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.

APDe-MVS		91.22 20	91.92 9	89.14 57	92.97 67	78.04 78	92.84 12	94.14 21	83.33 37	93.90 26	95.73 29	88.77 18	96.41 1	87.60 17	97.98 42	92.98 129

HSP-MVS		88.63 61	87.84 69	91.02 29	95.76 16	86.14 19	92.75 13	91.01 123	78.43 94	89.16 114	92.25 127	72.03 206	96.36 2	88.21 9	90.93 229	90.55 197

SteuartSystems-ACMMP		91.16 22	91.36 22	90.55 37	93.91 47	80.97 58	91.49 29	93.48 36	82.82 44	92.60 50	93.97 85	88.19 24	96.29 3	87.61 16	98.20 33	94.39 90
Skip Steuart: Steuart Systems R&D Blog.
test_part3							89.63 51		84.39 28		93.43 98		96.26 4	82.18 75

ESAPD		90.05 36	90.56 41	88.50 63	93.86 48	77.77 80	89.63 51	93.93 25	84.39 28	92.84 43	93.43 98	87.19 36	96.26 4	82.18 75	97.61 55	91.48 173

SMA-MVS		90.40 31	90.57 40	89.87 47	95.31 27	79.64 68	90.98 34	93.36 37	75.21 140	92.90 39	95.28 41	86.29 48	96.09 6	87.92 11	97.89 44	93.88 103

DTE-MVSNet		89.98 39	91.91 11	84.21 141	96.51 7	57.84 254	88.93 66	92.84 64	91.92 2	96.16 3	96.23 20	86.95 39	95.99 7	79.05 113	98.57 16	98.80 6

PGM-MVS		91.20 21	90.95 33	91.93 13	95.67 20	85.85 25	90.00 40	93.90 28	80.32 69	91.74 65	94.41 69	88.17 25	95.98 8	86.37 26	97.99 41	93.96 101

APD-MVS		89.54 50	89.63 50	89.26 56	92.57 75	81.34 56	90.19 38	93.08 52	80.87 64	91.13 72	93.19 101	86.22 49	95.97 9	82.23 74	97.18 66	90.45 199
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
TSAR-MVS + MP.		88.14 66	87.82 70	89.09 58	95.72 19	76.74 94	92.49 20	91.19 119	67.85 226	86.63 152	94.84 54	79.58 109	95.96 10	87.62 15	94.50 153	94.56 81

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 11	85.07 37	99.27 3	99.54 1

WR-MVS_H		89.91 44	91.31 25	85.71 110	96.32 9	62.39 213	89.54 56	93.31 42	90.21 10	95.57 11	95.66 31	81.42 94	95.90 12	80.94 88	98.80 4	98.84 5

region2R		91.44 17	91.30 26	91.87 16	95.75 17	85.90 23	92.63 17	93.30 43	81.91 55	90.88 78	94.21 77	87.75 30	95.87 13	87.60 17	97.71 51	93.83 104

ACMMPR		91.49 14	91.35 24	91.92 14	95.74 18	85.88 24	92.58 18	93.25 47	81.99 53	91.40 70	94.17 79	87.51 34	95.87 13	87.74 12	97.76 48	93.99 99

3Dnovator+	83.92 2	89.97 41	89.66 49	90.92 32	91.27 113	81.66 54	91.25 32	94.13 22	88.89 12	88.83 119	94.26 75	77.55 125	95.86 15	84.88 40	95.87 111	95.24 71

XVS		91.54 12	91.36 22	92.08 8	95.64 21	86.25 16	92.64 15	93.33 40	85.07 25	89.99 87	94.03 83	86.57 43	95.80 16	87.35 20	97.62 53	94.20 92

X-MVStestdata		85.04 114	82.70 161	92.08 8	95.64 21	86.25 16	92.64 15	93.33 40	85.07 25	89.99 87	16.05 355	86.57 43	95.80 16	87.35 20	97.62 53	94.20 92

DeepC-MVS	82.31 4	89.15 56	89.08 54	89.37 54	93.64 52	79.07 71	88.54 72	94.20 17	73.53 155	89.71 98	94.82 55	85.09 53	95.77 18	84.17 51	98.03 38	93.26 122
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MVS_0304		84.88 118	83.96 148	87.64 78	87.43 196	74.83 106	84.18 136	93.30 43	77.48 106	77.39 269	88.46 209	74.53 162	95.74 19	78.09 123	94.75 149	92.36 150

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 43	91.77 64	93.94 91	90.55 13	95.73 20	88.50 8	98.23 31	95.33 69
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
CP-MVS		91.67 11	91.58 17	91.96 12	95.29 28	87.62 9	93.38 7	93.36 37	83.16 39	91.06 73	94.00 84	88.26 23	95.71 21	87.28 23	98.39 23	92.55 144

ACMMP		91.91 9	91.87 14	92.03 11	95.53 24	85.91 22	93.35 9	94.16 20	82.52 47	92.39 55	94.14 80	89.15 17	95.62 22	87.35 20	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
PEN-MVS		90.03 37	91.88 12	84.48 132	96.57 5	58.88 250	88.95 64	93.19 48	91.62 4	96.01 6	96.16 22	87.02 38	95.60 23	78.69 116	98.72 10	98.97 3

PS-CasMVS		90.06 35	91.92 9	84.47 133	96.56 6	58.83 251	89.04 63	92.74 67	91.40 5	96.12 4	96.06 24	87.23 35	95.57 24	79.42 112	98.74 7	99.00 2

HFP-MVS		91.30 18	91.39 21	91.02 29	95.43 25	84.66 39	92.58 18	93.29 45	81.99 53	91.47 68	93.96 87	88.35 21	95.56 25	87.74 12	97.74 49	92.85 130

#test#		90.49 30	90.31 43	91.02 29	95.43 25	84.66 39	90.65 35	93.29 45	77.00 118	91.47 68	93.96 87	88.35 21	95.56 25	84.88 40	97.74 49	92.85 130

CP-MVSNet		89.27 54	90.91 34	84.37 136	96.34 8	58.61 253	88.66 71	92.06 83	90.78 6	95.67 9	95.17 45	81.80 90	95.54 27	79.00 114	98.69 11	98.95 4

LPG-MVS_test		91.47 16	91.68 15	90.82 34	94.75 36	81.69 51	90.00 40	94.27 13	82.35 48	93.67 30	94.82 55	91.18 6	95.52 28	85.36 35	98.73 8	95.23 72

LGP-MVS_train				90.82 34	94.75 36	81.69 51		94.27 13	82.35 48	93.67 30	94.82 55	91.18 6	95.52 28	85.36 35	98.73 8	95.23 72

mPP-MVS		91.69 10	91.47 20	92.37 5	96.04 11	88.48 8	92.72 14	92.60 72	83.09 40	91.54 67	94.25 76	87.67 33	95.51 30	87.21 24	98.11 35	93.12 126

ACMMP_Plus		90.65 26	91.07 30	89.42 53	95.93 14	79.54 69	89.95 43	93.68 31	77.65 103	91.97 61	94.89 52	88.38 19	95.45 31	89.27 3	97.87 46	93.27 121

CANet		83.79 151	82.85 160	86.63 87	86.17 229	72.21 127	83.76 151	91.43 107	77.24 114	74.39 292	87.45 228	75.36 146	95.42 32	77.03 133	92.83 192	92.25 156

MP-MVS		91.14 23	90.91 34	91.83 18	96.18 10	86.88 11	92.20 22	93.03 56	82.59 46	88.52 125	94.37 73	86.74 40	95.41 33	86.32 27	98.21 32	93.19 125
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
LS3D		90.60 28	90.34 42	91.38 23	89.03 150	84.23 42	93.58 4	94.68 10	90.65 7	90.33 82	93.95 90	84.50 58	95.37 34	80.87 89	95.50 121	94.53 85

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 51	95.13 46	90.65 11	95.34 35	88.06 10	98.15 34	95.95 51

NCCC		87.36 73	86.87 87	88.83 59	92.32 85	78.84 74	86.58 107	91.09 121	78.77 90	84.85 178	90.89 166	80.85 98	95.29 36	81.14 85	95.32 125	92.34 151

EPP-MVSNet		85.47 109	85.04 115	86.77 86	91.52 107	69.37 149	91.63 28	87.98 184	81.51 60	87.05 147	91.83 134	66.18 228	95.29 36	70.75 177	96.89 72	95.64 59

zzz-MVS		91.27 19	91.26 27	91.29 25	96.59 3	86.29 14	88.94 65	91.81 91	84.07 32	92.00 59	94.40 70	86.63 41	95.28 38	88.59 4	98.31 26	92.30 152

MTAPA		91.52 13	91.60 16	91.29 25	96.59 3	86.29 14	92.02 24	91.81 91	84.07 32	92.00 59	94.40 70	86.63 41	95.28 38	88.59 4	98.31 26	92.30 152

HQP_MVS		87.75 72	87.43 77	88.70 61	93.45 54	76.42 98	89.45 59	93.61 32	79.44 79	86.55 153	92.95 108	74.84 154	95.22 40	80.78 91	95.83 113	94.46 86

plane_prior5								93.61 32					95.22 40	80.78 91	95.83 113	94.46 86

ACMP	79.16 10	90.54 29	90.60 37	90.35 41	94.36 41	80.98 57	89.16 62	94.05 23	79.03 86	92.87 41	93.74 94	90.60 12	95.21 42	82.87 66	98.76 5	94.87 77
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
DeepC-MVS_fast	80.27 8	86.23 96	85.65 107	87.96 74	91.30 111	76.92 91	87.19 90	91.99 85	70.56 201	84.96 174	90.69 172	80.01 106	95.14 43	78.37 117	95.78 115	91.82 164
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
abl_6		93.02 4	93.16 4	92.60 4	94.73 39	88.99 7	93.26 10	94.19 19	89.11 11	94.43 19	95.27 42	91.86 4	95.09 44	87.54 19	98.02 39	93.71 111

