273	86.50 232	16.00 345	59.22 334	38.79 323	1.47 340	1.55 339

testmvs		5.91 322	7.65 323	0.72 332	1.20 344	0.37 346	59.14 322	0.67 348	0.49 341	1.11 341	2.76 342	0.94 349	0.24 344	1.02 341	1.47 340	1.55 339

cdsmvs_eth3d_5k		20.81 317	27.75 318	0.00 333	0.00 346	0.00 347	0.00 338	85.44 213	0.00 342	0.00 343	82.82 281	81.46 90	0.00 345	0.00 342	0.00 343	0.00 341

pcd_1.5k_mvsjas		6.41 320	8.55 321	0.00 333	0.00 346	0.00 347	0.00 338	0.00 349	0.00 342	0.00 343	0.00 344	76.94 130	0.00 345	0.00 342	0.00 343	0.00 341

sosnet-low-res		0.00 323	0.00 324	0.00 333	0.00 346	0.00 347	0.00 338	0.00 349	0.00 342	0.00 343	0.00 344	0.00 350	0.00 345	0.00 342	0.00 343	0.00 341

sosnet		0.00 323	0.00 324	0.00 333	0.00 346	0.00 347	0.00 338	0.00 349	0.00 342	0.00 343	0.00 344	0.00 350	0.00 345	0.00 342	0.00 343	0.00 341

uncertanet		0.00 323	0.00 324	0.00 333	0.00 346	0.00 347	0.00 338	0.00 349	0.00 342	0.00 343	0.00 344	0.00 350	0.00 345	0.00 342	0.00 343	0.00 341

Regformer		0.00 323	0.00 324	0.00 333	0.00 346	0.00 347	0.00 338	0.00 349	0.00 342	0.00 343	0.00 344	0.00 350	0.00 345	0.00 342	0.00 343	0.00 341

ab-mvs-re		6.65 319	8.87 320	0.00 333	0.00 346	0.00 347	0.00 338	0.00 349	0.00 342	0.00 343	79.80 303	0.00 350	0.00 345	0.00 342	0.00 343	0.00 341

uanet		0.00 323	0.00 324	0.00 333	0.00 346	0.00 347	0.00 338	0.00 349	0.00 342	0.00 343	0.00 344	0.00 350	0.00 345	0.00 342	0.00 343	0.00 341

ESAPD								93.79 28

sam_mvs1												46.11 296

sam_mvs												45.92 301

MTGPA								91.81 89

test_post1							78.85 245				3.13 340	45.19 309	80.13 287	58.11 261

test_post											3.10 341	45.43 305	77.22 292

patchmatchnet-post											81.71 292	45.93 300	87.01 237

MTMP								33.14 344

gm-plane-assit					75.42 315	44.97 322			52.17 299		72.36 325		87.90 229	54.10 281

TEST9					92.34 80	79.70 66	83.94 139	90.32 135	65.41 232	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	65.79 225	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		75.43 132	84.58 182	91.57 137	81.92 85		79.54 106	96.97 67

旧先验2							81.73 206		56.88 278	86.54 155			84.90 262	72.81 162

新几何2							81.72 207

原ACMM2							82.26 193

testdata2													86.43 247	63.52 226

segment_acmp												81.94 82

testdata1							79.62 231		73.95 146

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								0.00 349

nn								0.00 349

door-mid								74.45 276

test11								91.46 102

door								72.57 288

HQP5-MVS						70.66 139

HQP-NCC					91.19 111		84.77 122		73.30 155	80.55 232

ACMP_Plane					91.19 111		84.77 122		73.30 155	80.55 232

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			68.29 278		78.03 296	43.87 324	74.12 283	72.22 290	52.17 299	67.02 309	85.54 242	45.36 306	80.85 283	55.73 269	84.42 284

ACMMP++_ref															95.74 114

ACMMP++															97.35 58

Test By Simon												79.09 108

High-resolution multi-view benchmark