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 36	95.54 5	97.36 1	96.97 1	99.04 1	99.05 1	96.61 1	95.92 14	85.07 54	99.27 1	99.54 1

PS-CasMVS		90.06 43	91.92 13	84.47 156	96.56 7	58.83 296	89.04 85	92.74 99	91.40 5	96.12 4	96.06 22	87.23 47	95.57 38	79.42 120	98.74 6	99.00 2

PEN-MVS		90.03 45	91.88 16	84.48 155	96.57 6	58.88 293	88.95 86	93.19 77	91.62 4	96.01 6	96.16 20	87.02 49	95.60 36	78.69 125	98.72 9	98.97 3

CP-MVSNet		89.27 63	90.91 43	84.37 157	96.34 9	58.61 298	88.66 95	92.06 113	90.78 6	95.67 7	95.17 45	81.80 115	95.54 42	79.00 123	98.69 10	98.95 4

WR-MVS_H		89.91 50	91.31 31	85.71 134	96.32 10	62.39 251	89.54 76	93.31 70	90.21 10	95.57 9	95.66 30	81.42 119	95.90 15	80.94 99	98.80 3	98.84 5

DTE-MVSNet		89.98 47	91.91 15	84.21 163	96.51 8	57.84 301	88.93 88	92.84 96	91.92 3	96.16 3	96.23 18	86.95 50	95.99 10	79.05 122	98.57 15	98.80 6

FC-MVSNet-test		85.93 113	87.05 96	82.58 202	92.25 106	56.44 312	85.75 139	93.09 83	77.33 125	91.94 71	94.65 59	74.78 184	93.41 135	75.11 171	98.58 14	97.88 7

v7n		90.13 40	90.96 41	87.65 97	91.95 116	71.06 173	89.99 62	93.05 85	86.53 28	94.29 19	96.27 17	82.69 93	94.08 103	86.25 40	97.63 65	97.82 8

TranMVSNet+NR-MVSNet		87.86 84	88.76 75	85.18 142	94.02 58	64.13 230	84.38 160	91.29 136	84.88 39	92.06 67	93.84 104	86.45 58	93.73 116	73.22 192	98.66 11	97.69 9

DU-MVS		86.80 97	86.99 97	86.21 122	93.24 79	67.02 206	83.16 197	92.21 109	81.73 72	90.92 87	91.97 154	77.20 158	93.99 105	74.16 177	98.35 22	97.61 10

NR-MVSNet		86.00 110	86.22 109	85.34 140	93.24 79	64.56 226	82.21 225	90.46 157	80.99 80	88.42 139	91.97 154	77.56 154	93.85 111	72.46 202	98.65 12	97.61 10

FIs		85.35 120	86.27 108	82.60 201	91.86 121	57.31 305	85.10 147	93.05 85	75.83 144	91.02 86	93.97 95	73.57 197	92.91 154	73.97 182	98.02 41	97.58 12

RRT_MVS		88.30 76	87.83 82	89.70 56	93.62 70	75.70 128	92.36 27	89.06 192	77.34 124	93.63 36	95.83 25	65.40 251	95.90 15	85.01 57	98.23 29	97.49 13

UniMVSNet_NR-MVSNet		86.84 96	87.06 95	86.17 124	92.86 89	67.02 206	82.55 213	91.56 127	83.08 57	90.92 87	91.82 160	78.25 148	93.99 105	74.16 177	98.35 22	97.49 13

UniMVSNet_ETH3D		89.12 66	90.72 46	84.31 161	97.00 2	64.33 229	89.67 71	88.38 201	88.84 15	94.29 19	97.57 3	90.48 14	91.26 196	72.57 201	97.65 64	97.34 15

OurMVSNet-221017-0		90.01 46	89.74 55	90.83 37	93.16 81	80.37 73	91.91 35	93.11 81	81.10 79	95.32 10	97.24 5	72.94 207	94.85 72	85.07 54	97.78 56	97.26 16

mvsmamba		87.87 83	87.23 92	89.78 55	92.31 104	76.51 121	91.09 43	91.87 119	72.61 190	92.16 64	95.23 43	66.01 247	95.59 37	86.02 46	97.78 56	97.24 17

WR-MVS		83.56 163	84.40 149	81.06 227	93.43 74	54.88 323	78.67 276	85.02 257	81.24 77	90.74 91	91.56 167	72.85 208	91.08 202	68.00 240	98.04 38	97.23 18

TDRefinement		93.52 2	93.39 3	93.88 1	95.94 15	90.26 3	95.70 4	96.46 2	90.58 8	92.86 50	96.29 16	88.16 35	94.17 99	86.07 43	98.48 18	97.22 19

v10		86.54 100	87.10 94	84.84 147	88.16 211	63.28 238	86.64 128	92.20 110	75.42 152	92.81 53	94.50 65	74.05 192	94.06 104	83.88 67	96.28 118	97.17 20

anonymousdsp		89.73 53	88.88 72	92.27 9	89.82 178	86.67 17	90.51 52	90.20 171	69.87 225	95.06 11	96.14 21	84.28 77	93.07 148	87.68 13	96.34 116	97.09 21

test_djsdf		89.62 54	89.01 68	91.45 25	92.36 100	82.98 57	91.98 32	90.08 174	71.54 204	94.28 21	96.54 13	81.57 117	94.27 90	86.26 38	96.49 109	97.09 21

v8		86.22 107	86.83 101	84.36 159	87.82 215	62.35 253	86.42 131	91.33 135	76.78 131	92.73 55	94.48 67	73.41 201	93.72 117	83.10 74	95.41 153	97.01 23

UniMVSNet (Re)		86.87 94	86.98 98	86.55 111	93.11 82	68.48 195	83.80 176	92.87 93	80.37 86	89.61 118	91.81 161	77.72 152	94.18 97	75.00 172	98.53 16	96.99 24

Anonymous20231211		88.40 74	89.62 58	84.73 151	90.46 166	65.27 220	88.86 89	93.02 89	87.15 25	93.05 46	97.10 6	82.28 102	92.02 176	76.70 152	97.99 43	96.88 25

IS-MVSNet		86.66 99	86.82 102	86.17 124	92.05 114	66.87 208	91.21 41	88.64 197	86.30 30	89.60 119	92.59 136	69.22 230	94.91 70	73.89 183	97.89 52	96.72 26

test_part1		87.15 92	87.82 83	85.15 143	88.88 194	63.04 241	87.98 103	94.85 16	82.52 63	93.61 38	95.73 27	67.51 238	95.71 32	80.48 107	98.83 2	96.69 27

UA-Net		91.49 17	91.53 22	91.39 26	94.98 36	82.95 58	93.52 7	92.79 97	88.22 20	88.53 136	97.64 2	83.45 86	94.55 84	86.02 46	98.60 13	96.67 28

pmmvs6		86.52 101	88.06 80	81.90 211	92.22 108	62.28 254	84.66 153	89.15 190	83.54 51	89.85 108	97.32 4	88.08 38	86.80 284	70.43 218	97.30 83	96.62 29

RPSCF		88.00 81	86.93 99	91.22 31	90.08 172	89.30 5	89.68 70	91.11 141	79.26 102	89.68 113	94.81 57	82.44 96	87.74 271	76.54 155	88.74 289	96.61 30

LTVRE_ROB	86.10 1	93.04 3	93.44 2	91.82 23	93.73 66	85.72 33	96.79 1	95.51 8	88.86 14	95.63 8	96.99 8	84.81 72	93.16 143	91.10 1	97.53 75	96.58 31
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 85	88.49 76	85.91 128	90.07 174	69.73 181	87.86 106	94.20 28	74.04 165	92.70 56	94.66 58	85.88 65	91.50 187	79.72 114	97.32 82	96.50 32

v2v482		84.09 151	84.24 152	83.62 177	87.13 230	61.40 261	82.71 208	89.71 180	72.19 199	89.55 120	91.41 170	70.70 226	93.20 140	81.02 97	93.76 199	96.25 33

PS-MVSNAJss		88.31 75	87.90 81	89.56 62	93.31 77	77.96 97	87.94 105	91.97 116	70.73 214	94.19 22	96.67 11	76.94 164	94.57 82	83.07 75	96.28 118	96.15 34

v1192		84.57 136	84.69 140	84.21 163	87.75 217	62.88 243	83.02 200	91.43 131	69.08 231	89.98 105	90.89 187	72.70 211	93.62 123	82.41 83	94.97 171	96.13 35

EI-MVSNet-UG-set		85.04 127	84.44 146	86.85 106	83.87 289	72.52 154	83.82 174	85.15 253	80.27 89	88.75 132	85.45 286	79.95 136	91.90 179	81.92 90	90.80 266	96.13 35

v1921920		84.23 148	84.37 150	83.79 172	87.64 221	61.71 259	82.91 203	91.20 139	67.94 246	90.06 100	90.34 201	72.04 218	93.59 125	82.32 85	94.91 172	96.07 37

v1240		84.30 144	84.51 145	83.65 176	87.65 220	61.26 264	82.85 205	91.54 128	67.94 246	90.68 92	90.65 196	71.71 221	93.64 119	82.84 79	94.78 177	96.07 37

v144192		84.24 147	84.41 148	83.71 175	87.59 222	61.57 260	82.95 202	91.03 143	67.82 249	89.80 110	90.49 199	73.28 204	93.51 130	81.88 91	94.89 174	96.04 39

v1144		84.54 139	84.72 138	84.00 167	87.67 219	62.55 249	82.97 201	90.93 147	70.32 220	89.80 110	90.99 182	73.50 198	93.48 131	81.69 92	94.65 182	95.97 40

EI-MVSNet-Vis-set		85.12 124	84.53 144	86.88 105	84.01 286	72.76 145	83.91 172	85.18 252	80.44 85	88.75 132	85.49 282	80.08 134	91.92 178	82.02 87	90.85 265	95.97 40

HPM-MVS_fast		92.50 5	92.54 6	92.37 6	95.93 16	85.81 32	92.99 13	94.23 26	85.21 36	92.51 58	95.13 46	90.65 10	95.34 54	88.06 9	98.15 36	95.95 42

tttt0517		81.07 197	79.58 218	85.52 137	88.99 192	66.45 211	87.03 118	75.51 319	73.76 169	88.32 143	90.20 205	37.96 371	94.16 102	79.36 121	95.13 164	95.93 43

ANet_high		83.17 171	85.68 121	75.65 301	81.24 311	45.26 370	79.94 254	92.91 92	83.83 45	91.33 80	96.88 10	80.25 133	85.92 297	68.89 232	95.89 138	95.76 44

IterMVS-LS		84.73 133	84.98 132	83.96 169	87.35 225	63.66 233	83.25 193	89.88 178	76.06 137	89.62 116	92.37 146	73.40 203	92.52 161	78.16 133	94.77 179	95.69 45
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
EI-MVSNet		82.61 176	82.42 180	83.20 188	83.25 293	63.66 233	83.50 186	85.07 254	76.06 137	86.55 173	85.10 292	73.41 201	90.25 225	78.15 135	90.67 269	95.68 46

EPP-MVSNet		85.47 118	85.04 131	86.77 108	91.52 138	69.37 185	91.63 38	87.98 212	81.51 75	87.05 163	91.83 159	66.18 246	95.29 55	70.75 213	96.89 93	95.64 47

V42		83.47 166	83.37 163	83.75 174	83.16 295	63.33 237	81.31 237	90.23 170	69.51 227	90.91 89	90.81 190	74.16 190	92.29 170	80.06 108	90.22 273	95.62 48

ACMH+	77.89 11	90.73 30	91.50 23	88.44 85	93.00 84	76.26 124	89.65 72	95.55 7	87.72 23	93.89 27	94.94 50	91.62 4	93.44 133	78.35 128	98.76 4	95.61 49

mvs_tets		89.78 52	89.27 63	91.30 28	93.51 71	84.79 43	89.89 65	90.63 154	70.00 224	94.55 15	96.67 11	87.94 39	93.59 125	84.27 64	95.97 132	95.52 50