APD-MVS_3200maxsize		92.05 7	92.24 6	91.48 20	93.02 65	85.17 31	92.47 21	95.05 8	87.65 19	93.21 36	94.39 72	90.09 14	95.08 45	86.67 25	97.60 57	94.18 94

HPM-MVS++		88.93 58	88.45 64	90.38 40	94.92 33	85.85 25	89.70 47	91.27 116	78.20 97	86.69 151	92.28 126	80.36 103	95.06 46	86.17 32	96.49 86	90.22 203

MP-MVS-pluss		90.81 24	91.08 29	89.99 46	95.97 12	79.88 63	88.13 76	94.51 11	75.79 131	92.94 38	94.96 50	88.36 20	95.01 47	90.70 2	98.40 21	95.09 75
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
CDPH-MVS		86.17 98	85.54 108	88.05 73	92.25 86	75.45 103	83.85 146	92.01 84	65.91 238	86.19 160	91.75 138	83.77 63	94.98 48	77.43 129	96.71 78	93.73 110

COLMAP_ROB	83.01 3	91.97 8	91.95 8	92.04 10	93.68 51	86.15 18	93.37 8	95.10 7	90.28 9	92.11 56	95.03 48	89.75 15	94.93 49	79.95 104	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
IS-MVSNet		86.66 86	86.82 90	86.17 102	92.05 92	66.87 167	91.21 33	88.64 172	86.30 23	89.60 107	92.59 116	69.22 216	94.91 50	73.89 152	97.89 44	96.72 35

OurMVSNet-221017-0		90.01 38	89.74 48	90.83 33	93.16 62	80.37 59	91.91 27	93.11 50	81.10 62	95.32 13	97.24 6	72.94 191	94.85 51	85.07 37	97.78 47	97.26 23

test12				86.57 88	90.74 125	72.63 119		90.69 126		82.76 211		79.20 110	94.80 52		95.32 125	92.27 154

SixPastTwentyTwo		87.20 76	87.45 76	86.45 91	92.52 77	69.19 154	87.84 81	88.05 181	81.66 58	94.64 17	96.53 14	65.94 229	94.75 53	83.02 65	96.83 75	95.41 67

CNVR-MVS		87.81 71	87.68 73	88.21 67	92.87 69	77.30 89	85.25 121	91.23 117	77.31 113	87.07 146	91.47 144	82.94 71	94.71 54	84.67 44	96.27 94	92.62 143

K. test v3		85.14 111	84.73 121	86.37 92	91.13 118	69.63 148	85.45 119	76.68 266	84.06 34	92.44 53	96.99 8	62.03 241	94.65 55	80.58 94	93.24 184	94.83 80

HQP4-MVS										80.56 244			94.61 56			93.56 117

HQP-MVS		84.61 123	84.06 145	86.27 95	91.19 114	70.66 142	84.77 125	92.68 68	73.30 161	80.55 245	90.17 186	72.10 202	94.61 56	77.30 130	94.47 154	93.56 117

PS-MVSNAJss		88.31 64	87.90 68	89.56 52	93.31 58	77.96 79	87.94 78	91.97 86	70.73 200	94.19 24	96.67 11	76.94 133	94.57 58	83.07 63	96.28 92	96.15 42

DeepPCF-MVS	81.24 5	87.28 75	86.21 98	90.49 38	91.48 108	84.90 34	83.41 163	92.38 77	70.25 205	89.35 112	90.68 173	82.85 72	94.57 58	79.55 108	95.95 107	92.00 160

UA-Net		91.49 14	91.53 18	91.39 22	94.98 32	82.95 50	93.52 5	92.79 65	88.22 16	88.53 124	97.64 3	83.45 66	94.55 60	86.02 34	98.60 14	96.67 36

114514_t		83.10 163	82.54 166	84.77 124	92.90 68	69.10 155	86.65 105	90.62 129	54.66 302	81.46 226	90.81 169	76.98 132	94.38 61	72.62 166	96.18 96	90.82 189

MVSFormer		82.23 172	81.57 178	84.19 143	85.54 240	69.26 151	91.98 25	90.08 150	71.54 194	76.23 276	85.07 260	58.69 259	94.27 62	86.26 28	88.77 254	89.03 219

test_djsdf		89.62 48	89.01 55	91.45 21	92.36 82	82.98 49	91.98 25	90.08 150	71.54 194	94.28 23	96.54 13	81.57 92	94.27 62	86.26 28	96.49 86	97.09 30

原ACMM1				84.60 129	92.81 73	74.01 111		91.50 98	62.59 263	82.73 212	90.67 174	76.53 140	94.25 64	69.24 189	95.69 118	85.55 253

AdaColmap		83.66 153	83.69 151	83.57 160	90.05 138	72.26 125	86.29 111	90.00 153	78.19 98	81.65 224	87.16 230	83.40 67	94.24 65	61.69 240	94.76 148	84.21 273

Effi-MVS+-dtu		85.82 104	83.38 153	93.14 3	87.13 207	91.15 3	87.70 82	88.42 174	74.57 146	83.56 201	85.65 247	78.49 115	94.21 66	72.04 170	92.88 191	94.05 98

UniMVSNet (Re)		86.87 80	86.98 84	86.55 89	93.11 64	68.48 157	83.80 149	92.87 61	80.37 67	89.61 106	91.81 136	77.72 122	94.18 67	75.00 145	98.53 17	96.99 34

PHI-MVS		86.38 91	85.81 103	88.08 69	88.44 164	77.34 87	89.35 61	93.05 53	73.15 166	84.76 179	87.70 224	78.87 113	94.18 67	80.67 93	96.29 91	92.73 134

test_prior3		86.31 93	86.31 95	86.32 93	90.59 128	71.99 130	83.37 164	92.85 62	75.43 137	84.58 185	91.57 140	81.92 88	94.17 69	79.54 109	96.97 70	92.80 132

test_prior				86.32 93	90.59 128	71.99 130		92.85 62					94.17 69			92.80 132

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 42	96.29 18	88.16 26	94.17 69	86.07 33	98.48 19	97.22 26

v7n		90.13 33	90.96 32	87.65 77	91.95 94	71.06 140	89.99 42	93.05 53	86.53 21	94.29 22	96.27 19	82.69 73	94.08 72	86.25 30	97.63 52	97.82 11

v10		86.54 88	87.10 80	84.84 121	88.16 171	63.28 194	86.64 106	92.20 80	75.42 139	92.81 45	94.50 65	74.05 166	94.06 73	83.88 54	96.28 92	97.17 28

UniMVSNet_NR-MVSNet		86.84 82	87.06 81	86.17 102	92.86 71	67.02 165	82.55 186	91.56 96	83.08 41	90.92 75	91.82 135	78.25 118	93.99 74	74.16 148	98.35 24	97.49 16

DU-MVS		86.80 83	86.99 83	86.21 99	93.24 60	67.02 165	83.16 171	92.21 79	81.73 57	90.92 75	91.97 129	77.20 127	93.99 74	74.16 148	98.35 24	97.61 13

mvs-test1		84.55 125	82.12 170	91.84 17	87.13 207	89.54 5	85.05 124	88.42 174	74.57 146	80.60 242	82.98 284	78.49 115	93.98 76	72.04 170	89.77 245	92.00 160

v52		89.97 41	90.60 37	88.07 70	88.69 156	72.01 128	91.35 30	92.64 70	82.22 50	95.97 8	96.31 16	84.82 54	93.98 76	88.59 4	94.83 143	98.23 8

V4		89.97 41	90.60 37	88.07 70	88.69 156	72.01 128	91.35 30	92.64 70	82.22 50	95.98 7	96.31 16	84.80 56	93.98 76	88.59 4	94.83 143	98.23 8

DP-MVS Recon		84.05 145	83.22 155	86.52 90	91.73 99	75.27 104	83.23 170	92.40 75	72.04 182	82.04 217	88.33 214	77.91 121	93.95 79	66.17 213	95.12 132	90.34 202

DP-MVS		88.60 62	89.01 55	87.36 82	91.30 111	77.50 85	87.55 84	92.97 58	87.95 17	89.62 104	92.87 110	84.56 57	93.89 80	77.65 125	96.62 80	90.70 191

NR-MVSNet		86.00 99	86.22 97	85.34 114	93.24 60	64.56 179	82.21 197	90.46 132	80.99 63	88.42 127	91.97 129	77.56 124	93.85 81	72.46 167	98.65 13	97.61 13

EPNet		80.37 193	78.41 205	86.23 96	76.75 319	73.28 115	87.18 91	77.45 260	76.24 124	68.14 320	88.93 203	65.41 231	93.85 81	69.47 187	96.12 101	91.55 171
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
OPM-MVS		89.80 45	89.97 44	89.27 55	94.76 35	79.86 64	86.76 100	92.78 66	78.78 89	92.51 51	93.64 95	88.13 27	93.84 83	84.83 42	97.55 58	94.10 97

TranMVSNet+NR-MVSNet		87.86 69	88.76 62	85.18 116	94.02 44	64.13 182	84.38 134	91.29 115	84.88 27	92.06 58	93.84 93	86.45 45	93.73 84	73.22 159	98.66 12	97.69 12

v8		86.22 97	86.83 89	84.36 137	87.82 182	62.35 214	86.42 109	91.33 114	76.78 120	92.73 47	94.48 66	73.41 180	93.72 85	83.10 62	95.41 122	97.01 33

agg_prior3		85.76 105	84.95 118	88.16 68	92.43 80	79.92 62	83.98 141	90.03 152	65.11 248	83.66 199	90.64 177	81.00 97	93.67 86	81.21 83	96.54 83	90.88 186