OMC-MVS		88.19 77	87.52 88	90.19 49	91.94 118	81.68 65	87.49 111	93.17 78	76.02 139	88.64 134	91.22 174	84.24 78	93.37 136	77.97 138	97.03 90	95.52 50

SixPastTwentyTwo		87.20 91	87.45 89	86.45 113	92.52 96	69.19 191	87.84 107	88.05 209	81.66 73	94.64 14	96.53 14	65.94 248	94.75 74	83.02 77	96.83 97	95.41 52

KD-MVS_self_test		81.93 189	83.14 167	78.30 268	84.75 270	52.75 335	80.37 249	89.42 187	70.24 222	90.26 98	93.39 114	74.55 189	86.77 285	68.61 236	96.64 102	95.38 53

jajsoiax		89.41 58	88.81 74	91.19 32	93.38 75	84.72 44	89.70 68	90.29 168	69.27 228	94.39 17	96.38 15	86.02 64	93.52 129	83.96 66	95.92 137	95.34 54

HPM-MVS		92.13 9	92.20 11	91.91 17	95.58 26	84.67 45	93.51 8	94.85 16	82.88 59	91.77 73	93.94 102	90.55 13	95.73 31	88.50 7	98.23 29	95.33 55
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
Anonymous20240529		86.20 108	87.13 93	83.42 182	90.19 170	64.55 227	84.55 155	90.71 151	85.85 33	89.94 106	95.24 42	82.13 104	90.40 223	69.19 229	96.40 114	95.31 56

Baseline_NR-MVSNet		84.00 155	85.90 115	78.29 269	91.47 140	53.44 331	82.29 221	87.00 231	79.06 105	89.55 120	95.72 29	77.20 158	86.14 295	72.30 203	98.51 17	95.28 57

casdiffmvs		85.21 121	85.85 116	83.31 185	86.17 255	62.77 245	83.03 199	93.93 44	74.69 159	88.21 144	92.68 135	82.29 101	91.89 180	77.87 139	93.75 201	95.27 58

3Dnovator+	83.92 2	89.97 49	89.66 56	90.92 36	91.27 144	81.66 66	91.25 40	94.13 36	88.89 13	88.83 131	94.26 80	77.55 155	95.86 22	84.88 58	95.87 139	95.24 59

LPG-MVS_test		91.47 19	91.68 18	90.82 38	94.75 42	81.69 63	90.00 60	94.27 23	82.35 65	93.67 34	94.82 54	91.18 5	95.52 43	85.36 51	98.73 7	95.23 60

LGP-MVS_train				90.82 38	94.75 42	81.69 63		94.27 23	82.35 65	93.67 34	94.82 54	91.18 5	95.52 43	85.36 51	98.73 7	95.23 60

Regformer-4		86.41 102	85.71 120	88.52 81	84.27 279	77.57 102	84.07 164	88.00 211	82.82 60	89.84 109	85.48 283	82.06 106	92.77 156	83.83 69	91.04 256	95.22 62

test1111		78.53 235	78.85 226	77.56 280	92.22 108	47.49 363	82.61 209	69.24 356	72.43 191	85.28 197	94.20 83	51.91 319	90.07 237	65.36 259	96.45 112	95.11 63

MP-MVS-pluss		90.81 29	91.08 36	89.99 51	95.97 14	79.88 76	88.13 101	94.51 21	75.79 145	92.94 47	94.96 49	88.36 29	95.01 67	90.70 2	98.40 20	95.09 64
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
COLMAP_ROB	83.01 3	91.97 11	91.95 12	92.04 12	93.68 68	86.15 23	93.37 10	95.10 14	90.28 9	92.11 65	95.03 48	89.75 21	94.93 69	79.95 110	98.27 27	95.04 65
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
dcpmvs_2		84.23 148	85.14 129	81.50 219	88.61 200	61.98 258	82.90 204	93.11 81	68.66 237	92.77 54	92.39 142	78.50 144	87.63 273	76.99 151	92.30 230	94.90 66

CS-MVS		88.14 78	87.67 86	89.54 63	89.56 180	79.18 84	90.47 53	94.77 18	79.37 101	84.32 216	89.33 222	83.87 79	94.53 85	82.45 82	94.89 174	94.90 66

test2506		74.12 281	73.39 281	76.28 297	91.85 122	44.20 373	84.06 166	48.20 384	72.30 197	81.90 255	94.20 83	27.22 386	89.77 242	64.81 262	96.02 130	94.87 68

ECVR-MVS		78.44 236	78.63 230	77.88 276	91.85 122	48.95 357	83.68 180	69.91 354	72.30 197	84.26 223	94.20 83	51.89 320	89.82 241	63.58 270	96.02 130	94.87 68

v148		82.31 180	82.48 179	81.81 216	85.59 261	59.66 283	81.47 235	86.02 240	72.85 185	88.05 145	90.65 196	70.73 225	90.91 208	75.15 170	91.79 243	94.87 68

ACMP	79.16 10	90.54 34	90.60 48	90.35 46	94.36 47	80.98 69	89.16 83	94.05 40	79.03 106	92.87 49	93.74 109	90.60 12	95.21 61	82.87 78	98.76 4	94.87 68
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
eth_miper_zixun_eth		80.84 201	80.22 210	82.71 199	81.41 309	60.98 270	77.81 286	90.14 173	67.31 252	86.95 165	87.24 258	64.26 255	92.31 168	75.23 169	91.61 246	94.85 72

Regformer-3		85.06 126	84.67 141	86.22 120	84.27 279	73.43 140	84.07 164	85.26 250	80.77 84	88.62 135	85.48 283	80.56 130	90.39 224	81.99 88	91.04 256	94.85 72

K. test v3		85.14 123	84.73 136	86.37 114	91.13 150	69.63 183	85.45 143	76.68 311	84.06 44	92.44 60	96.99 8	62.03 269	94.65 77	80.58 105	93.24 210	94.83 74

baseline		85.20 122	85.93 114	83.02 191	86.30 249	62.37 252	84.55 155	93.96 43	74.48 162	87.12 157	92.03 153	82.30 100	91.94 177	78.39 126	94.21 191	94.74 75

thisisatest0530		79.07 225	77.33 244	84.26 162	87.13 230	64.58 225	83.66 181	75.95 314	68.86 234	85.22 198	87.36 255	38.10 369	93.57 128	75.47 166	94.28 190	94.62 76

c3_l		81.64 191	81.59 191	81.79 217	80.86 317	59.15 290	78.61 277	90.18 172	68.36 238	87.20 155	87.11 261	69.39 228	91.62 185	78.16 133	94.43 187	94.60 77

TSAR-MVS + MP.		88.14 78	87.82 83	89.09 70	95.72 22	76.74 117	92.49 25	91.19 140	67.85 248	86.63 172	94.84 53	79.58 138	95.96 13	87.62 14	94.50 184	94.56 78
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
ACMMP		91.91 12	91.87 17	92.03 13	95.53 27	85.91 27	93.35 11	94.16 31	82.52 63	92.39 61	94.14 88	89.15 23	95.62 35	87.35 23	98.24 28	94.56 78
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 50	90.72 160	84.97 40		90.30 165	81.56 74	90.02 102	91.20 176	82.40 98	90.81 212	73.58 188	94.66 181	94.56 78

LS3D		90.60 33	90.34 50	91.38 27	89.03 190	84.23 49	93.58 6	94.68 19	90.65 7	90.33 97	93.95 101	84.50 74	95.37 53	80.87 100	95.50 152	94.53 81

ETH3D-3000-0.1		88.85 71	88.96 71	88.52 81	91.94 118	77.27 111	88.71 93	95.26 13	76.08 136	90.66 93	92.69 134	84.48 75	93.83 114	83.38 72	97.48 78	94.47 82

HQP_MVS		87.75 88	87.43 90	88.70 79	93.45 72	76.42 122	89.45 79	93.61 58	79.44 99	86.55 173	92.95 124	74.84 182	95.22 59	80.78 102	95.83 140	94.46 83

plane_prior5								93.61 58					95.22 59	80.78 102	95.83 140	94.46 83

FMVS1		89.30 61	89.12 65	89.84 52	88.67 197	85.64 34	90.61 48	93.17 78	86.02 31	93.12 44	95.30 37	84.94 69	89.44 249	74.12 179	96.10 127	94.45 85

APD_test		89.30 61	89.12 65	89.84 52	88.67 197	85.64 34	90.61 48	93.17 78	86.02 31	93.12 44	95.30 37	84.94 69	89.44 249	74.12 179	96.10 127	94.45 85

TransMVSNet (Re)		84.02 154	85.74 119	78.85 257	91.00 153	55.20 322	82.29 221	87.26 219	79.65 96	88.38 141	95.52 34	83.00 90	86.88 282	67.97 241	96.60 105	94.45 85

pm-mvs1		83.69 160	84.95 133	79.91 244	90.04 176	59.66 283	82.43 217	87.44 216	75.52 149	87.85 148	95.26 41	81.25 121	85.65 301	68.74 234	96.04 129	94.42 88

SteuartSystems-ACMMP		91.16 26	91.36 26	90.55 42	93.91 61	80.97 70	91.49 39	93.48 63	82.82 60	92.60 57	93.97 95	88.19 33	96.29 4	87.61 15	98.20 33	94.39 89
Skip Steuart: Steuart Systems R&D Blog.
iter_conf05		78.81 230	77.35 243	83.21 187	82.98 299	60.75 274	84.09 163	88.34 203	63.12 281	84.25 224	89.48 218	31.41 379	94.51 87	76.64 153	95.83 140	94.38 90

VPA-MVSNet		83.47 166	84.73 136	79.69 248	90.29 168	57.52 304	81.30 239	88.69 196	76.29 133	87.58 152	94.44 68	80.60 129	87.20 277	66.60 249	96.82 98	94.34 91

xxxxxxxxxxxxxcwj		89.04 68	89.13 64	88.79 75	93.75 64	77.44 105	86.31 132	95.27 12	70.80 212	92.28 62	93.80 105	86.89 51	94.64 78	85.52 49	97.51 76	94.30 92

SF-MVS		90.27 39	90.80 45	88.68 80	92.86 89	77.09 112	91.19 42	95.74 5	81.38 76	92.28 62	93.80 105	86.89 51	94.64 78	85.52 49	97.51 76	94.30 92

XVS		91.54 15	91.36 26	92.08 10	95.64 24	86.25 21	92.64 19	93.33 67	85.07 37	89.99 103	94.03 92	86.57 56	95.80 25	87.35 23	97.62 66	94.20 94

X-MVStestdata		85.04 127	82.70 173	92.08 10	95.64 24	86.25 21	92.64 19	93.33 67	85.07 37	89.99 103	16.05 382	86.57 56	95.80 25	87.35 23	97.62 66	94.20 94

APD-MVS_3200maxsize		92.05 10	92.24 10	91.48 24	93.02 83	85.17 38	92.47 26	95.05 15	87.65 24	93.21 43	94.39 75	90.09 18	95.08 65	86.67 33	97.60 68	94.18 96

AllTest		87.97 82	87.40 91	89.68 57	91.59 129	83.40 52	89.50 77	95.44 9	79.47 97	88.00 146	93.03 119	82.66 94	91.47 188	70.81 210	96.14 124	94.16 97

TestCases				89.68 57	91.59 129	83.40 52		95.44 9	79.47 97	88.00 146	93.03 119	82.66 94	91.47 188	70.81 210	96.14 124	94.16 97

CS-MVS-test		87.00 93	86.43 105	88.71 78	89.46 181	77.46 104	89.42 81	95.73 6	77.87 119	81.64 263	87.25 257	82.43 97	94.53 85	77.65 140	96.46 111	94.14 99