Vis-MVSNet		86.86 81	86.58 91	87.72 75	92.09 90	77.43 86	87.35 87	92.09 82	78.87 88	84.27 194	94.05 82	78.35 117	93.65 87	80.54 95	91.58 210	92.08 159
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
v1240		84.30 135	84.51 134	83.65 157	87.65 191	61.26 231	82.85 177	91.54 97	67.94 224	90.68 80	90.65 175	71.71 208	93.64 88	82.84 68	94.78 145	96.07 45

TEST9					92.34 83	79.70 66	83.94 142	90.32 137	65.41 246	84.49 187	90.97 162	82.03 84	93.63 89

train_agg		85.98 102	85.28 112	88.07 70	92.34 83	79.70 66	83.94 142	90.32 137	65.79 239	84.49 187	90.97 162	81.93 86	93.63 89	81.21 83	96.54 83	90.88 186

v7		84.81 119	85.00 116	84.23 140	88.15 172	63.27 195	83.79 150	91.39 112	71.10 198	90.07 84	91.28 146	74.04 167	93.63 89	81.48 82	93.67 171	95.79 52

PCF-MVS	74.62 15	82.15 173	80.92 186	85.84 108	89.43 143	72.30 124	80.53 228	91.82 90	57.36 290	87.81 135	89.92 189	77.67 123	93.63 89	58.69 264	95.08 133	91.58 170
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
v1192		84.57 124	84.69 125	84.21 141	87.75 187	62.88 202	83.02 173	91.43 107	69.08 215	89.98 89	90.89 166	72.70 196	93.62 93	82.41 71	94.97 137	96.13 43

v1921920		84.23 138	84.37 141	83.79 150	87.64 192	61.71 222	82.91 176	91.20 118	67.94 224	90.06 85	90.34 180	72.04 205	93.59 94	82.32 73	94.91 138	96.07 45

mvs_tets		89.78 46	89.27 53	91.30 24	93.51 53	84.79 36	89.89 45	90.63 128	70.00 207	94.55 18	96.67 11	87.94 29	93.59 94	84.27 49	95.97 106	95.52 65

test_0402		88.65 60	89.58 51	85.88 107	92.55 76	72.22 126	84.01 140	89.44 164	88.63 14	94.38 21	95.77 28	86.38 47	93.59 94	79.84 105	95.21 129	91.82 164

v13		87.31 74	88.10 65	84.94 118	88.84 153	63.75 186	87.85 80	91.47 103	79.12 83	93.72 29	95.82 27	75.20 148	93.58 97	84.76 43	96.16 97	97.48 17

v12		87.15 77	87.91 67	84.84 121	88.69 156	63.52 189	87.58 83	91.46 104	78.74 91	93.57 32	95.66 31	74.94 152	93.57 98	84.50 46	96.08 102	97.43 18

v11		86.96 78	87.78 71	84.51 130	88.50 162	62.60 209	87.21 89	91.63 95	78.08 100	93.40 34	95.56 36	75.07 149	93.57 98	84.46 47	96.08 102	97.36 21

V9		86.96 78	87.70 72	84.74 125	88.52 161	63.27 195	87.31 88	91.45 106	78.28 96	93.43 33	95.45 38	74.59 160	93.57 98	84.23 50	96.01 105	97.38 19

V14		86.75 84	87.46 75	84.62 128	88.35 165	63.00 200	87.02 94	91.42 109	77.78 102	93.27 35	95.23 44	74.22 163	93.56 101	83.95 53	95.93 108	97.31 22

v15		86.56 87	87.25 79	84.51 130	88.15 172	62.72 205	86.72 104	91.40 111	77.38 107	93.11 37	95.00 49	73.93 168	93.55 102	83.67 57	95.86 112	97.26 23

v17		86.32 92	86.95 85	84.44 134	88.00 174	62.62 208	86.74 102	91.48 100	77.17 115	92.74 46	94.56 61	73.74 172	93.53 103	83.27 60	94.87 142	97.18 27

jajsoiax		89.41 51	88.81 60	91.19 28	93.38 57	84.72 37	89.70 47	90.29 144	69.27 211	94.39 20	96.38 15	86.02 51	93.52 104	83.96 52	95.92 109	95.34 68

v18		85.99 101	86.55 92	84.30 139	87.73 188	62.29 218	86.40 110	91.49 99	76.64 121	92.40 54	94.20 78	73.28 184	93.52 104	82.87 66	93.99 161	97.09 30

v16		86.24 95	86.85 88	84.43 135	87.96 176	62.59 210	86.73 103	91.48 100	77.17 115	92.67 49	94.55 62	73.63 173	93.52 104	83.26 61	94.16 157	97.17 28

v144192		84.24 137	84.41 136	83.71 156	87.59 193	61.57 227	82.95 175	91.03 122	67.82 227	89.80 96	90.49 178	73.28 184	93.51 107	81.88 80	94.89 139	96.04 47

v1144		84.54 127	84.72 123	84.00 145	87.67 190	62.55 211	82.97 174	90.93 124	70.32 204	89.80 96	90.99 161	73.50 178	93.48 108	81.69 81	94.65 151	95.97 49

MCST-MVS		84.36 132	83.93 149	85.63 111	91.59 101	71.58 137	83.52 158	92.13 81	61.82 269	83.96 195	89.75 192	79.93 108	93.46 109	78.33 119	94.34 156	91.87 163

test_8					92.09 90	78.87 73	83.82 147	90.31 139	65.79 239	84.36 190	90.96 164	81.93 86	93.44 110

ACMH+	77.89 11	90.73 25	91.50 19	88.44 64	93.00 66	76.26 100	89.65 50	95.55 3	87.72 18	93.89 27	94.94 51	91.62 5	93.44 110	78.35 118	98.76 5	95.61 64

FC-MVSNet-test		85.93 103	87.05 82	82.58 178	92.25 86	56.44 265	85.75 115	93.09 51	77.33 112	91.94 62	94.65 60	74.78 156	93.41 112	75.11 143	98.58 15	97.88 10

OMC-MVS		88.19 65	87.52 74	90.19 44	91.94 96	81.68 53	87.49 86	93.17 49	76.02 127	88.64 122	91.22 148	84.24 60	93.37 113	77.97 124	97.03 69	95.52 65

MG-MVS		80.32 194	80.94 185	78.47 230	88.18 169	52.62 292	82.29 193	85.01 224	72.01 183	79.24 257	92.54 119	69.36 215	93.36 114	70.65 179	89.19 251	89.45 211

v1neww		84.43 129	84.66 127	83.75 152	87.81 183	62.34 215	83.59 154	90.27 145	72.33 177	89.93 91	91.22 148	73.28 184	93.29 115	80.25 100	93.25 182	95.62 60

v7new		84.43 129	84.66 127	83.75 152	87.81 183	62.34 215	83.59 154	90.27 145	72.33 177	89.93 91	91.22 148	73.28 184	93.29 115	80.25 100	93.25 182	95.62 60

v6		84.43 129	84.66 127	83.75 152	87.81 183	62.34 215	83.59 154	90.26 147	72.33 177	89.94 90	91.19 152	73.30 183	93.29 115	80.26 99	93.26 181	95.62 60

CPTT-MVS		89.39 52	88.98 57	90.63 36	95.09 30	86.95 10	92.09 23	92.30 78	79.74 74	87.50 139	92.38 121	81.42 94	93.28 118	83.07 63	97.24 64	91.67 167

F-COLMAP		84.97 117	83.42 152	89.63 50	92.39 81	83.40 45	88.83 67	91.92 88	73.19 165	80.18 250	89.15 200	77.04 131	93.28 118	65.82 218	92.28 200	92.21 157

v2v482		84.09 143	84.24 143	83.62 158	87.13 207	61.40 228	82.71 183	89.71 159	72.19 181	89.55 108	91.41 145	70.70 213	93.20 120	81.02 86	93.76 168	96.25 41

agg_prior1		85.72 106	85.20 113	87.28 83	91.58 104	77.69 82	83.69 153	90.30 141	66.29 234	84.32 191	91.07 159	82.13 81	93.18 121	81.02 86	96.36 89	90.98 181

agg_prior					91.58 104	77.69 82		90.30 141		84.32 191			93.18 121

Regformer-2		86.74 85	86.08 100	88.73 60	84.18 261	79.20 70	83.52 158	89.33 165	83.33 37	89.92 93	85.07 260	83.23 69	93.16 123	83.39 58	92.72 194	93.83 104

LTVRE_ROB	86.10 1	93.04 3	93.44 2	91.82 19	93.73 50	85.72 28	96.79 1	95.51 4	88.86 13	95.63 10	96.99 8	84.81 55	93.16 123	91.10 1	97.53 59	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
semantic-postprocess				84.34 138	83.93 264	69.66 147		81.09 245	72.43 173	86.47 159	90.19 184	57.56 266	93.15 125	77.45 128	86.39 281	90.22 203

v1141		84.16 140	84.38 138	83.52 162	87.32 199	61.70 224	82.79 179	89.74 156	71.90 191	89.64 101	91.12 155	72.68 197	93.10 126	80.39 98	93.80 166	95.75 54

divwei89l23v2f112		84.16 140	84.38 138	83.52 162	87.32 199	61.70 224	82.79 179	89.74 156	71.90 191	89.64 101	91.12 155	72.68 197	93.10 126	80.40 96	93.81 165	95.75 54

v1		84.16 140	84.38 138	83.52 162	87.33 198	61.71 222	82.79 179	89.73 158	71.89 193	89.64 101	91.11 157	72.72 194	93.10 126	80.40 96	93.79 167	95.75 54

XVG-ACMP-BASELINE		89.98 39	89.84 46	90.41 39	94.91 34	84.50 41	89.49 58	93.98 24	79.68 75	92.09 57	93.89 92	83.80 62	93.10 126	82.67 70	98.04 36	93.64 113

anonymousdsp		89.73 47	88.88 58	92.27 7	89.82 141	86.67 12	90.51 36	90.20 149	69.87 208	95.06 14	96.14 23	84.28 59	93.07 130	87.68 14	96.34 90	97.09 30

ACMM	79.39 9	90.65 26	90.99 31	89.63 50	95.03 31	83.53 44	89.62 53	93.35 39	79.20 82	93.83 28	93.60 96	90.81 9	92.96 131	85.02 39	98.45 20	92.41 147
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CLD-MVS		83.18 161	82.64 163	84.79 123	89.05 149	67.82 162	77.93 266	92.52 73	68.33 219	85.07 173	81.54 308	82.06 82	92.96 131	69.35 188	97.91 43	93.57 116
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
Effi-MVS+		83.90 150	84.01 146	83.57 160	87.22 205	65.61 174	86.55 108	92.40 75	78.64 92	81.34 229	84.18 271	83.65 64	92.93 133	74.22 147	87.87 266	92.17 158

lessismore_v0				85.95 104	91.10 119	70.99 141		70.91 310		91.79 63	94.42 68	61.76 242	92.93 133	79.52 111	93.03 188	93.93 102

FIs		85.35 110	86.27 96	82.60 177	91.86 97	57.31 258	85.10 123	93.05 53	75.83 130	91.02 74	93.97 85	73.57 177	92.91 135	73.97 151	98.02 39	97.58 15

PVSNet_Blended_VisFu		81.55 179	80.49 190	84.70 127	91.58 104	73.24 116	84.21 135	91.67 94	62.86 261	80.94 231	87.16 230	67.27 223	92.87 136	69.82 185	88.94 253	87.99 229

Regformer-4		86.41 90	85.71 105	88.52 62	84.27 257	77.57 84	84.07 138	88.00 183	82.82 44	89.84 95	85.48 250	82.06 82	92.77 137	83.83 56	91.04 222	95.22 74

DELS-MVS		81.44 180	81.25 181	82.03 185	84.27 257	62.87 203	76.47 280	92.49 74	70.97 199	81.64 225	83.83 274	75.03 150	92.70 138	74.29 146	92.22 204	90.51 198
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
TSAR-MVS + GP.		83.95 148	82.69 162	87.72 75	89.27 146	81.45 55	83.72 152	81.58 243	74.73 144	85.66 167	86.06 245	72.56 200	92.69 139	75.44 141	95.21 129	89.01 221

v748		88.91 59	89.82 47	86.19 101	90.06 137	68.53 156	88.81 68	91.48 100	84.36 30	94.19 24	95.98 25	82.52 76	92.67 140	84.30 48	96.67 79	97.37 20

Fast-Effi-MVS+		81.04 186	80.57 187	82.46 182	87.50 194	63.22 197	78.37 262	89.63 160	68.01 221	81.87 219	82.08 303	82.31 79	92.65 141	67.10 205	88.30 262	91.51 172

PLC	73.85 16	82.09 174	80.31 191	87.45 80	90.86 124	80.29 60	85.88 113	90.65 127	68.17 220	76.32 275	86.33 241	73.12 189	92.61 142	61.40 244	90.02 244	89.44 212
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
IterMVS-LS		84.73 121	84.98 117	83.96 147	87.35 197	63.66 187	83.25 168	89.88 155	76.06 125	89.62 104	92.37 124	73.40 182	92.52 143	78.16 121	94.77 147	95.69 57
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
PAPM_NR		83.23 160	83.19 157	83.33 166	90.90 122	65.98 171	88.19 75	90.78 125	78.13 99	80.87 233	87.92 222	73.49 179	92.42 144	70.07 183	88.40 257	91.60 169

PAPM		71.77 272	70.06 283	76.92 251	86.39 218	53.97 279	76.62 277	86.62 204	53.44 308	63.97 337	84.73 266	57.79 265	92.34 145	39.65 338	81.33 317	84.45 268

PAPR		78.84 203	78.10 206	81.07 201	85.17 244	60.22 241	82.21 197	90.57 130	62.51 264	75.32 285	84.61 267	74.99 151	92.30 146	59.48 262	88.04 264	90.68 192

V42		83.47 158	83.37 154	83.75 152	83.16 272	63.33 193	81.31 216	90.23 148	69.51 210	90.91 77	90.81 169	74.16 164	92.29 147	80.06 102	90.22 242	95.62 60

QAPM		82.59 167	82.59 165	82.58 178	86.44 217	66.69 168	89.94 44	90.36 136	67.97 223	84.94 176	92.58 118	72.71 195	92.18 148	70.63 180	87.73 268	88.85 222

CSCG		86.26 94	86.47 93	85.60 112	90.87 123	74.26 110	87.98 77	91.85 89	80.35 68	89.54 110	88.01 218	79.09 111	92.13 149	75.51 140	95.06 134	90.41 200

TAPA-MVS	77.73 12	85.71 107	84.83 120	88.37 65	88.78 155	79.72 65	87.15 92	93.50 35	69.17 213	85.80 166	89.56 195	80.76 99	92.13 149	73.21 163	95.51 120	93.25 123
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
HyFIR lowres test		75.12 239	72.66 261	82.50 181	91.44 110	65.19 175	72.47 304	87.31 191	46.79 338	80.29 248	84.30 270	52.70 284	92.10 151	51.88 307	86.73 276	90.22 203

testing_2		84.36 132	84.64 130	83.50 165	86.74 216	63.97 185	84.56 131	90.31 139	66.22 235	91.62 66	94.55 62	75.88 143	91.95 152	77.02 134	94.89 139	94.56 81

EI-MVSNet-Vis-set		85.12 112	84.53 133	86.88 84	84.01 263	72.76 118	83.91 145	85.18 219	80.44 66	88.75 120	85.49 249	80.08 105	91.92 153	82.02 77	90.85 232	95.97 49

EI-MVSNet-UG-set		85.04 114	84.44 135	86.85 85	83.87 266	72.52 121	83.82 147	85.15 220	80.27 70	88.75 120	85.45 253	79.95 107	91.90 154	81.92 79	90.80 233	96.13 43

Regformer-1		86.00 99	85.50 109	87.49 79	84.18 261	76.90 92	83.52 158	87.94 185	82.18 52	89.19 113	85.07 260	82.28 80	91.89 155	82.40 72	92.72 194	93.69 112

IB-MVS	62.13 19	71.64 273	68.97 287	79.66 217	80.80 291	62.26 220	73.94 298	76.90 263	63.27 258	68.63 319	76.79 329	33.83 349	91.84 156	59.28 263	87.26 272	84.88 264
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
DI_MVS_plusplus_test		81.27 183	81.26 180	81.29 198	84.98 245	61.65 226	81.98 202	87.25 193	63.56 254	87.56 138	89.60 194	73.62 174	91.83 157	72.20 169	90.59 240	90.38 201

UGNet		82.78 164	81.64 176	86.21 99	86.20 228	76.24 101	86.86 95	85.68 213	77.07 117	73.76 295	92.82 111	69.64 214	91.82 158	69.04 193	93.69 170	90.56 196
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
BH-untuned		80.96 187	80.99 184	80.84 203	88.55 160	68.23 158	80.33 230	88.46 173	72.79 170	86.55 153	86.76 234	74.72 158	91.77 159	61.79 239	88.99 252	82.52 296

Anonymous20231211		90.14 32	91.88 12	84.92 119	94.75 36	64.47 180	90.13 39	92.97 58	91.68 3	95.35 12	98.79 2	93.19 3	91.76 160	71.67 173	98.40 21	98.52 7

Test4		81.31 181	81.13 183	81.88 189	84.89 247	63.05 199	82.37 190	90.50 131	62.75 262	89.00 116	88.29 215	67.55 222	91.68 161	73.55 156	91.24 219	90.89 185

test_normal		81.23 185	81.16 182	81.43 196	84.77 250	61.99 221	81.46 215	86.95 203	63.16 259	87.22 141	89.63 193	73.62 174	91.65 162	72.92 164	90.70 235	90.65 194

API-MVS		82.28 171	82.61 164	81.30 197	86.29 224	69.79 145	88.71 70	87.67 187	78.42 95	82.15 216	84.15 273	77.98 119	91.59 163	65.39 220	92.75 193	82.51 297

nrg030		87.85 70	88.49 63	85.91 105	90.07 136	69.73 146	87.86 79	94.20 17	74.04 150	92.70 48	94.66 59	85.88 52	91.50 164	79.72 106	97.32 62	96.50 40

AllTest		87.97 68	87.40 78	89.68 48	91.59 101	83.40 45	89.50 57	95.44 5	79.47 77	88.00 132	93.03 104	82.66 74	91.47 165	70.81 175	96.14 99	94.16 95

TestCases				89.68 48	91.59 101	83.40 45		95.44 5	79.47 77	88.00 132	93.03 104	82.66 74	91.47 165	70.81 175	96.14 99	94.16 95

PVSNet_BlendedMVS		78.80 204	77.84 207	81.65 194	84.43 253	63.41 190	79.49 242	90.44 133	61.70 272	75.43 283	87.07 232	69.11 217	91.44 167	60.68 249	92.24 202	90.11 207

PVSNet_Blended		76.49 227	75.40 230	79.76 213	84.43 253	63.41 190	75.14 290	90.44 133	57.36 290	75.43 283	78.30 324	69.11 217	91.44 167	60.68 249	87.70 269	84.42 269