ZNCC-MVS		91.26 23	91.34 29	91.01 35	95.73 21	83.05 56	92.18 29	94.22 27	80.14 91	91.29 81	93.97 95	87.93 40	95.87 19	88.65 4	97.96 48	94.12 100

OPM-MVS		89.80 51	89.97 52	89.27 66	94.76 41	79.86 77	86.76 125	92.78 98	78.78 109	92.51 58	93.64 111	88.13 36	93.84 113	84.83 60	97.55 71	94.10 101
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
Effi-MVS+-dtu		85.82 114	83.38 162	93.14 3	87.13 230	91.15 2	87.70 108	88.42 199	74.57 160	83.56 233	85.65 280	78.49 145	94.21 95	72.04 204	92.88 220	94.05 102

bld_raw_dy_0_64		84.85 131	84.44 146	86.07 126	93.73 66	74.93 132	88.57 96	81.90 282	70.44 216	91.28 82	95.18 44	56.62 303	89.28 253	85.15 53	97.09 88	93.99 103

ACMMPR		91.49 17	91.35 28	91.92 16	95.74 20	85.88 29	92.58 22	93.25 75	81.99 68	91.40 78	94.17 86	87.51 44	95.87 19	87.74 11	97.76 58	93.99 103

XVG-OURS-SEG-HR		89.59 55	89.37 61	90.28 47	94.47 46	85.95 26	86.84 121	93.91 45	80.07 92	86.75 168	93.26 115	93.64 2	90.93 206	84.60 62	90.75 267	93.97 105

PGM-MVS		91.20 25	90.95 42	91.93 15	95.67 23	85.85 30	90.00 60	93.90 46	80.32 88	91.74 74	94.41 72	88.17 34	95.98 11	86.37 36	97.99 43	93.96 106

GST-MVS		90.96 28	91.01 39	90.82 38	95.45 28	82.73 59	91.75 37	93.74 52	80.98 81	91.38 79	93.80 105	87.20 48	95.80 25	87.10 31	97.69 63	93.93 107

lessismore_v0				85.95 127	91.10 151	70.99 174		70.91 350		91.79 72	94.42 71	61.76 270	92.93 152	79.52 119	93.03 216	93.93 107

SMA-MVS		90.31 38	90.48 49	89.83 54	95.31 31	79.52 82	90.98 44	93.24 76	75.37 153	92.84 51	95.28 39	85.58 66	96.09 7	87.92 10	97.76 58	93.88 109
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
cl22		78.97 226	78.21 236	81.24 224	77.74 341	59.01 291	77.46 294	87.13 223	65.79 262	84.32 216	85.10 292	58.96 289	90.88 210	75.36 168	92.03 238	93.84 110

region2R		91.44 20	91.30 32	91.87 19	95.75 19	85.90 28	92.63 21	93.30 72	81.91 70	90.88 90	94.21 82	87.75 41	95.87 19	87.60 16	97.71 62	93.83 111

Regformer-2		86.74 98	86.08 112	88.73 76	84.18 283	79.20 83	83.52 183	89.33 188	83.33 53	89.92 107	85.07 295	83.23 89	93.16 143	83.39 71	92.72 225	93.83 111

GBi-Net		82.02 186	82.07 183	81.85 213	86.38 244	61.05 267	86.83 122	88.27 206	72.43 191	86.00 185	95.64 31	63.78 259	90.68 216	65.95 252	93.34 207	93.82 113

test1		82.02 186	82.07 183	81.85 213	86.38 244	61.05 267	86.83 122	88.27 206	72.43 191	86.00 185	95.64 31	63.78 259	90.68 216	65.95 252	93.34 207	93.82 113

FMVSNet1		84.55 137	85.45 125	81.85 213	90.27 169	61.05 267	86.83 122	88.27 206	78.57 113	89.66 115	95.64 31	75.43 175	90.68 216	69.09 230	95.33 156	93.82 113

VDDNet		84.35 142	85.39 126	81.25 222	95.13 33	59.32 286	85.42 144	81.11 286	86.41 29	87.41 154	96.21 19	73.61 196	90.61 219	66.33 250	96.85 95	93.81 116

DROMVSNet		88.01 80	88.32 78	87.09 102	89.28 185	72.03 162	90.31 56	96.31 3	80.88 82	85.12 199	89.67 216	84.47 76	95.46 49	82.56 81	96.26 121	93.77 117

CDPH-MVS		86.17 109	85.54 123	88.05 93	92.25 106	75.45 129	83.85 173	92.01 114	65.91 261	86.19 180	91.75 163	83.77 83	94.98 68	77.43 145	96.71 101	93.73 118

abl_6		93.02 4	93.16 4	92.60 4	94.73 44	88.99 7	93.26 12	94.19 30	89.11 12	94.43 16	95.27 40	91.86 3	95.09 64	87.54 18	98.02 41	93.71 119

Regformer-1		86.00 110	85.50 124	87.49 98	84.18 283	76.90 115	83.52 183	87.94 213	82.18 67	89.19 125	85.07 295	82.28 102	91.89 180	82.40 84	92.72 225	93.69 120

GeoE		85.45 119	85.81 117	84.37 157	90.08 172	67.07 205	85.86 138	91.39 134	72.33 196	87.59 151	90.25 204	84.85 71	92.37 166	78.00 136	91.94 242	93.66 121

DIV-MVS_self_test		80.43 208	80.23 208	81.02 228	79.99 325	59.25 287	77.07 297	87.02 228	67.38 250	86.19 180	89.22 223	63.09 263	90.16 230	76.32 156	95.80 143	93.66 121

cl____		80.42 209	80.23 208	81.02 228	79.99 325	59.25 287	77.07 297	87.02 228	67.37 251	86.18 182	89.21 224	63.08 264	90.16 230	76.31 157	95.80 143	93.65 123

XVG-ACMP-BASELINE		89.98 47	89.84 54	90.41 44	94.91 38	84.50 48	89.49 78	93.98 42	79.68 95	92.09 66	93.89 103	83.80 82	93.10 147	82.67 80	98.04 38	93.64 124

MIMVSNet1		83.63 162	84.59 142	80.74 232	94.06 57	62.77 245	82.72 207	84.53 265	77.57 123	90.34 96	95.92 24	76.88 170	85.83 299	61.88 284	97.42 79	93.62 125

XVG-OURS		89.18 64	88.83 73	90.23 48	94.28 48	86.11 25	85.91 135	93.60 60	80.16 90	89.13 127	93.44 113	83.82 81	90.98 204	83.86 68	95.30 160	93.60 126

CLD-MVS		83.18 170	82.64 175	84.79 148	89.05 189	67.82 202	77.93 284	92.52 103	68.33 239	85.07 200	81.54 334	82.06 106	92.96 150	69.35 225	97.91 51	93.57 127
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
HQP4-MVS										80.56 276			94.61 80			93.56 128

HQP-MVS		84.61 135	84.06 154	86.27 118	91.19 146	70.66 175	84.77 149	92.68 100	73.30 177	80.55 277	90.17 208	72.10 215	94.61 80	77.30 147	94.47 185	93.56 128

VDD-MVS		84.23 148	84.58 143	83.20 188	91.17 149	65.16 222	83.25 193	84.97 260	79.79 93	87.18 156	94.27 77	74.77 185	90.89 209	69.24 226	96.54 107	93.55 130

iter_conf_final		80.36 212	78.88 224	84.79 148	86.29 250	66.36 213	86.95 119	86.25 236	68.16 242	82.09 252	89.48 218	36.59 374	94.51 87	79.83 112	94.30 189	93.50 131

miper_ehance_all_eth		80.34 213	80.04 215	81.24 224	79.82 327	58.95 292	77.66 288	89.66 181	65.75 265	85.99 188	85.11 291	68.29 235	91.42 192	76.03 160	92.03 238	93.33 132

VPNet		80.25 215	81.68 188	75.94 300	92.46 98	47.98 361	76.70 301	81.67 284	73.45 172	84.87 205	92.82 128	74.66 187	86.51 289	61.66 287	96.85 95	93.33 132

IU-MVS					94.18 50	72.64 148		90.82 149	56.98 323	89.67 114				85.78 48	97.92 49	93.28 134

ACMMP_NAP		90.65 31	91.07 38	89.42 64	95.93 16	79.54 81	89.95 63	93.68 56	77.65 121	91.97 70	94.89 51	88.38 28	95.45 50	89.27 3	97.87 53	93.27 135

DeepC-MVS	82.31 4	89.15 65	89.08 67	89.37 65	93.64 69	79.07 85	88.54 97	94.20 28	73.53 171	89.71 112	94.82 54	85.09 67	95.77 30	84.17 65	98.03 40	93.26 136
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	85.71 116	84.83 135	88.37 87	88.78 196	79.72 78	87.15 116	93.50 62	69.17 229	85.80 190	89.56 217	80.76 126	92.13 172	73.21 197	95.51 151	93.25 137
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMH	76.49 14	89.34 60	91.14 34	83.96 169	92.50 97	70.36 178	89.55 74	93.84 50	81.89 71	94.70 13	95.44 35	90.69 9	88.31 267	83.33 73	98.30 26	93.20 138
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MP-MVS		91.14 27	90.91 43	91.83 21	96.18 11	86.88 16	92.20 28	93.03 88	82.59 62	88.52 137	94.37 76	86.74 53	95.41 52	86.32 37	98.21 31	93.19 139
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
diffmvs		80.40 210	80.48 205	80.17 242	79.02 337	60.04 279	77.54 291	90.28 169	66.65 257	82.40 246	87.33 256	73.50 198	87.35 276	77.98 137	89.62 278	93.13 140

CL-MVSNet_self_test		76.81 253	77.38 242	75.12 304	86.90 238	51.34 346	73.20 331	80.63 291	68.30 240	81.80 260	88.40 236	66.92 242	80.90 328	55.35 322	94.90 173	93.12 141

mPP-MVS		91.69 13	91.47 24	92.37 6	96.04 13	88.48 10	92.72 18	92.60 102	83.09 56	91.54 75	94.25 81	87.67 43	95.51 45	87.21 27	98.11 37	93.12 141

ETH3 D test6400		85.09 125	84.87 134	85.75 133	90.80 158	69.34 186	85.90 136	93.31 70	65.43 268	86.11 183	89.95 210	80.92 124	94.86 71	75.90 162	95.57 150	93.05 143

Vis-MVSNet (Re-imp)		77.82 242	77.79 239	77.92 275	88.82 195	51.29 348	83.28 191	71.97 343	74.04 165	82.23 249	89.78 214	57.38 299	89.41 251	57.22 310	95.41 153	93.05 143

tfpnnormal		81.79 190	82.95 170	78.31 267	88.93 193	55.40 318	80.83 246	82.85 274	76.81 130	85.90 189	94.14 88	74.58 188	86.51 289	66.82 248	95.68 149	93.01 145

test_0728_THIRD									85.33 34	93.75 31	94.65 59	87.44 45	95.78 28	87.41 21	98.21 31	92.98 146

MSP-MVS		89.08 67	88.16 79	91.83 21	95.76 18	86.14 24	92.75 17	93.90 46	78.43 114	89.16 126	92.25 150	72.03 219	96.36 2	88.21 8	90.93 262	92.98 146
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
APDe-MVS		91.22 24	91.92 13	89.14 69	92.97 85	78.04 94	92.84 16	94.14 35	83.33 53	93.90 25	95.73 27	88.77 26	96.41 1	87.60 16	97.98 45	92.98 146

ETH3D cwj APD-0.16		87.83 86	87.62 87	88.47 83	91.21 145	78.20 92	87.26 113	94.54 20	72.05 200	88.89 128	92.31 147	83.86 80	94.24 93	81.59 93	96.87 94	92.97 149