无先验							82.81 178	85.62 214	58.09 287				91.41 169	67.95 203		84.48 267

1121		80.86 188	79.81 198	84.02 144	93.93 46	78.70 75	81.64 211	80.18 249	55.43 299	83.67 198	91.15 153	71.29 210	91.41 169	67.95 203	93.06 187	81.96 304

ambc				82.98 171	90.55 130	64.86 177	88.20 74	89.15 167		89.40 111	93.96 87	71.67 209	91.38 171	78.83 115	96.55 82	92.71 135

3Dnovator	80.37 7	84.80 120	84.71 124	85.06 117	86.36 222	74.71 107	88.77 69	90.00 153	75.65 135	84.96 174	93.17 102	74.06 165	91.19 172	78.28 120	91.09 220	89.29 216

cascas		76.29 229	74.81 235	80.72 206	84.47 252	62.94 201	73.89 299	87.34 190	55.94 296	75.16 287	76.53 331	63.97 234	91.16 173	65.00 221	90.97 228	88.06 227

EG-PatchMatch MVS		84.08 144	84.11 144	83.98 146	92.22 88	72.61 120	82.20 199	87.02 201	72.63 172	88.86 117	91.02 160	78.52 114	91.11 174	73.41 158	91.09 220	88.21 225

WR-MVS		83.56 155	84.40 137	81.06 202	93.43 56	54.88 276	78.67 261	85.02 223	81.24 61	90.74 79	91.56 142	72.85 192	91.08 175	68.00 201	98.04 36	97.23 25

canonicalmvs		85.50 108	86.14 99	83.58 159	87.97 175	67.13 164	87.55 84	94.32 12	73.44 157	88.47 126	87.54 227	86.45 45	91.06 176	75.76 139	93.76 168	92.54 145

XVG-OURS		89.18 55	88.83 59	90.23 43	94.28 42	86.11 20	85.91 112	93.60 34	80.16 71	89.13 115	93.44 97	83.82 61	90.98 177	83.86 55	95.30 128	93.60 115

PS-MVSNAJ		77.04 217	76.53 220	78.56 228	87.09 211	61.40 228	75.26 289	87.13 197	61.25 274	74.38 293	77.22 328	76.94 133	90.94 178	64.63 224	84.83 297	83.35 285

xiu_mvs_v2_base		77.19 215	76.75 214	78.52 229	87.01 212	61.30 230	75.55 288	87.12 199	61.24 275	74.45 291	78.79 322	77.20 127	90.93 179	64.62 225	84.80 298	83.32 286

XVG-OURS-SEG-HR		89.59 49	89.37 52	90.28 42	94.47 40	85.95 21	86.84 96	93.91 27	80.07 72	86.75 150	93.26 100	93.64 2	90.93 179	84.60 45	90.75 234	93.97 100

v148		82.31 170	82.48 167	81.81 193	85.59 239	59.66 244	81.47 214	86.02 210	72.85 169	88.05 131	90.65 175	70.73 212	90.91 181	75.15 142	91.79 206	94.87 77

VDD-MVS		84.23 138	84.58 132	83.20 168	91.17 117	65.16 176	83.25 168	84.97 225	79.79 73	87.18 142	94.27 74	74.77 157	90.89 182	69.24 189	96.54 83	93.55 119

alignmvs		83.94 149	83.98 147	83.80 149	87.80 186	67.88 161	84.54 132	91.42 109	73.27 164	88.41 128	87.96 219	72.33 201	90.83 183	76.02 138	94.11 158	92.69 136

ITE_SJBPF				90.11 45	90.72 126	84.97 33		90.30 141	81.56 59	90.02 86	91.20 151	82.40 78	90.81 184	73.58 155	94.66 150	94.56 81

BH-RMVSNet		80.53 192	80.22 193	81.49 195	87.19 206	66.21 170	77.79 268	86.23 207	74.21 149	83.69 197	88.50 208	73.25 188	90.75 185	63.18 233	87.90 265	87.52 234

BH-w/o		76.57 225	76.07 224	78.10 235	86.88 214	65.92 172	77.63 269	86.33 206	65.69 241	80.89 232	79.95 317	68.97 219	90.74 186	53.01 299	85.25 291	77.62 327

TR-MVS		76.77 223	75.79 225	79.72 214	86.10 236	65.79 173	77.14 273	83.02 231	65.20 247	81.40 227	82.10 302	66.30 226	90.73 187	55.57 285	85.27 290	82.65 292

GBi-Net		82.02 175	82.07 171	81.85 190	86.38 219	61.05 234	86.83 97	88.27 178	72.43 173	86.00 162	95.64 33	63.78 236	90.68 188	65.95 214	93.34 178	93.82 106

test1		82.02 175	82.07 171	81.85 190	86.38 219	61.05 234	86.83 97	88.27 178	72.43 173	86.00 162	95.64 33	63.78 236	90.68 188	65.95 214	93.34 178	93.82 106

FMVSNet1		84.55 125	85.45 110	81.85 190	90.27 133	61.05 234	86.83 97	88.27 178	78.57 93	89.66 100	95.64 33	75.43 145	90.68 188	69.09 192	95.33 124	93.82 106

VDDNet		84.35 134	85.39 111	81.25 199	95.13 29	59.32 247	85.42 120	81.11 244	86.41 22	87.41 140	96.21 21	73.61 176	90.61 191	66.33 212	96.85 73	93.81 109

MAR-MVS		80.24 196	78.74 203	84.73 126	86.87 215	78.18 77	85.75 115	87.81 186	65.67 242	77.84 264	78.50 323	73.79 171	90.53 192	61.59 243	90.87 231	85.49 255
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
MVS_Test		82.47 169	83.22 155	80.22 209	82.62 276	57.75 256	82.54 187	91.96 87	71.16 197	82.89 210	92.52 120	77.41 126	90.50 193	80.04 103	87.84 267	92.40 148

MVS_111021_HR		84.63 122	84.34 142	85.49 113	90.18 134	75.86 102	79.23 255	87.13 197	73.35 158	85.56 170	89.34 198	83.60 65	90.50 193	76.64 135	94.05 160	90.09 208

Regformer-3		85.06 113	84.67 126	86.22 97	84.27 257	73.43 114	84.07 138	85.26 217	80.77 65	88.62 123	85.48 250	80.56 102	90.39 195	81.99 78	91.04 222	94.85 79

EI-MVSNet		82.61 166	82.42 168	83.20 168	83.25 270	63.66 187	83.50 161	85.07 221	76.06 125	86.55 153	85.10 258	73.41 180	90.25 196	78.15 122	90.67 236	95.68 58

MVSTER		77.09 216	75.70 228	81.25 199	75.27 333	61.08 233	77.49 272	85.07 221	60.78 277	86.55 153	88.68 206	43.14 328	90.25 196	73.69 154	90.67 236	92.42 146

Fast-Effi-MVS+-dtu		82.54 168	81.41 179	85.90 106	85.60 238	76.53 97	83.07 172	89.62 161	73.02 168	79.11 258	83.51 277	80.74 100	90.24 198	68.76 195	89.29 248	90.94 183

SD-MVS		88.96 57	89.88 45	86.22 97	91.63 100	77.07 90	89.82 46	93.77 30	78.90 87	92.88 40	92.29 125	86.11 50	90.22 199	86.24 31	97.24 64	91.36 176

FMVSNet2		81.31 181	81.61 177	80.41 207	86.38 219	58.75 252	83.93 144	86.58 205	72.43 173	87.65 136	92.98 106	63.78 236	90.22 199	66.86 207	93.92 163	92.27 154

OpenMVS	76.72 13	81.98 177	82.00 173	81.93 186	84.42 255	68.22 159	88.50 73	89.48 163	66.92 230	81.80 223	91.86 131	72.59 199	90.16 201	71.19 174	91.25 218	87.40 236

xiu_mvs_v1_base_debu		80.84 189	80.14 194	82.93 173	88.31 166	71.73 133	79.53 239	87.17 194	65.43 243	79.59 252	82.73 291	76.94 133	90.14 202	73.22 159	88.33 258	86.90 241

xiu_mvs_v1_base		80.84 189	80.14 194	82.93 173	88.31 166	71.73 133	79.53 239	87.17 194	65.43 243	79.59 252	82.73 291	76.94 133	90.14 202	73.22 159	88.33 258	86.90 241

xiu_mvs_v1_base_debi		80.84 189	80.14 194	82.93 173	88.31 166	71.73 133	79.53 239	87.17 194	65.43 243	79.59 252	82.73 291	76.94 133	90.14 202	73.22 159	88.33 258	86.90 241

FMVSNet3		78.80 204	78.55 204	79.57 218	82.89 274	56.89 262	81.76 208	85.77 212	69.04 216	86.00 162	90.44 179	51.75 286	90.09 205	65.95 214	93.34 178	91.72 166

LFMVS		80.15 198	80.56 188	78.89 222	89.19 148	55.93 267	85.22 122	73.78 282	82.96 42	84.28 193	92.72 115	57.38 267	90.07 206	63.80 228	95.75 116	90.68 192

MVS		73.21 260	72.59 263	75.06 269	80.97 287	60.81 237	81.64 211	85.92 211	46.03 341	71.68 306	77.54 325	68.47 220	89.77 207	55.70 284	85.39 288	74.60 333

LCM-MVSNet-Re		83.48 157	85.06 114	78.75 225	85.94 237	55.75 270	80.05 232	94.27 13	76.47 122	96.09 5	94.54 64	83.31 68	89.75 208	59.95 252	94.89 139	90.75 190

CANet_DTU		77.81 210	77.05 211	80.09 210	81.37 283	59.90 243	83.26 167	88.29 177	69.16 214	67.83 323	83.72 275	60.93 244	89.47 209	69.22 191	89.70 246	90.88 186

GA-MVS		75.83 233	74.61 236	79.48 220	81.87 279	59.25 248	73.42 302	82.88 232	68.68 218	79.75 251	81.80 305	50.62 288	89.46 210	66.85 208	85.64 287	89.72 209

MVP-Stereo		75.81 234	73.51 254	82.71 176	89.35 144	73.62 112	80.06 231	85.20 218	60.30 279	73.96 294	87.94 220	57.89 264	89.45 211	52.02 302	74.87 335	85.06 259
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
Vis-MVSNet (Re-imp)		77.82 209	77.79 208	77.92 238	88.82 154	51.29 305	83.28 166	71.97 298	74.04 150	82.23 214	89.78 191	57.38 267	89.41 212	57.22 276	95.41 122	93.05 127

MSLP-MVS++		85.00 116	86.03 101	81.90 187	91.84 98	71.56 138	86.75 101	93.02 57	75.95 128	87.12 143	89.39 197	77.98 119	89.40 213	77.46 127	94.78 145	84.75 266

tfpn111		76.03 231	75.53 229	77.53 246	87.27 201	51.88 297	81.07 221	73.26 287	75.68 132	83.25 204	86.37 238	45.54 308	89.38 214	55.07 290	92.26 201	91.34 177

view600		76.79 219	76.54 216	77.56 242	87.91 178	50.77 311	81.92 203	71.35 306	77.38 107	84.62 181	88.40 210	45.18 318	89.26 215	58.58 265	93.49 173	92.66 137

view800		76.79 219	76.54 216	77.56 242	87.91 178	50.77 311	81.92 203	71.35 306	77.38 107	84.62 181	88.40 210	45.18 318	89.26 215	58.58 265	93.49 173	92.66 137

conf0.05thres1000		76.79 219	76.54 216	77.56 242	87.91 178	50.77 311	81.92 203	71.35 306	77.38 107	84.62 181	88.40 210	45.18 318	89.26 215	58.58 265	93.49 173	92.66 137

tfpn		76.79 219	76.54 216	77.56 242	87.91 178	50.77 311	81.92 203	71.35 306	77.38 107	84.62 181	88.40 210	45.18 318	89.26 215	58.58 265	93.49 173	92.66 137

thres600view7		75.97 232	75.35 232	77.85 240	87.01 212	51.84 301	80.45 229	73.26 287	75.20 141	83.10 208	86.31 243	45.54 308	89.05 219	55.03 291	92.24 202	92.66 137

jason		77.42 213	75.75 227	82.43 183	87.10 210	69.27 150	77.99 265	81.94 240	51.47 322	77.84 264	85.07 260	60.32 248	89.00 220	70.74 178	89.27 250	89.03 219
jason: jason.
lupinMVS		76.37 228	74.46 239	82.09 184	85.54 240	69.26 151	76.79 274	80.77 247	50.68 329	76.23 276	82.82 289	58.69 259	88.94 221	69.85 184	88.77 254	88.07 226

PMVS	80.48 6	90.08 34	90.66 36	88.34 66	96.71 2	92.97 2	90.31 37	89.57 162	88.51 15	90.11 83	95.12 47	90.98 8	88.92 222	77.55 126	97.07 68	83.13 290
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
conf200view11		75.62 235	75.05 233	77.34 248	87.27 201	51.88 297	81.07 221	73.26 287	75.68 132	83.25 204	86.37 238	45.54 308	88.80 223	51.98 303	90.99 224	91.34 177

thres100view900		75.45 236	75.05 233	76.66 257	87.27 201	51.88 297	81.07 221	73.26 287	75.68 132	83.25 204	86.37 238	45.54 308	88.80 223	51.98 303	90.99 224	89.31 214

tfpn200view9		74.86 243	74.23 241	76.74 256	86.24 225	52.12 294	79.24 252	73.87 280	73.34 159	81.82 221	84.60 268	46.02 302	88.80 223	51.98 303	90.99 224	89.31 214

thres400		75.14 237	74.23 241	77.86 239	86.24 225	52.12 294	79.24 252	73.87 280	73.34 159	81.82 221	84.60 268	46.02 302	88.80 223	51.98 303	90.99 224	92.66 137

TAMVS		78.08 208	76.36 221	83.23 167	90.62 127	72.87 117	79.08 256	80.01 251	61.72 271	81.35 228	86.92 233	63.96 235	88.78 227	50.61 308	93.01 189	88.04 228

CDS-MVSNet		77.32 214	75.40 230	83.06 170	89.00 151	72.48 122	77.90 267	82.17 237	60.81 276	78.94 259	83.49 278	59.30 256	88.76 228	54.64 294	92.37 198	87.93 231
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
tpmp4_e23		69.43 289	67.33 296	75.72 266	78.53 308	52.75 289	82.13 201	74.91 273	49.23 335	66.37 326	84.17 272	41.28 338	88.67 229	49.73 313	79.63 321	85.75 252

OpenMVS_ROB	70.19 17	77.77 211	77.46 209	78.71 226	84.39 256	61.15 232	81.18 220	82.52 234	62.45 266	83.34 203	87.37 229	66.20 227	88.66 230	64.69 223	85.02 294	86.32 245

tpm2		68.45 294	66.83 298	73.30 282	78.93 304	48.50 327	79.76 236	71.76 301	47.50 337	69.92 315	83.60 276	42.07 331	88.40 231	48.44 319	79.51 322	83.01 291

新几何1				82.95 172	93.96 45	78.56 76		80.24 248	55.45 298	83.93 196	91.08 158	71.19 211	88.33 232	65.84 217	93.07 186	81.95 305

ACMH	76.49 14	89.34 53	91.14 28	83.96 147	92.50 78	70.36 144	89.55 54	93.84 29	81.89 56	94.70 16	95.44 39	90.69 10	88.31 233	83.33 59	98.30 28	93.20 124
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
thres200		72.34 268	71.55 273	74.70 272	83.48 267	51.60 302	75.02 291	73.71 283	70.14 206	78.56 260	80.57 312	46.20 300	88.20 234	46.99 325	89.29 248	84.32 271

gm-plane-assit					75.42 331	44.97 338			52.17 315		72.36 341		87.90 235	54.10 295

EU-MVSNet		75.12 239	74.43 240	77.18 249	83.11 273	59.48 246	85.71 117	82.43 235	39.76 350	85.64 168	88.76 204	44.71 324	87.88 236	73.86 153	85.88 285	84.16 274

diffmvs		79.20 202	79.04 200	79.69 215	78.64 307	58.90 249	81.79 207	87.61 188	65.07 249	73.65 297	89.80 190	73.10 190	87.79 237	75.02 144	86.63 277	92.38 149

RPSCF		88.00 67	86.93 86	91.22 27	90.08 135	89.30 6	89.68 49	91.11 120	79.26 81	89.68 99	94.81 58	82.44 77	87.74 238	76.54 136	88.74 256	96.61 38

CostFormer		69.98 287	68.68 290	73.87 278	77.14 316	50.72 315	79.26 251	74.51 278	51.94 319	70.97 311	84.75 265	45.16 322	87.49 239	55.16 289	79.23 325	83.40 284

CVMVSNet		72.62 264	71.41 274	76.28 261	83.25 270	60.34 240	83.50 161	79.02 254	37.77 351	76.33 274	85.10 258	49.60 291	87.41 240	70.54 181	77.54 331	81.08 320

wuykxyi23d		88.46 63	88.80 61	87.44 81	90.96 121	93.03 1	85.85 114	81.96 238	74.58 145	98.58 2	97.29 5	87.73 31	87.31 241	82.84 68	99.41 1	81.99 303

VPA-MVSNet		83.47 158	84.73 121	79.69 215	90.29 132	57.52 257	81.30 218	88.69 171	76.29 123	87.58 137	94.44 67	80.60 101	87.20 242	66.60 211	96.82 76	94.34 91

patchmatchnet-post											81.71 306	45.93 305	87.01 243

mvs_anonymous		78.13 207	78.76 202	76.23 262	79.24 301	50.31 317	78.69 260	84.82 226	61.60 273	83.09 209	92.82 111	73.89 170	87.01 243	68.33 200	86.41 280	91.37 175

TinyColmap		81.25 184	82.34 169	77.99 237	85.33 243	60.68 238	82.32 192	88.33 176	71.26 196	86.97 148	92.22 128	77.10 130	86.98 245	62.37 234	95.17 131	86.31 246

TransMVSNet (Re)		84.02 146	85.74 104	78.85 223	91.00 120	55.20 275	82.29 193	87.26 192	79.65 76	88.38 129	95.52 37	83.00 70	86.88 246	67.97 202	96.60 81	94.45 88