HFP-MVS		91.30 21	91.39 25	91.02 33	95.43 29	84.66 46	92.58 22	93.29 73	81.99 68	91.47 76	93.96 98	88.35 30	95.56 39	87.74 11	97.74 60	92.85 150

#test#		90.49 36	90.31 51	91.02 33	95.43 29	84.66 46	90.65 46	93.29 73	77.00 129	91.47 76	93.96 98	88.35 30	95.56 39	84.88 58	97.74 60	92.85 150

test_prior3		86.31 104	86.31 107	86.32 115	90.59 163	71.99 163	83.37 189	92.85 94	75.43 150	84.58 209	91.57 165	81.92 112	94.17 99	79.54 117	96.97 91	92.80 152

test_prior				86.32 115	90.59 163	71.99 163		92.85 94					94.17 99			92.80 152

miper_lstm_enhance		76.45 259	76.10 256	77.51 281	76.72 349	60.97 271	64.69 358	85.04 256	63.98 278	83.20 237	88.22 238	56.67 302	78.79 336	73.22 192	93.12 213	92.78 154

SR-MVS-dyc-post		92.41 6	92.41 7	92.39 5	94.13 55	88.95 8	92.87 14	94.16 31	88.75 16	93.79 29	94.43 69	88.83 24	95.51 45	87.16 28	97.60 68	92.73 155

RE-MVS-def			92.61 5		94.13 55	88.95 8	92.87 14	94.16 31	88.75 16	93.79 29	94.43 69	90.64 11		87.16 28	97.60 68	92.73 155

PHI-MVS		86.38 103	85.81 117	88.08 91	88.44 205	77.34 108	89.35 82	93.05 85	73.15 182	84.76 207	87.70 248	78.87 142	94.18 97	80.67 104	96.29 117	92.73 155

ambc				82.98 192	90.55 165	64.86 223	88.20 99	89.15 190		89.40 123	93.96 98	71.67 222	91.38 195	78.83 124	96.55 106	92.71 158

alignmvs		83.94 157	83.98 156	83.80 171	87.80 216	67.88 201	84.54 157	91.42 133	73.27 180	88.41 140	87.96 242	72.33 214	90.83 211	76.02 161	94.11 193	92.69 159

thres600view7		75.97 262	75.35 264	77.85 278	87.01 236	51.84 344	80.45 248	73.26 335	75.20 154	83.10 239	86.31 272	45.54 346	89.05 254	55.03 325	92.24 234	92.66 160

thres400		75.14 268	74.23 273	77.86 277	86.24 252	52.12 340	79.24 266	73.87 329	73.34 175	81.82 258	84.60 303	46.02 340	88.80 258	51.98 340	90.99 258	92.66 160

CNVR-MVS		87.81 87	87.68 85	88.21 90	92.87 87	77.30 110	85.25 145	91.23 138	77.31 126	87.07 162	91.47 169	82.94 91	94.71 75	84.67 61	96.27 120	92.62 162

Anonymous20240521		80.18 218	81.25 194	76.95 287	83.15 296	60.84 272	82.46 216	85.99 241	68.76 235	86.78 166	93.73 110	59.13 287	77.44 338	73.71 186	97.55 71	92.56 163

CP-MVS		91.67 14	91.58 21	91.96 14	95.29 32	87.62 12	93.38 9	93.36 65	83.16 55	91.06 85	94.00 94	88.26 32	95.71 32	87.28 26	98.39 21	92.55 164

test1172		92.40 7	92.41 7	92.37 6	94.68 45	89.04 6	91.98 32	93.62 57	90.14 11	93.63 36	94.16 87	88.83 24	95.51 45	87.11 30	97.54 74	92.54 165

canonicalmvs		85.50 117	86.14 111	83.58 178	87.97 212	67.13 204	87.55 109	94.32 22	73.44 173	88.47 138	87.54 251	86.45 58	91.06 203	75.76 164	93.76 199	92.54 165

DVP-MVS++		90.07 42	91.09 35	87.00 103	91.55 135	72.64 148	96.19 2	94.10 38	85.33 34	93.49 39	94.64 62	81.12 122	95.88 17	87.41 21	95.94 135	92.48 167

PC_three_1452									58.96 309	90.06 100	91.33 172	80.66 128	93.03 149	75.78 163	95.94 135	92.48 167

MVSTER		77.09 249	75.70 260	81.25 222	75.27 361	61.08 266	77.49 293	85.07 254	60.78 301	86.55 173	88.68 233	43.14 361	90.25 225	73.69 187	90.67 269	92.42 169

ACMM	79.39 9	90.65 31	90.99 40	89.63 59	95.03 35	83.53 51	89.62 73	93.35 66	79.20 103	93.83 28	93.60 112	90.81 8	92.96 150	85.02 56	98.45 19	92.41 170
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MSC_two_6792asdad				88.81 73	91.55 135	77.99 95		91.01 144					96.05 8	87.45 19	98.17 34	92.40 171

No_MVS				88.81 73	91.55 135	77.99 95		91.01 144					96.05 8	87.45 19	98.17 34	92.40 171

MVS_Test		82.47 179	83.22 164	80.22 241	82.62 301	57.75 303	82.54 214	91.96 117	71.16 210	82.89 241	92.52 141	77.41 156	90.50 221	80.04 109	87.84 301	92.40 171

NCCC		87.36 89	86.87 100	88.83 72	92.32 103	78.84 88	86.58 129	91.09 142	78.77 110	84.85 206	90.89 187	80.85 125	95.29 55	81.14 96	95.32 157	92.34 174

miper_enhance_ethall		77.83 241	76.93 248	80.51 236	76.15 354	58.01 300	75.47 316	88.82 193	58.05 315	83.59 232	80.69 338	64.41 254	91.20 197	73.16 198	92.03 238	92.33 175

zzz-MVS		91.27 22	91.26 33	91.29 29	96.59 4	86.29 19	88.94 87	91.81 123	84.07 42	92.00 68	94.40 73	86.63 54	95.28 57	88.59 5	98.31 24	92.30 176

MTAPA		91.52 16	91.60 20	91.29 29	96.59 4	86.29 19	92.02 31	91.81 123	84.07 42	92.00 68	94.40 73	86.63 54	95.28 57	88.59 5	98.31 24	92.30 176

SED-MVS		90.46 37	91.64 19	86.93 104	94.18 50	72.65 146	90.47 53	93.69 54	83.77 46	94.11 23	94.27 77	90.28 15	95.84 23	86.03 44	97.92 49	92.29 178

OPU-MVS				88.27 89	91.89 120	77.83 98	90.47 53				91.22 174	81.12 122	94.68 76	74.48 174	95.35 155	92.29 178

test12				86.57 110	90.74 159	72.63 150		90.69 152		82.76 242		79.20 139	94.80 73		95.32 157	92.27 180

FMVSNet2		81.31 194	81.61 190	80.41 238	86.38 244	58.75 297	83.93 171	86.58 233	72.43 191	87.65 150	92.98 121	63.78 259	90.22 228	66.86 245	93.92 197	92.27 180

CANet		83.79 159	82.85 171	86.63 109	86.17 255	72.21 161	83.76 177	91.43 131	77.24 127	74.39 328	87.45 253	75.36 176	95.42 51	77.03 150	92.83 221	92.25 182

F-COLMAP		84.97 130	83.42 161	89.63 59	92.39 99	83.40 52	88.83 90	91.92 118	73.19 181	80.18 284	89.15 226	77.04 162	93.28 138	65.82 256	92.28 233	92.21 183

SR-MVS		92.23 8	92.34 9	91.91 17	94.89 39	87.85 11	92.51 24	93.87 49	88.20 21	93.24 42	94.02 93	90.15 17	95.67 34	86.82 32	97.34 81	92.19 184

Effi-MVS+		83.90 158	84.01 155	83.57 179	87.22 228	65.61 219	86.55 130	92.40 105	78.64 112	81.34 268	84.18 306	83.65 84	92.93 152	74.22 176	87.87 300	92.17 185

Vis-MVSNet		86.86 95	86.58 103	87.72 95	92.09 112	77.43 107	87.35 112	92.09 112	78.87 108	84.27 222	94.05 91	78.35 147	93.65 118	80.54 106	91.58 248	92.08 186
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
test_241102_TWO								93.71 53	83.77 46	93.49 39	94.27 77	89.27 22	95.84 23	86.03 44	97.82 54	92.04 187

test_0728_SECOND				86.79 107	94.25 49	72.45 156	90.54 50	94.10 38					95.88 17	86.42 34	97.97 46	92.02 188

mvs-test1		84.55 137	82.12 182	91.84 20	87.13 230	89.54 4	85.05 148	88.42 199	74.57 160	80.60 274	82.98 316	78.49 145	93.98 107	72.04 204	89.77 276	92.00 189

new-patchmatchnet		70.10 309	73.37 282	60.29 356	81.23 312	16.95 387	59.54 366	74.62 322	62.93 282	80.97 269	87.93 244	62.83 268	71.90 352	55.24 323	95.01 170	92.00 189

DeepPCF-MVS	81.24 5	87.28 90	86.21 110	90.49 43	91.48 139	84.90 41	83.41 188	92.38 107	70.25 221	89.35 124	90.68 194	82.85 92	94.57 82	79.55 116	95.95 134	92.00 189

Anonymous202405211		80.51 207	81.19 197	78.49 264	88.48 203	57.26 306	76.63 302	82.49 276	81.21 78	84.30 220	92.24 151	67.99 236	86.24 293	62.22 279	95.13 164	91.98 192

EIA-MVS		82.19 183	81.23 196	85.10 144	87.95 213	69.17 192	83.22 196	93.33 67	70.42 217	78.58 296	79.77 350	77.29 157	94.20 96	71.51 207	88.96 285	91.93 193

MCST-MVS		84.36 141	83.93 157	85.63 135	91.59 129	71.58 170	83.52 183	92.13 111	61.82 290	83.96 227	89.75 215	79.93 137	93.46 132	78.33 129	94.34 188	91.87 194

testtj		89.51 57	89.48 60	89.59 61	92.26 105	80.80 71	90.14 59	93.54 61	83.37 52	90.57 94	92.55 139	84.99 68	96.15 5	81.26 94	96.61 104	91.83 195

test_0402		88.65 72	89.58 59	85.88 130	92.55 95	72.22 160	84.01 167	89.44 186	88.63 18	94.38 18	95.77 26	86.38 60	93.59 125	79.84 111	95.21 161	91.82 196

DeepC-MVS_fast	80.27 8	86.23 106	85.65 122	87.96 94	91.30 142	76.92 114	87.19 114	91.99 115	70.56 215	84.96 202	90.69 193	80.01 135	95.14 62	78.37 127	95.78 145	91.82 196
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
FA-MVS(test-final)		83.13 172	83.02 169	83.43 181	86.16 257	66.08 215	88.00 102	88.36 202	75.55 148	85.02 201	92.75 132	65.12 252	92.50 162	74.94 173	91.30 252	91.72 198

FMVSNet3		78.80 231	78.55 231	79.57 250	82.89 300	56.89 310	81.76 229	85.77 243	69.04 232	86.00 185	90.44 200	51.75 321	90.09 236	65.95 252	93.34 207	91.72 198

DPE-MVS		90.53 35	91.08 36	88.88 71	93.38 75	78.65 90	89.15 84	94.05 40	84.68 40	93.90 25	94.11 90	88.13 36	96.30 3	84.51 63	97.81 55	91.70 200
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
CPTT-MVS		89.39 59	88.98 70	90.63 41	95.09 34	86.95 15	92.09 30	92.30 108	79.74 94	87.50 153	92.38 143	81.42 119	93.28 138	83.07 75	97.24 84	91.67 201

MDA-MVSNet-bldmvs		77.47 245	76.90 249	79.16 255	79.03 336	64.59 224	66.58 354	75.67 317	73.15 182	88.86 129	88.99 229	66.94 241	81.23 327	64.71 263	88.22 297	91.64 202

PAPM_NR		83.23 169	83.19 166	83.33 184	90.90 155	65.98 216	88.19 100	90.78 150	78.13 118	80.87 272	87.92 245	73.49 200	92.42 163	70.07 220	88.40 291	91.60 203

PCF-MVS	74.62 15	82.15 184	80.92 200	85.84 131	89.43 182	72.30 158	80.53 247	91.82 122	57.36 321	87.81 149	89.92 212	77.67 153	93.63 120	58.69 302	95.08 167	91.58 204
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
EPNet		80.37 211	78.41 234	86.23 119	76.75 348	73.28 141	87.18 115	77.45 306	76.24 135	68.14 351	88.93 230	65.41 250	93.85 111	69.47 224	96.12 126	91.55 205
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Fast-Effi-MVS+		81.04 198	80.57 201	82.46 206	87.50 223	63.22 239	78.37 280	89.63 182	68.01 243	81.87 256	82.08 329	82.31 99	92.65 159	67.10 244	88.30 296	91.51 206

mvs_anonymous		78.13 239	78.76 228	76.23 299	79.24 334	50.31 354	78.69 275	84.82 262	61.60 294	83.09 240	92.82 128	73.89 194	87.01 278	68.33 239	86.41 312	91.37 207

SD-MVS		88.96 69	89.88 53	86.22 120	91.63 128	77.07 113	89.82 66	93.77 51	78.90 107	92.88 48	92.29 148	86.11 62	90.22 228	86.24 41	97.24 84	91.36 208
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
D2MVS		76.84 252	75.67 261	80.34 239	80.48 323	62.16 257	73.50 328	84.80 263	57.61 319	82.24 248	87.54 251	51.31 322	87.65 272	70.40 219	93.19 212	91.23 209

patch_mono-2		78.89 227	79.39 220	77.41 283	84.78 269	68.11 198	75.60 312	83.11 271	60.96 299	79.36 289	89.89 213	75.18 178	72.97 349	73.32 191	92.30 230	91.15 210

EGC-MVSNET		74.79 276	69.99 310	89.19 68	94.89 39	87.00 14	91.89 36	86.28 235	1.09 383	2.23 385	95.98 23	81.87 114	89.48 245	79.76 113	95.96 133	91.10 211

ETV-MVS		84.31 143	83.91 158	85.52 137	88.58 201	70.40 177	84.50 159	93.37 64	78.76 111	84.07 226	78.72 353	80.39 131	95.13 63	73.82 185	92.98 218	91.04 212

agg_prior1		85.72 115	85.20 128	87.28 101	91.58 132	77.69 100	83.69 179	90.30 165	66.29 259	84.32 216	91.07 180	82.13 104	93.18 141	81.02 97	96.36 115	90.98 213

VNet		79.31 224	80.27 207	76.44 294	87.92 214	53.95 327	75.58 314	84.35 266	74.39 163	82.23 249	90.72 192	72.84 209	84.39 311	60.38 296	93.98 196	90.97 214

Fast-Effi-MVS+-dtu		82.54 178	81.41 193	85.90 129	85.60 260	76.53 120	83.07 198	89.62 183	73.02 184	79.11 293	83.51 311	80.74 127	90.24 227	68.76 233	89.29 280	90.94 215

Patchmtry		76.56 257	77.46 240	73.83 310	79.37 333	46.60 367	82.41 218	76.90 308	73.81 168	85.56 194	92.38 143	48.07 332	83.98 314	63.36 273	95.31 159	90.92 216

CANet_DTU		77.81 243	77.05 246	80.09 243	81.37 310	59.90 281	83.26 192	88.29 205	69.16 230	67.83 354	83.72 309	60.93 272	89.47 246	69.22 228	89.70 277	90.88 217

train_agg		85.98 112	85.28 127	88.07 92	92.34 101	79.70 79	83.94 169	90.32 162	65.79 262	84.49 211	90.97 183	81.93 110	93.63 120	81.21 95	96.54 107	90.88 217

114514_t		83.10 173	82.54 178	84.77 150	92.90 86	69.10 193	86.65 127	90.62 155	54.66 332	81.46 265	90.81 190	76.98 163	94.38 89	72.62 200	96.18 122	90.82 219

LCM-MVSNet-Re		83.48 165	85.06 130	78.75 259	85.94 259	55.75 317	80.05 252	94.27 23	76.47 132	96.09 5	94.54 64	83.31 88	89.75 244	59.95 297	94.89 174	90.75 220

FMVS2		75.72 265	75.20 265	77.27 284	75.01 364	69.47 184	78.93 270	84.88 261	46.67 363	87.08 161	87.84 246	50.44 327	71.62 353	77.42 146	88.53 290	90.72 221

hse-mvs2		83.47 166	81.81 187	88.47 83	91.03 152	82.27 61	82.61 209	83.69 267	71.27 206	86.70 169	86.05 276	63.04 265	92.41 164	78.26 131	93.62 205	90.71 222

DP-MVS		88.60 73	89.01 68	87.36 100	91.30 142	77.50 103	87.55 109	92.97 91	87.95 22	89.62 116	92.87 127	84.56 73	93.89 110	77.65 140	96.62 103	90.70 223

LFMVS		80.15 219	80.56 202	78.89 256	89.19 188	55.93 314	85.22 146	73.78 331	82.96 58	84.28 221	92.72 133	57.38 299	90.07 237	63.80 269	95.75 146	90.68 224

PAPR		78.84 229	78.10 237	81.07 226	85.17 265	60.22 278	82.21 225	90.57 156	62.51 285	75.32 323	84.61 302	74.99 180	92.30 169	59.48 300	88.04 298	90.68 224

AUN-MVS		81.18 196	78.78 227	88.39 86	90.93 154	82.14 62	82.51 215	83.67 268	64.69 276	80.29 280	85.91 279	51.07 323	92.38 165	76.29 158	93.63 204	90.65 226

test9_res														80.83 101	96.45 112	90.57 227

UGNet		82.78 174	81.64 189	86.21 122	86.20 254	76.24 125	86.86 120	85.68 244	77.07 128	73.76 331	92.82 128	69.64 227	91.82 183	69.04 231	93.69 202	90.56 228
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
DVP-MVS		90.06 43	91.32 30	86.29 117	94.16 53	72.56 152	90.54 50	91.01 144	83.61 49	93.75 31	94.65 59	89.76 19	95.78 28	86.42 34	97.97 46	90.55 229
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
DELS-MVS		81.44 193	81.25 194	82.03 209	84.27 279	62.87 244	76.47 305	92.49 104	70.97 211	81.64 263	83.83 308	75.03 179	92.70 157	74.29 175	92.22 236	90.51 230
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 56	89.63 57	89.26 67	92.57 94	81.34 68	90.19 58	93.08 84	80.87 83	91.13 83	93.19 116	86.22 61	95.97 12	82.23 86	97.18 86	90.45 231
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
CSCG		86.26 105	86.47 104	85.60 136	90.87 156	74.26 136	87.98 103	91.85 120	80.35 87	89.54 122	88.01 241	79.09 140	92.13 172	75.51 165	95.06 168	90.41 232

DP-MVS Recon		84.05 153	83.22 164	86.52 112	91.73 127	75.27 130	83.23 195	92.40 105	72.04 201	82.04 253	88.33 237	77.91 151	93.95 108	66.17 251	95.12 166	90.34 233

IterMVS-SCA-FT		80.64 205	79.41 219	84.34 160	83.93 287	69.66 182	76.28 307	81.09 287	72.43 191	86.47 179	90.19 206	60.46 275	93.15 145	77.45 144	86.39 313	90.22 234

agg_prior2														79.68 115	96.16 123	90.22 234

HPM-MVS++		88.93 70	88.45 77	90.38 45	94.92 37	85.85 30	89.70 68	91.27 137	78.20 116	86.69 171	92.28 149	80.36 132	95.06 66	86.17 42	96.49 109	90.22 234

HyFIR lowres test		75.12 270	72.66 289	82.50 205	91.44 141	65.19 221	72.47 333	87.31 218	46.79 362	80.29 280	84.30 305	52.70 318	92.10 175	51.88 344	86.73 309	90.22 234

PVSNet_BlendedMVS		78.80 231	77.84 238	81.65 218	84.43 273	63.41 235	79.49 262	90.44 158	61.70 293	75.43 321	87.07 262	69.11 231	91.44 190	60.68 294	92.24 234	90.11 238

MVS_111021_HR		84.63 134	84.34 151	85.49 139	90.18 171	75.86 127	79.23 268	87.13 223	73.35 174	85.56 194	89.34 221	83.60 85	90.50 221	76.64 153	94.05 195	90.09 239

FE-MVS		79.98 222	78.86 225	83.36 183	86.47 241	66.45 211	89.73 67	84.74 264	72.80 186	84.22 225	91.38 171	44.95 355	93.60 124	63.93 268	91.50 249	90.04 240

GA-MVS		75.83 263	74.61 268	79.48 252	81.87 304	59.25 287	73.42 329	82.88 273	68.68 236	79.75 285	81.80 331	50.62 325	89.46 247	66.85 246	85.64 318	89.72 241

h-mvs33		84.25 146	82.76 172	88.72 77	91.82 126	82.60 60	84.00 168	84.98 259	71.27 206	86.70 169	90.55 198	63.04 265	93.92 109	78.26 131	94.20 192	89.63 242

ppachtmachnet_test		74.73 277	74.00 275	76.90 289	80.71 320	56.89 310	71.53 337	78.42 301	58.24 313	79.32 291	82.92 320	57.91 296	84.26 312	65.60 257	91.36 251	89.56 243

MG-MVS		80.32 214	80.94 199	78.47 265	88.18 209	52.62 338	82.29 221	85.01 258	72.01 202	79.24 292	92.54 140	69.36 229	93.36 137	70.65 215	89.19 283	89.45 244

PLC	73.85 16	82.09 185	80.31 206	87.45 99	90.86 157	80.29 74	85.88 137	90.65 153	68.17 241	76.32 311	86.33 270	73.12 206	92.61 160	61.40 289	90.02 275	89.44 245
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
ab-mvs		79.67 223	80.56 202	76.99 286	88.48 203	56.93 308	84.70 152	86.06 239	68.95 233	80.78 273	93.08 118	75.30 177	84.62 309	56.78 311	90.90 263	89.43 246

thisisatest0515		73.00 290	70.52 304	80.46 237	81.45 308	59.90 281	73.16 332	74.31 326	57.86 316	76.08 315	77.78 356	37.60 372	92.12 174	65.00 260	91.45 250	89.35 247

thres100view900		75.45 266	75.05 266	76.66 293	87.27 226	51.88 343	81.07 242	73.26 335	75.68 146	83.25 236	86.37 269	45.54 346	88.80 258	51.98 340	90.99 258	89.31 248

tfpn200view9		74.86 274	74.23 273	76.74 292	86.24 252	52.12 340	79.24 266	73.87 329	73.34 175	81.82 258	84.60 303	46.02 340	88.80 258	51.98 340	90.99 258	89.31 248

3Dnovator	80.37 7	84.80 132	84.71 139	85.06 145	86.36 247	74.71 133	88.77 92	90.00 176	75.65 147	84.96 202	93.17 117	74.06 191	91.19 198	78.28 130	91.09 254	89.29 250

ET-MVSNet_ETH3D		75.28 267	72.77 287	82.81 198	83.03 298	68.11 198	77.09 296	76.51 312	60.67 303	77.60 305	80.52 342	38.04 370	91.15 200	70.78 212	90.68 268	89.17 251