LF4IMVS		82.75 165	81.93 174	85.19 115	82.08 277	80.15 61	85.53 118	88.76 170	68.01 221	85.58 169	87.75 223	71.80 207	86.85 247	74.02 150	93.87 164	88.58 223

conf0.01		74.17 249	73.53 248	76.08 263	86.13 230	50.06 320	79.45 243	68.54 319	72.01 183	80.76 235	82.50 294	41.39 332	86.83 248	59.66 255	91.36 211	91.34 177

conf0.002		74.17 249	73.53 248	76.08 263	86.13 230	50.06 320	79.45 243	68.54 319	72.01 183	80.76 235	82.50 294	41.39 332	86.83 248	59.66 255	91.36 211	91.34 177

thresconf0.02		73.65 254	73.53 248	73.98 274	86.13 230	50.06 320	79.45 243	68.54 319	72.01 183	80.76 235	82.50 294	41.39 332	86.83 248	59.66 255	91.36 211	85.06 259

tfpn_n400		73.65 254	73.53 248	73.98 274	86.13 230	50.06 320	79.45 243	68.54 319	72.01 183	80.76 235	82.50 294	41.39 332	86.83 248	59.66 255	91.36 211	85.06 259

tfpnconf		73.65 254	73.53 248	73.98 274	86.13 230	50.06 320	79.45 243	68.54 319	72.01 183	80.76 235	82.50 294	41.39 332	86.83 248	59.66 255	91.36 211	85.06 259

tfpnview11		73.65 254	73.53 248	73.98 274	86.13 230	50.06 320	79.45 243	68.54 319	72.01 183	80.76 235	82.50 294	41.39 332	86.83 248	59.66 255	91.36 211	85.06 259

pmmvs6		86.52 89	88.06 66	81.90 187	92.22 88	62.28 219	84.66 129	89.15 167	83.54 36	89.85 94	97.32 4	88.08 28	86.80 254	70.43 182	97.30 63	96.62 37

tfpn_ndepth		72.54 265	72.30 266	73.24 283	84.81 249	51.42 303	79.24 252	70.49 312	69.26 212	78.48 261	79.80 318	40.16 342	86.77 255	58.08 274	90.43 241	81.53 313

1112_ss		74.82 244	73.74 244	78.04 236	89.57 142	60.04 242	76.49 279	87.09 200	54.31 303	73.66 296	79.80 318	60.25 249	86.76 256	58.37 269	84.15 301	87.32 237

tfpn1000		73.63 258	73.58 246	73.79 280	85.46 242	50.31 317	79.99 234	68.18 325	72.33 177	80.66 241	83.05 282	39.80 343	86.74 257	60.96 247	91.78 207	84.32 271

USDC		76.63 224	76.73 215	76.34 260	83.46 268	57.20 259	80.02 233	88.04 182	52.14 317	83.65 200	91.25 147	63.24 239	86.65 258	54.66 293	94.11 158	85.17 257

tfpnnormal		81.79 178	82.95 159	78.31 231	88.93 152	55.40 271	80.83 227	82.85 233	76.81 119	85.90 165	94.14 80	74.58 161	86.51 259	66.82 210	95.68 119	93.01 128

VPNet		80.25 195	81.68 175	75.94 265	92.46 79	47.98 330	76.70 276	81.67 242	73.45 156	84.87 177	92.82 111	74.66 159	86.51 259	61.66 241	96.85 73	93.33 120

testdata2													86.43 261	63.52 230

MSDG		80.06 199	79.99 197	80.25 208	83.91 265	68.04 160	77.51 271	89.19 166	77.65 103	81.94 218	83.45 279	76.37 141	86.31 262	63.31 232	86.59 278	86.41 244

MVS_111021_LR		84.28 136	83.76 150	85.83 109	89.23 147	83.07 48	80.99 224	83.56 229	72.71 171	86.07 161	89.07 201	81.75 91	86.19 263	77.11 132	93.36 177	88.24 224

Baseline_NR-MVSNet		84.00 147	85.90 102	78.29 232	91.47 109	53.44 285	82.29 193	87.00 202	79.06 85	89.55 108	95.72 30	77.20 127	86.14 264	72.30 168	98.51 18	95.28 70

EPNet_dtu		72.87 262	71.33 275	77.49 247	77.72 313	60.55 239	82.35 191	75.79 268	66.49 233	58.39 350	81.06 311	53.68 282	85.98 265	53.55 297	92.97 190	85.95 249
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
ANet_high		83.17 162	85.68 106	75.65 267	81.24 284	45.26 335	79.94 235	92.91 60	83.83 35	91.33 71	96.88 10	80.25 104	85.92 266	68.89 194	95.89 110	95.76 53

Test_1112_low_res		73.90 252	73.08 257	76.35 259	90.35 131	55.95 266	73.40 303	86.17 208	50.70 328	73.14 298	85.94 246	58.31 261	85.90 267	56.51 279	83.22 305	87.20 238

MIMVSNet1		83.63 154	84.59 131	80.74 204	94.06 43	62.77 204	82.72 182	84.53 227	77.57 105	90.34 81	95.92 26	76.88 139	85.83 268	61.88 238	97.42 60	93.62 114

tpmvs		70.16 283	69.56 285	71.96 294	74.71 337	48.13 328	79.63 237	75.45 272	65.02 250	70.26 313	81.88 304	45.34 315	85.68 269	58.34 270	75.39 334	82.08 302

pm-mvs1		83.69 152	84.95 118	79.91 211	90.04 139	59.66 244	82.43 188	87.44 189	75.52 136	87.85 134	95.26 43	81.25 96	85.65 270	68.74 196	96.04 104	94.42 89

pmmvs-eth3d		78.42 206	77.04 212	82.57 180	87.44 195	74.41 109	80.86 226	79.67 252	55.68 297	84.69 180	90.31 183	60.91 245	85.42 271	62.20 235	91.59 209	87.88 232

testdata				79.54 219	92.87 69	72.34 123		80.14 250	59.91 281	85.47 172	91.75 138	67.96 221	85.24 272	68.57 199	92.18 205	81.06 322

1314		73.22 259	72.56 264	75.20 268	80.41 295	57.84 254	81.64 211	85.36 216	51.68 320	73.10 299	76.65 330	61.45 243	85.19 273	63.54 229	79.21 326	82.59 293

CHOSEN 1792x2688		72.45 266	70.56 277	78.13 234	90.02 140	63.08 198	68.72 317	83.16 230	42.99 347	75.92 279	85.46 252	57.22 269	85.18 274	49.87 312	81.67 314	86.14 247

pmmvs4		74.92 242	72.98 259	80.73 205	84.95 246	71.71 136	76.23 282	77.59 259	52.83 311	77.73 267	86.38 237	56.35 271	84.97 275	57.72 275	87.05 274	85.51 254

旧先验2							81.73 209		56.88 294	86.54 158			84.90 276	72.81 165

DWT-MVSNet_test		66.43 301	64.37 306	72.63 289	74.86 336	50.86 310	76.52 278	72.74 292	54.06 305	65.50 330	68.30 346	32.13 351	84.84 277	61.63 242	73.59 336	82.19 300

HY-MVS	64.64 18	73.03 261	72.47 265	74.71 271	83.36 269	54.19 278	82.14 200	81.96 238	56.76 295	69.57 316	86.21 244	60.03 250	84.83 278	49.58 314	82.65 310	85.11 258

ab-mvs		79.67 200	80.56 188	76.99 250	88.48 163	56.93 260	84.70 128	86.06 209	68.95 217	80.78 234	93.08 103	75.30 147	84.62 279	56.78 278	90.90 230	89.43 213

IterMVS		76.91 218	76.34 222	78.64 227	80.91 288	64.03 183	76.30 281	79.03 253	64.88 251	83.11 207	89.16 199	59.90 252	84.46 280	68.61 198	85.15 293	87.42 235
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
VNet		79.31 201	80.27 192	76.44 258	87.92 177	53.95 280	75.58 287	84.35 228	74.39 148	82.23 214	90.72 171	72.84 193	84.39 281	60.38 251	93.98 162	90.97 182

ppachtmachnet_test		74.73 245	74.00 243	76.90 252	80.71 292	56.89 262	71.53 308	78.42 255	58.24 286	79.32 256	82.92 288	57.91 263	84.26 282	65.60 219	91.36 211	89.56 210

CR-MVSNet		74.00 251	73.04 258	76.85 254	79.58 296	62.64 206	82.58 184	76.90 263	50.50 330	75.72 281	92.38 121	48.07 295	84.07 283	68.72 197	82.91 308	83.85 277

RPMNet		76.06 230	75.79 225	76.85 254	79.58 296	62.64 206	82.58 184	71.75 302	74.80 143	75.72 281	92.59 116	48.69 293	84.07 283	73.48 157	82.91 308	83.85 277

Patchmtry		76.56 226	77.46 209	73.83 279	79.37 300	46.60 332	82.41 189	76.90 263	73.81 153	85.56 170	92.38 121	48.07 295	83.98 285	63.36 231	95.31 127	90.92 184

gg-mvs-nofinetune		68.96 293	69.11 286	68.52 308	76.12 324	45.32 334	83.59 154	55.88 351	86.68 20	64.62 336	97.01 7	30.36 353	83.97 286	44.78 330	82.94 307	76.26 330

GG-mvs-BLEND				67.16 311	73.36 340	46.54 333	84.15 137	55.04 352		58.64 349	61.95 352	29.93 354	83.87 287	38.71 342	76.92 332	71.07 339

PM-MVS		80.20 197	79.00 201	83.78 151	88.17 170	86.66 13	81.31 216	66.81 334	69.64 209	88.33 130	90.19 184	64.58 232	83.63 288	71.99 172	90.03 243	81.06 322

JIA-IIPM		69.41 291	66.64 301	77.70 241	73.19 342	71.24 139	75.67 285	65.56 335	70.42 202	65.18 332	92.97 107	33.64 350	83.06 289	53.52 298	69.61 347	78.79 326

CMPMVS	59.41 20	75.12 239	73.57 247	79.77 212	75.84 325	67.22 163	81.21 219	82.18 236	50.78 327	76.50 272	87.66 225	55.20 278	82.99 290	62.17 237	90.64 239	89.09 218
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
PatchFormer-LS_test		67.91 296	66.49 302	72.17 293	75.29 332	51.85 300	75.68 284	73.62 285	57.23 292	68.64 317	68.13 347	42.19 330	82.76 291	64.06 227	73.51 337	81.89 307