CNLPA		83.55 164	83.10 168	84.90 146	89.34 184	83.87 50	84.54 157	88.77 194	79.09 104	83.54 234	88.66 234	74.87 181	81.73 325	66.84 247	92.29 232	89.11 252

test_yl		78.71 233	78.51 232	79.32 253	84.32 277	58.84 294	78.38 278	85.33 248	75.99 140	82.49 244	86.57 266	58.01 293	90.02 239	62.74 276	92.73 223	89.10 253

DCV-MVSNet		78.71 233	78.51 232	79.32 253	84.32 277	58.84 294	78.38 278	85.33 248	75.99 140	82.49 244	86.57 266	58.01 293	90.02 239	62.74 276	92.73 223	89.10 253

CMPMVS	59.41 20	75.12 270	73.57 278	79.77 245	75.84 356	67.22 203	81.21 240	82.18 278	50.78 354	76.50 308	87.66 249	55.20 312	82.99 319	62.17 282	90.64 272	89.09 255
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MVSFormer		82.23 182	81.57 192	84.19 165	85.54 262	69.26 188	91.98 32	90.08 174	71.54 204	76.23 312	85.07 295	58.69 290	94.27 90	86.26 38	88.77 287	89.03 256

jason		77.42 246	75.75 259	82.43 207	87.10 234	69.27 187	77.99 283	81.94 281	51.47 350	77.84 301	85.07 295	60.32 277	89.00 255	70.74 214	89.27 282	89.03 256
jason: jason.
TSAR-MVS + GP.		83.95 156	82.69 174	87.72 95	89.27 186	81.45 67	83.72 178	81.58 285	74.73 158	85.66 191	86.06 275	72.56 213	92.69 158	75.44 167	95.21 161	89.01 258

QAPM		82.59 177	82.59 177	82.58 202	86.44 242	66.69 209	89.94 64	90.36 161	67.97 245	84.94 204	92.58 138	72.71 210	92.18 171	70.63 216	87.73 302	88.85 259

baseline2		69.77 313	66.89 323	78.41 266	79.51 330	58.09 299	76.23 308	69.57 355	57.50 320	64.82 366	77.45 359	46.02 340	88.44 264	53.08 333	77.83 360	88.70 260

LF4IMVS		82.75 175	81.93 186	85.19 141	82.08 302	80.15 75	85.53 142	88.76 195	68.01 243	85.58 193	87.75 247	71.80 220	86.85 283	74.02 181	93.87 198	88.58 261

MVS_111021_LR		84.28 145	83.76 159	85.83 132	89.23 187	83.07 55	80.99 243	83.56 269	72.71 188	86.07 184	89.07 228	81.75 116	86.19 294	77.11 149	93.36 206	88.24 262

EG-PatchMatch MVS		84.08 152	84.11 153	83.98 168	92.22 108	72.61 151	82.20 227	87.02 228	72.63 189	88.86 129	91.02 181	78.52 143	91.11 201	73.41 190	91.09 254	88.21 263

lupinMVS		76.37 260	74.46 271	82.09 208	85.54 262	69.26 188	76.79 299	80.77 290	50.68 356	76.23 312	82.82 321	58.69 290	88.94 256	69.85 221	88.77 287	88.07 264

cascas		76.29 261	74.81 267	80.72 234	84.47 272	62.94 242	73.89 326	87.34 217	55.94 326	75.16 325	76.53 364	63.97 257	91.16 199	65.00 260	90.97 261	88.06 265

TAMVS		78.08 240	76.36 253	83.23 186	90.62 162	72.87 144	79.08 269	80.01 295	61.72 292	81.35 267	86.92 264	63.96 258	88.78 261	50.61 345	93.01 217	88.04 266

PVSNet_Blended_VisFu		81.55 192	80.49 204	84.70 153	91.58 132	73.24 143	84.21 161	91.67 126	62.86 283	80.94 270	87.16 259	67.27 240	92.87 155	69.82 222	88.94 286	87.99 267

FMVSNet5		72.10 297	71.69 297	73.32 311	81.57 307	53.02 334	76.77 300	78.37 302	63.31 279	76.37 309	91.85 157	36.68 373	78.98 334	47.87 357	92.45 228	87.95 268

CDS-MVSNet		77.32 247	75.40 262	83.06 190	89.00 191	72.48 155	77.90 285	82.17 279	60.81 300	78.94 294	83.49 312	59.30 285	88.76 262	54.64 328	92.37 229	87.93 269
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
pmmvs-eth3d		78.42 237	77.04 247	82.57 204	87.44 224	74.41 135	80.86 245	79.67 296	55.68 327	84.69 208	90.31 203	60.91 273	85.42 302	62.20 280	91.59 247	87.88 270

baseline1		73.26 286	73.54 279	72.43 319	84.92 267	47.79 362	79.89 255	74.00 327	65.93 260	78.81 295	86.28 273	56.36 305	81.63 326	56.63 312	79.04 358	87.87 271

test20.03		73.75 284	74.59 270	71.22 323	81.11 313	51.12 350	70.15 342	72.10 342	70.42 217	80.28 282	91.50 168	64.21 256	74.72 348	46.96 361	94.58 183	87.82 272

BH-RMVSNet		80.53 206	80.22 210	81.49 220	87.19 229	66.21 214	77.79 287	86.23 237	74.21 164	83.69 229	88.50 235	73.25 205	90.75 213	63.18 275	87.90 299	87.52 273

IterMVS		76.91 251	76.34 254	78.64 261	80.91 315	64.03 231	76.30 306	79.03 299	64.88 275	83.11 238	89.16 225	59.90 281	84.46 310	68.61 236	85.15 323	87.42 274
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
OpenMVS	76.72 13	81.98 188	82.00 185	81.93 210	84.42 275	68.22 197	88.50 98	89.48 185	66.92 254	81.80 260	91.86 156	72.59 212	90.16 230	71.19 209	91.25 253	87.40 275

1112_ss		74.82 275	73.74 276	78.04 273	89.57 179	60.04 279	76.49 304	87.09 227	54.31 333	73.66 332	79.80 348	60.25 278	86.76 287	58.37 303	84.15 333	87.32 276

Test_1112_low_res		73.90 283	73.08 284	76.35 295	90.35 167	55.95 313	73.40 330	86.17 238	50.70 355	73.14 333	85.94 277	58.31 292	85.90 298	56.51 313	83.22 337	87.20 277

MVS_0304		78.17 238	77.23 245	80.99 230	84.13 285	69.07 194	81.39 236	80.81 289	76.28 134	67.53 356	89.11 227	62.87 267	86.77 285	60.90 293	92.01 241	87.13 278

UnsupCasMVSNet_eth		71.63 301	72.30 294	69.62 328	76.47 351	52.70 337	70.03 343	80.97 288	59.18 308	79.36 289	88.21 239	60.50 274	69.12 359	58.33 305	77.62 362	87.04 279

testgi		72.36 294	74.61 268	65.59 343	80.56 322	42.82 377	68.29 347	73.35 334	66.87 255	81.84 257	89.93 211	72.08 217	66.92 366	46.05 363	92.54 227	87.01 280

xiu_mvs_v1_base_debu		80.84 201	80.14 212	82.93 194	88.31 206	71.73 166	79.53 259	87.17 220	65.43 268	79.59 286	82.73 323	76.94 164	90.14 233	73.22 192	88.33 292	86.90 281

xiu_mvs_v1_base		80.84 201	80.14 212	82.93 194	88.31 206	71.73 166	79.53 259	87.17 220	65.43 268	79.59 286	82.73 323	76.94 164	90.14 233	73.22 192	88.33 292	86.90 281

xiu_mvs_v1_base_debi		80.84 201	80.14 212	82.93 194	88.31 206	71.73 166	79.53 259	87.17 220	65.43 268	79.59 286	82.73 323	76.94 164	90.14 233	73.22 192	88.33 292	86.90 281

MSDG		80.06 221	79.99 216	80.25 240	83.91 288	68.04 200	77.51 292	89.19 189	77.65 121	81.94 254	83.45 313	76.37 172	86.31 292	63.31 274	86.59 310	86.41 284

OpenMVS_ROB	70.19 17	77.77 244	77.46 240	78.71 260	84.39 276	61.15 265	81.18 241	82.52 275	62.45 287	83.34 235	87.37 254	66.20 245	88.66 263	64.69 264	85.02 324	86.32 285

TinyColmap		81.25 195	82.34 181	77.99 274	85.33 264	60.68 275	82.32 220	88.33 204	71.26 208	86.97 164	92.22 152	77.10 161	86.98 281	62.37 278	95.17 163	86.31 286

CHOSEN 1792x2688		72.45 293	70.56 303	78.13 271	90.02 177	63.08 240	68.72 346	83.16 270	42.99 373	75.92 316	85.46 285	57.22 301	85.18 305	49.87 349	81.67 346	86.14 287

YYNet1		70.06 310	70.44 305	68.90 331	73.76 367	53.42 332	58.99 369	67.20 360	58.42 312	87.10 159	85.39 288	59.82 282	67.32 363	59.79 298	83.50 336	85.96 288

EPNet_dtu		72.87 291	71.33 302	77.49 282	77.72 342	60.55 276	82.35 219	75.79 315	66.49 258	58.39 378	81.06 337	53.68 315	85.98 296	53.55 331	92.97 219	85.95 289
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MDA-MVSNet_test_wron		70.05 311	70.44 305	68.88 332	73.84 366	53.47 330	58.93 370	67.28 359	58.43 311	87.09 160	85.40 287	59.80 283	67.25 364	59.66 299	83.54 335	85.92 290

XXY-MVS		74.44 280	76.19 255	69.21 330	84.61 271	52.43 339	71.70 336	77.18 307	60.73 302	80.60 274	90.96 185	75.44 174	69.35 358	56.13 315	88.33 292	85.86 291

DPM-MVS		80.10 220	79.18 222	82.88 197	90.71 161	69.74 180	78.87 273	90.84 148	60.29 305	75.64 320	85.92 278	67.28 239	93.11 146	71.24 208	91.79 243	85.77 292

原ACMM1				84.60 154	92.81 92	74.01 137		91.50 129	62.59 284	82.73 243	90.67 195	76.53 171	94.25 92	69.24 226	95.69 148	85.55 293

pmmvs4		74.92 273	72.98 286	80.73 233	84.95 266	71.71 169	76.23 308	77.59 305	52.83 340	77.73 304	86.38 268	56.35 306	84.97 306	57.72 309	87.05 307	85.51 294

MAR-MVS		80.24 216	78.74 229	84.73 151	86.87 240	78.18 93	85.75 139	87.81 214	65.67 267	77.84 301	78.50 354	73.79 195	90.53 220	61.59 288	90.87 264	85.49 295
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
our_test_3		71.85 298	71.59 298	72.62 317	80.71 320	53.78 328	69.72 344	71.71 347	58.80 310	78.03 298	80.51 343	56.61 304	78.84 335	62.20 280	86.04 316	85.23 296

USDC		76.63 255	76.73 251	76.34 296	83.46 291	57.20 307	80.02 253	88.04 210	52.14 346	83.65 231	91.25 173	63.24 262	86.65 288	54.66 327	94.11 193	85.17 297

HY-MVS	64.64 18	73.03 289	72.47 293	74.71 306	83.36 292	54.19 325	82.14 228	81.96 280	56.76 325	69.57 348	86.21 274	60.03 279	84.83 308	49.58 350	82.65 342	85.11 298

MVP-Stereo		75.81 264	73.51 280	82.71 199	89.35 183	73.62 138	80.06 251	85.20 251	60.30 304	73.96 330	87.94 243	57.89 297	89.45 248	52.02 339	74.87 367	85.06 299
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
IB-MVS	62.13 19	71.64 300	68.97 314	79.66 249	80.80 319	62.26 255	73.94 325	76.90 308	63.27 280	68.63 350	76.79 362	33.83 377	91.84 182	59.28 301	87.26 305	84.88 300
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		70.73 305	70.07 308	72.72 316	77.03 347	52.73 336	74.14 323	75.65 318	50.36 358	72.17 338	85.37 289	55.42 311	80.67 330	52.86 337	87.59 304	84.77 301

MSLP-MVS++		85.00 129	86.03 113	81.90 211	91.84 124	71.56 171	86.75 126	93.02 89	75.95 142	87.12 157	89.39 220	77.98 149	89.40 252	77.46 143	94.78 177	84.75 302

无先验							82.81 206	85.62 245	58.09 314				91.41 193	67.95 242		84.48 303

PAPM		71.77 299	70.06 309	76.92 288	86.39 243	53.97 326	76.62 303	86.62 232	53.44 337	63.97 368	84.73 301	57.79 298	92.34 167	39.65 373	81.33 349	84.45 304

PVSNet_Blended		76.49 258	75.40 262	79.76 246	84.43 273	63.41 235	75.14 318	90.44 158	57.36 321	75.43 321	78.30 355	69.11 231	91.44 190	60.68 294	87.70 303	84.42 305

thres200		72.34 295	71.55 300	74.70 307	83.48 290	51.60 345	75.02 319	73.71 332	70.14 223	78.56 297	80.57 341	46.20 338	88.20 268	46.99 360	89.29 280	84.32 306

AdaColmap		83.66 161	83.69 160	83.57 179	90.05 175	72.26 159	86.29 134	90.00 176	78.19 117	81.65 262	87.16 259	83.40 87	94.24 93	61.69 286	94.76 180	84.21 307

EU-MVSNet		75.12 270	74.43 272	77.18 285	83.11 297	59.48 285	85.71 141	82.43 277	39.76 377	85.64 192	88.76 231	44.71 357	87.88 270	73.86 184	85.88 317	84.16 308

GSMVS																83.88 309

sam_mvs1												46.11 339				83.88 309

SCA		73.32 285	72.57 291	75.58 302	81.62 306	55.86 315	78.89 272	71.37 348	61.73 291	74.93 326	83.42 314	60.46 275	87.01 278	58.11 307	82.63 344	83.88 309

CR-MVSNet		74.00 282	73.04 285	76.85 291	79.58 328	62.64 247	82.58 211	76.90 308	50.50 357	75.72 318	92.38 143	48.07 332	84.07 313	68.72 235	82.91 340	83.85 312

RPMNet		78.88 228	78.28 235	80.68 235	79.58 328	62.64 247	82.58 211	94.16 31	74.80 157	75.72 318	92.59 136	48.69 330	95.56 39	73.48 189	82.91 340	83.85 312

MDTV_nov1_ep13_2view						27.60 386	70.76 339		46.47 365	61.27 370		45.20 352		49.18 351		83.75 314

旧先验1					91.97 115	71.77 165		81.78 283			91.84 158	73.92 193			93.65 203	83.61 315

N_pmnet		70.20 307	68.80 316	74.38 308	80.91 315	84.81 42	59.12 368	76.45 313	55.06 330	75.31 324	82.36 326	55.74 308	54.82 377	47.02 359	87.24 306	83.52 316

ADS-MVSNet2		65.87 329	63.64 335	72.55 318	73.16 370	56.92 309	67.10 352	74.81 321	49.74 359	66.04 359	82.97 317	46.71 335	77.26 339	42.29 368	69.96 374	83.46 317

ADS-MVSNet		61.90 336	62.19 339	61.03 355	73.16 370	36.42 381	67.10 352	61.75 371	49.74 359	66.04 359	82.97 317	46.71 335	63.21 373	42.29 368	69.96 374	83.46 317

CostFormer		69.98 312	68.68 317	73.87 309	77.14 345	50.72 352	79.26 265	74.51 324	51.94 348	70.97 344	84.75 300	45.16 354	87.49 274	55.16 324	79.23 356	83.40 319

PS-MVSNAJ		77.04 250	76.53 252	78.56 262	87.09 235	61.40 261	75.26 317	87.13 223	61.25 295	74.38 329	77.22 361	76.94 164	90.94 205	64.63 265	84.83 329	83.35 320

xiu_mvs_v2_base		77.19 248	76.75 250	78.52 263	87.01 236	61.30 263	75.55 315	87.12 226	61.24 296	74.45 327	78.79 352	77.20 158	90.93 206	64.62 266	84.80 330	83.32 321

PatchmatchNet		69.71 314	68.83 315	72.33 320	77.66 343	53.60 329	79.29 264	69.99 353	57.66 318	72.53 336	82.93 319	46.45 337	80.08 333	60.91 292	72.09 370	83.31 322
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
Anonymous20231206		71.38 302	71.88 296	69.88 326	86.31 248	54.37 324	70.39 341	74.62 322	52.57 342	76.73 307	88.76 231	59.94 280	72.06 351	44.35 366	93.23 211	83.23 323

tpm		67.95 319	68.08 320	67.55 338	78.74 339	43.53 375	75.60 312	67.10 363	54.92 331	72.23 337	88.10 240	42.87 362	75.97 343	52.21 338	80.95 352	83.15 324

PMVS	80.48 6	90.08 41	90.66 47	88.34 88	96.71 3	92.97 1	90.31 56	89.57 184	88.51 19	90.11 99	95.12 47	90.98 7	88.92 257	77.55 142	97.07 89	83.13 325
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
tpm2		68.45 318	66.83 324	73.30 312	78.93 338	48.50 358	79.76 256	71.76 345	47.50 361	69.92 347	83.60 310	42.07 363	88.40 265	48.44 355	79.51 353	83.01 326

TR-MVS		76.77 254	75.79 258	79.72 247	86.10 258	65.79 218	77.14 295	83.02 272	65.20 273	81.40 266	82.10 327	66.30 244	90.73 215	55.57 319	85.27 321	82.65 327

1314		73.22 287	72.56 292	75.20 303	80.41 324	57.84 301	81.64 232	85.36 247	51.68 349	73.10 334	76.65 363	61.45 271	85.19 304	63.54 271	79.21 357	82.59 328

WTY-MVS		67.91 320	68.35 318	66.58 341	80.82 318	48.12 360	65.96 355	72.60 338	53.67 336	71.20 342	81.68 333	58.97 288	69.06 360	48.57 353	81.67 346	82.55 329

MIMVSNet		71.09 303	71.59 298	69.57 329	87.23 227	50.07 355	78.91 271	71.83 344	60.20 306	71.26 341	91.76 162	55.08 313	76.09 342	41.06 371	87.02 308	82.54 330

BH-untuned		80.96 199	80.99 198	80.84 231	88.55 202	68.23 196	80.33 250	88.46 198	72.79 187	86.55 173	86.76 265	74.72 186	91.77 184	61.79 285	88.99 284	82.52 331

API-MVS		82.28 181	82.61 176	81.30 221	86.29 250	69.79 179	88.71 93	87.67 215	78.42 115	82.15 251	84.15 307	77.98 149	91.59 186	65.39 258	92.75 222	82.51 332

Gipuma		84.44 140	86.33 106	78.78 258	84.20 282	73.57 139	89.55 74	90.44 158	84.24 41	84.38 213	94.89 51	76.35 173	80.40 331	76.14 159	96.80 99	82.36 333
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PatchT		70.52 306	72.76 288	63.79 348	79.38 332	33.53 383	77.63 289	65.37 366	73.61 170	71.77 339	92.79 131	44.38 358	75.65 345	64.53 267	85.37 320	82.18 334

tpmvs		70.16 308	69.56 312	71.96 321	74.71 365	48.13 359	79.63 257	75.45 320	65.02 274	70.26 345	81.88 330	45.34 351	85.68 300	58.34 304	75.39 366	82.08 335

1121		80.86 200	79.81 217	84.02 166	93.93 60	78.70 89	81.64 232	80.18 293	55.43 329	83.67 230	91.15 177	71.29 223	91.41 193	67.95 242	93.06 215	81.96 336

新几何1				82.95 193	93.96 59	78.56 91		80.24 292	55.45 328	83.93 228	91.08 179	71.19 224	88.33 266	65.84 255	93.07 214	81.95 337

Patchmatch-test		65.91 328	67.38 321	61.48 354	75.51 358	43.21 376	68.84 345	63.79 368	62.48 286	72.80 335	83.42 314	44.89 356	59.52 376	48.27 356	86.45 311	81.70 338

UnsupCasMVSNet_bld		69.21 316	69.68 311	67.82 337	79.42 331	51.15 349	67.82 351	75.79 315	54.15 334	77.47 306	85.36 290	59.26 286	70.64 355	48.46 354	79.35 355	81.66 339

PVSNet	58.17 21	66.41 326	65.63 331	68.75 333	81.96 303	49.88 356	62.19 364	72.51 340	51.03 352	68.04 352	75.34 367	50.84 324	74.77 346	45.82 364	82.96 338	81.60 340

Patchmatch-RL test		74.48 278	73.68 277	76.89 290	84.83 268	66.54 210	72.29 334	69.16 357	57.70 317	86.76 167	86.33 270	45.79 345	82.59 320	69.63 223	90.65 271	81.54 341

test0.0.03 1		64.66 332	64.36 333	65.57 344	75.03 363	46.89 366	64.69 358	61.58 373	62.43 288	71.18 343	77.54 357	43.41 359	68.47 361	40.75 372	82.65 342	81.35 342

test-LLR		67.21 321	66.74 325	68.63 334	76.45 352	55.21 320	67.89 348	67.14 361	62.43 288	65.08 363	72.39 369	43.41 359	69.37 356	61.00 290	84.89 327	81.31 343

test-mter		65.00 331	63.79 334	68.63 334	76.45 352	55.21 320	67.89 348	67.14 361	50.98 353	65.08 363	72.39 369	28.27 384	69.37 356	61.00 290	84.89 327	81.31 343

test222					93.31 77	76.54 118	79.38 263	77.79 304	52.59 341	82.36 247	90.84 189	66.83 243			91.69 245	81.25 345

sss		66.92 322	67.26 322	65.90 342	77.23 344	51.10 351	64.79 357	71.72 346	52.12 347	70.13 346	80.18 345	57.96 295	65.36 371	50.21 346	81.01 351	81.25 345

tpm cat1		66.76 325	65.21 332	71.42 322	77.09 346	50.62 353	78.01 282	73.68 333	44.89 368	68.64 349	79.00 351	45.51 348	82.42 323	49.91 348	70.15 373	81.23 347

CVMVSNet		72.62 292	71.41 301	76.28 297	83.25 293	60.34 277	83.50 186	79.02 300	37.77 378	76.33 310	85.10 292	49.60 329	87.41 275	70.54 217	77.54 363	81.08 348

tpmrst		66.28 327	66.69 326	65.05 346	72.82 373	39.33 378	78.20 281	70.69 351	53.16 339	67.88 353	80.36 344	48.18 331	74.75 347	58.13 306	70.79 372	81.08 348

testdata				79.54 251	92.87 87	72.34 157		80.14 294	59.91 307	85.47 196	91.75 163	67.96 237	85.24 303	68.57 238	92.18 237	81.06 350

PM-MVS		80.20 217	79.00 223	83.78 173	88.17 210	86.66 18	81.31 237	66.81 364	69.64 226	88.33 142	90.19 206	64.58 253	83.63 317	71.99 206	90.03 274	81.06 350

EPMVS		62.47 334	62.63 338	62.01 350	70.63 377	38.74 379	74.76 320	52.86 381	53.91 335	67.71 355	80.01 346	39.40 367	66.60 367	55.54 320	68.81 377	80.68 352

KD-MVS_2432*1600		66.87 323	65.81 329	70.04 324	67.50 379	47.49 363	62.56 362	79.16 297	61.21 297	77.98 299	80.61 339	25.29 388	82.48 321	53.02 334	84.92 325	80.16 353

miper_refine_blended		66.87 323	65.81 329	70.04 324	67.50 379	47.49 363	62.56 362	79.16 297	61.21 297	77.98 299	80.61 339	25.29 388	82.48 321	53.02 334	84.92 325	80.16 353

mvsany_test		65.48 330	62.97 336	73.03 315	69.99 378	76.17 126	64.83 356	43.71 386	43.68 371	80.25 283	87.05 263	52.83 317	63.09 375	51.92 343	72.44 369	79.84 355

JIA-IIPM		69.41 315	66.64 327	77.70 279	73.19 369	71.24 172	75.67 311	65.56 365	70.42 217	65.18 362	92.97 123	33.64 378	83.06 318	53.52 332	69.61 376	78.79 356

BH-w/o		76.57 256	76.07 257	78.10 272	86.88 239	65.92 217	77.63 289	86.33 234	65.69 266	80.89 271	79.95 347	68.97 233	90.74 214	53.01 336	85.25 322	77.62 357

TESTMET0.1,1		61.29 339	60.32 344	64.19 347	72.06 374	51.30 347	67.89 348	62.09 369	45.27 367	60.65 372	69.01 372	27.93 385	64.74 372	56.31 314	81.65 348	76.53 358

gg-mvs-nofinetune		68.96 317	69.11 313	68.52 336	76.12 355	45.32 369	83.59 182	55.88 379	86.68 26	64.62 367	97.01 7	30.36 381	83.97 315	44.78 365	82.94 339	76.26 359

dp		60.70 343	60.29 345	61.92 352	72.04 375	38.67 380	70.83 338	64.08 367	51.28 351	60.75 371	77.28 360	36.59 374	71.58 354	47.41 358	62.34 379	75.52 360

MS-PatchMatch		70.93 304	70.22 307	73.06 314	81.85 305	62.50 250	73.82 327	77.90 303	52.44 343	75.92 316	81.27 335	55.67 309	81.75 324	55.37 321	77.70 361	74.94 361

MVS		73.21 288	72.59 290	75.06 305	80.97 314	60.81 273	81.64 232	85.92 242	46.03 366	71.68 340	77.54 357	68.47 234	89.77 242	55.70 318	85.39 319	74.60 362

pmmvs3		62.47 334	60.02 346	69.80 327	71.58 376	64.00 232	70.52 340	58.44 377	39.77 376	66.05 358	75.84 365	27.10 387	72.28 350	46.15 362	84.77 331	73.11 363

PMMVS2		55.64 347	59.27 347	44.74 363	64.30 385	12.32 388	40.60 376	49.79 383	53.19 338	65.06 365	84.81 299	53.60 316	49.76 380	32.68 380	89.41 279	72.15 364

PatchMatch-RL		74.48 278	73.22 283	78.27 270	87.70 218	85.26 37	75.92 310	70.09 352	64.34 277	76.09 314	81.25 336	65.87 249	78.07 337	53.86 330	83.82 334	71.48 365

GG-mvs-BLEND				67.16 339	73.36 368	46.54 368	84.15 162	55.04 380		58.64 377	61.95 378	29.93 382	83.87 316	38.71 375	76.92 364	71.07 366

MVE	40.22 23	51.82 348	50.47 351	55.87 360	62.66 386	51.91 342	31.61 378	39.28 387	40.65 374	50.76 381	74.98 368	56.24 307	44.67 382	33.94 379	64.11 378	71.04 367
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
new_pmnet		55.69 346	57.66 348	49.76 362	75.47 359	30.59 384	59.56 365	51.45 382	43.62 372	62.49 369	75.48 366	40.96 365	49.15 381	37.39 376	72.52 368	69.55 368

DSMNet-mixed		60.98 342	61.61 341	59.09 359	72.88 372	45.05 371	74.70 321	46.61 385	26.20 380	65.34 361	90.32 202	55.46 310	63.12 374	41.72 370	81.30 350	69.09 369

CHOSEN 280x420		59.08 344	56.52 349	66.76 340	76.51 350	64.39 228	49.62 375	59.00 375	43.86 370	55.66 380	68.41 374	35.55 376	68.21 362	43.25 367	76.78 365	67.69 370

FMVS		64.31 333	65.85 328	59.67 357	66.54 382	62.24 256	57.76 371	70.96 349	40.13 375	84.36 214	82.09 328	46.93 334	51.67 379	61.99 283	81.89 345	65.12 371

EMVS		61.10 341	60.81 342	61.99 351	65.96 383	55.86 315	53.10 374	58.97 376	67.06 253	56.89 379	63.33 376	40.98 364	67.03 365	54.79 326	86.18 315	63.08 372

E-PMN		61.59 338	61.62 340	61.49 353	66.81 381	55.40 318	53.77 373	60.34 374	66.80 256	58.90 376	65.50 375	40.48 366	66.12 369	55.72 317	86.25 314	62.95 373

PMMVS		61.65 337	60.38 343	65.47 345	65.40 384	69.26 188	63.97 360	61.73 372	36.80 379	60.11 373	68.43 373	59.42 284	66.35 368	48.97 352	78.57 359	60.81 374

wuyk23d		75.13 269	79.30 221	62.63 349	75.56 357	75.18 131	80.89 244	73.10 337	75.06 156	94.76 12	95.32 36	87.73 42	52.85 378	34.16 378	97.11 87	59.85 375

PVSNet_0	51.08 22	56.10 345	54.97 350	59.48 358	75.12 362	53.28 333	55.16 372	61.89 370	44.30 369	59.16 374	62.48 377	54.22 314	65.91 370	35.40 377	47.01 380	59.25 376

FPMVS		72.29 296	72.00 295	73.14 313	88.63 199	85.00 39	74.65 322	67.39 358	71.94 203	77.80 303	87.66 249	50.48 326	75.83 344	49.95 347	79.51 353	58.58 377

MVS-HIRNet		61.16 340	62.92 337	55.87 360	79.09 335	35.34 382	71.83 335	57.98 378	46.56 364	59.05 375	91.14 178	49.95 328	76.43 341	38.74 374	71.92 371	55.84 378

test_method		30.46 349	29.60 352	33.06 364	17.99 388	3.84 390	13.62 379	73.92 328	2.79 382	18.29 384	53.41 379	28.53 383	43.25 383	22.56 381	35.27 382	52.11 379

DeepMVS_CX				24.13 365	32.95 387	29.49 385		21.63 390	12.07 381	37.95 382	45.07 380	30.84 380	19.21 384	17.94 383	33.06 383	23.69 380

tmp_tt		20.25 351	24.50 354	7.49 366	4.47 389	8.70 389	34.17 377	25.16 389	1.00 384	32.43 383	18.49 381	39.37 368	9.21 385	21.64 382	43.75 381	4.57 381

test123		6.27 354	8.08 357	0.84 367	1.11 391	0.57 391	62.90 361	0.82 391	0.54 385	1.07 387	2.75 386	1.26 390	0.30 386	1.04 384	1.26 385	1.66 382

testmvs		5.91 355	7.65 358	0.72 368	1.20 390	0.37 392	59.14 367	0.67 392	0.49 386	1.11 386	2.76 385	0.94 391	0.24 387	1.02 385	1.47 384	1.55 383

test_blank		0.00 356	0.00 359	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.00 387	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

uanet_test		0.00 356	0.00 359	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.00 387	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

DCPMVS		0.00 356	0.00 359	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.00 387	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

cdsmvs_eth3d_5k		20.81 350	27.75 353	0.00 369	0.00 392	0.00 393	0.00 380	85.44 246	0.00 387	0.00 388	82.82 321	81.46 118	0.00 388	0.00 386	0.00 386	0.00 384

pcd_1.5k_mvsjas		6.41 353	8.55 356	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.00 387	76.94 164	0.00 388	0.00 386	0.00 386	0.00 384

sosnet-low-res		0.00 356	0.00 359	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.00 387	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

sosnet		0.00 356	0.00 359	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.00 387	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

uncertanet		0.00 356	0.00 359	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.00 387	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

Regformer		0.00 356	0.00 359	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.00 387	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

ab-mvs-re		6.65 352	8.87 355	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	79.80 348	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

uanet		0.00 356	0.00 359	0.00 369	0.00 392	0.00 393	0.00 380	0.00 393	0.00 387	0.00 388	0.00 387	0.00 392	0.00 388	0.00 386	0.00 386	0.00 384

FOURS1					96.08 12	87.41 13	96.19 2	95.83 4	92.95 2	96.57 2

test_one_0601					93.85 63	73.27 142		94.11 37	86.57 27	93.47 41	94.64 62	88.42 27

eth-test2					0.00 392

eth-test					0.00 392

ZD-MVS					92.22 108	80.48 72		91.85 120	71.22 209	90.38 95	92.98 121	86.06 63	96.11 6	81.99 88	96.75 100

test_241102_ONE					94.18 50	72.65 146		93.69 54	83.62 48	94.11 23	93.78 108	90.28 15	95.50 48

9.14			89.29 62		91.84 124		88.80 91	95.32 11	75.14 155	91.07 84	92.89 126	87.27 46	93.78 115	83.69 70	97.55 71

save fliter					93.75 64	77.44 105	86.31 132	89.72 179	70.80 212

test0726					94.16 53	72.56 152	90.63 47	93.90 46	83.61 49	93.75 31	94.49 66	89.76 19

test_part2					93.86 62	77.77 99				92.84 51

sam_mvs												45.92 344

MTGPA								91.81 123

test_post1							78.85 274				3.13 383	45.19 353	80.13 332	58.11 307

test_post											3.10 384	45.43 349	77.22 340

patchmatchnet-post											81.71 332	45.93 343	87.01 278

MTMP							90.66 45	33.14 388

gm-plane-assit					75.42 360	44.97 372			52.17 344		72.36 371		87.90 269	54.10 329

TEST9					92.34 101	79.70 79	83.94 169	90.32 162	65.41 272	84.49 211	90.97 183	82.03 108	93.63 120

test_8					92.09 112	78.87 87	83.82 174	90.31 164	65.79 262	84.36 214	90.96 185	81.93 110	93.44 133

agg_prior					91.58 132	77.69 100		90.30 165		84.32 216			93.18 141

test_prior4						78.97 86	84.59 154

test_prior2							83.37 189		75.43 150	84.58 209	91.57 165	81.92 112		79.54 117	96.97 91

旧先验2							81.73 230		56.88 324	86.54 178			84.90 307	72.81 199

新几何2							81.72 231

原ACMM2							82.26 224

testdata2													86.43 291	63.52 272

segment_acmp												81.94 109

testdata1							79.62 258		73.95 167

plane_prior7					93.45 72	77.31 109

plane_prior6					92.61 93	76.54 118						74.84 182

plane_prior4											92.95 124

plane_prior3						76.85 116			77.79 120	86.55 173

plane_prior2							89.45 79		79.44 99

plane_prior1					92.83 91

plane_prior						76.42 122	87.15 116		75.94 143						95.03 169

n2								0.00 393

nn								0.00 393

door-mid								74.45 325

test11								91.46 130

door								72.57 339

HQP5-MVS						70.66 175

HQP-NCC					91.19 146		84.77 149		73.30 177	80.55 277

ACMP_Plane					91.19 146		84.77 149		73.30 177	80.55 277

BP-MVS														77.30 147

HQP3-MVS								92.68 100							94.47 185

HQP2-MVS												72.10 215

NP-MVS					91.95 116	74.55 134					90.17 208

MDTV_nov1_ep13			68.29 319		78.03 340	43.87 374	74.12 324	72.22 341	52.17 344	67.02 357	85.54 281	45.36 350	80.85 329	55.73 316	84.42 332

ACMMP++_ref															95.74 147

ACMMP++															97.35 80

Test By Simon												79.09 140

High-resolution multi-view benchmark