Patchmatch-RL test		74.48 246	73.68 245	76.89 253	84.83 248	66.54 169	72.29 305	69.16 318	57.70 288	86.76 149	86.33 241	45.79 307	82.59 292	69.63 186	90.65 238	81.54 312

tpm cat1		66.76 300	65.21 305	71.42 295	77.09 317	50.62 316	78.01 264	73.68 284	44.89 343	68.64 317	79.00 321	45.51 312	82.42 293	49.91 311	70.15 344	81.23 319

Patchmatch-test1		72.75 263	72.61 262	73.19 284	81.62 281	55.86 268	78.89 258	71.37 305	61.73 270	74.93 288	82.15 301	60.46 247	81.80 294	59.68 254	82.63 312	81.92 306

MS-PatchMatch		70.93 278	70.22 281	73.06 286	81.85 280	62.50 212	73.82 300	77.90 257	52.44 314	75.92 279	81.27 309	55.67 275	81.75 295	55.37 287	77.70 329	74.94 332

CNLPA		83.55 156	83.10 158	84.90 120	89.34 145	83.87 43	84.54 132	88.77 169	79.09 84	83.54 202	88.66 207	74.87 153	81.73 296	66.84 209	92.29 199	89.11 217

MDA-MVSNet-bldmvs		77.47 212	76.90 213	79.16 221	79.03 303	64.59 178	66.58 326	75.67 270	73.15 166	88.86 117	88.99 202	66.94 224	81.23 297	64.71 222	88.22 263	91.64 168

MDTV_nov1_ep13			68.29 293		78.03 312	43.87 340	74.12 297	72.22 296	52.17 315	67.02 325	85.54 248	45.36 314	80.85 298	55.73 282	84.42 300

pmmvs5		70.73 279	70.07 282	72.72 288	77.03 318	52.73 290	74.14 296	75.65 271	50.36 331	72.17 304	85.37 256	55.42 277	80.67 299	52.86 300	87.59 270	84.77 265

Gipuma		84.44 128	86.33 94	78.78 224	84.20 260	73.57 113	89.55 54	90.44 133	84.24 31	84.38 189	94.89 52	76.35 142	80.40 300	76.14 137	96.80 77	82.36 298
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
no-one		71.52 275	70.43 280	74.81 270	78.45 309	63.41 190	57.73 343	77.03 262	51.46 323	77.17 270	90.33 181	54.96 280	80.35 301	47.41 322	99.29 2	80.68 324

test_post1							78.85 259				3.13 356	45.19 317	80.13 302	58.11 273

PatchmatchNet		69.71 288	68.83 288	72.33 292	77.66 314	53.60 283	79.29 250	69.99 314	57.66 289	72.53 301	82.93 287	46.45 299	80.08 303	60.91 248	72.09 340	83.31 287
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
FMVSNet5		72.10 270	71.69 270	73.32 281	81.57 282	53.02 288	76.77 275	78.37 256	63.31 257	76.37 273	91.85 132	36.68 346	78.98 304	47.87 321	92.45 197	87.95 230

our_test_3		71.85 271	71.59 271	72.62 290	80.71 292	53.78 282	69.72 315	71.71 304	58.80 283	78.03 263	80.51 313	56.61 270	78.84 305	62.20 235	86.04 284	85.23 256

PatchMatch-RL		74.48 246	73.22 256	78.27 233	87.70 189	85.26 30	75.92 283	70.09 313	64.34 253	76.09 278	81.25 310	65.87 230	78.07 306	53.86 296	83.82 302	71.48 338

ADS-MVSNet2		65.87 305	63.64 310	72.55 291	73.16 343	56.92 261	67.10 324	74.81 275	49.74 332	66.04 328	82.97 285	46.71 297	77.26 307	42.29 333	69.96 345	83.46 282

test_post											3.10 357	45.43 313	77.22 308

LP		69.42 290	68.30 292	72.77 287	71.48 350	56.84 264	73.66 301	74.84 274	63.52 255	70.95 312	83.35 281	49.55 292	77.15 309	57.13 277	70.21 343	84.33 270

MVS-HIRNet		61.16 317	62.92 312	55.87 334	79.09 302	35.34 350	71.83 306	57.98 350	46.56 339	59.05 347	91.14 154	49.95 290	76.43 310	38.74 341	71.92 341	55.84 351

MIMVSNet		71.09 277	71.59 271	69.57 301	87.23 204	50.07 319	78.91 257	71.83 300	60.20 280	71.26 308	91.76 137	55.08 279	76.09 311	41.06 336	87.02 275	82.54 295

tpm		67.95 295	68.08 294	67.55 310	78.74 306	43.53 341	75.60 286	67.10 333	54.92 301	72.23 303	88.10 217	42.87 329	75.97 312	52.21 301	80.95 320	83.15 289

FPMVS		72.29 269	72.00 268	73.14 285	88.63 159	85.00 32	74.65 294	67.39 328	71.94 190	77.80 266	87.66 225	50.48 289	75.83 313	49.95 310	79.51 322	58.58 350

PatchT		70.52 280	72.76 260	63.79 321	79.38 299	33.53 351	77.63 269	65.37 336	73.61 154	71.77 305	92.79 114	44.38 325	75.65 314	64.53 226	85.37 289	82.18 301

PVSNet	58.17 21	66.41 302	65.63 304	68.75 305	81.96 278	49.88 326	62.19 333	72.51 295	51.03 325	68.04 321	75.34 335	50.84 287	74.77 315	45.82 329	82.96 306	81.60 311

tpmrst		66.28 303	66.69 300	65.05 319	72.82 346	39.33 346	78.20 263	70.69 311	53.16 310	67.88 322	80.36 314	48.18 294	74.75 316	58.13 272	70.79 342	81.08 320

test20.03		73.75 253	74.59 238	71.22 296	81.11 286	51.12 307	70.15 313	72.10 297	70.42 202	80.28 249	91.50 143	64.21 233	74.72 317	46.96 326	94.58 152	87.82 233

testmv		70.47 281	70.70 276	69.77 299	86.22 227	53.89 281	67.32 323	71.91 299	63.32 256	78.16 262	89.47 196	56.12 273	73.10 318	36.43 344	87.33 271	82.33 299

pmmvs3		62.47 309	60.02 322	69.80 298	71.58 349	64.00 184	70.52 311	58.44 348	39.77 349	66.05 327	75.84 332	27.10 358	72.28 319	46.15 327	84.77 299	73.11 336

Anonymous20231206		71.38 276	71.88 269	69.88 297	86.31 223	54.37 277	70.39 312	74.62 276	52.57 313	76.73 271	88.76 204	59.94 251	72.06 320	44.35 331	93.23 185	83.23 288

new-patchmatchnet		70.10 284	73.37 255	60.29 330	81.23 285	16.95 358	59.54 337	74.62 276	62.93 260	80.97 230	87.93 221	62.83 240	71.90 321	55.24 288	95.01 136	92.00 160

dp		60.70 320	60.29 321	61.92 325	72.04 348	38.67 348	70.83 309	64.08 337	51.28 324	60.75 341	77.28 327	36.59 347	71.58 322	47.41 322	62.34 351	75.52 331

UnsupCasMVSNet_bld		69.21 292	69.68 284	67.82 309	79.42 298	51.15 306	67.82 322	75.79 268	54.15 304	77.47 268	85.36 257	59.26 257	70.64 323	48.46 318	79.35 324	81.66 310

test1235678		65.57 306	65.73 303	65.06 318	82.84 275	50.90 309	62.90 331	69.26 316	57.17 293	72.36 302	83.04 283	46.02 302	70.10 324	32.79 349	85.24 292	74.19 334

test-LLR		67.21 298	66.74 299	68.63 306	76.45 322	55.21 273	67.89 319	67.14 331	62.43 267	65.08 333	72.39 339	43.41 326	69.37 325	61.00 245	84.89 295	81.31 315

test-mter		65.00 307	63.79 308	68.63 306	76.45 322	55.21 273	67.89 319	67.14 331	50.98 326	65.08 333	72.39 339	28.27 356	69.37 325	61.00 245	84.89 295	81.31 315

XXY-MVS		74.44 248	76.19 223	69.21 302	84.61 251	52.43 293	71.70 307	77.18 261	60.73 278	80.60 242	90.96 164	75.44 144	69.35 327	56.13 281	88.33 258	85.86 251

UnsupCasMVSNet_eth		71.63 274	72.30 266	69.62 300	76.47 321	52.70 291	70.03 314	80.97 246	59.18 282	79.36 255	88.21 216	60.50 246	69.12 328	58.33 271	77.62 330	87.04 239

WTY-MVS		67.91 296	68.35 291	66.58 313	80.82 290	48.12 329	65.96 327	72.60 293	53.67 307	71.20 309	81.68 307	58.97 258	69.06 329	48.57 317	81.67 314	82.55 294

test0.0.03 1		64.66 308	64.36 307	65.57 316	75.03 335	46.89 331	64.69 329	61.58 344	62.43 267	71.18 310	77.54 325	43.41 326	68.47 330	40.75 337	82.65 310	81.35 314

CHOSEN 280x420		59.08 321	56.52 326	66.76 312	76.51 320	64.39 181	49.62 350	59.00 346	43.86 345	55.66 353	68.41 345	35.55 348	68.21 331	43.25 332	76.78 333	67.69 343

YYNet1		70.06 285	70.44 278	68.90 303	73.76 339	53.42 286	58.99 341	67.20 330	58.42 285	87.10 144	85.39 255	59.82 253	67.32 332	59.79 253	83.50 304	85.96 248

MDA-MVSNet_test_wron		70.05 286	70.44 278	68.88 304	73.84 338	53.47 284	58.93 342	67.28 329	58.43 284	87.09 145	85.40 254	59.80 254	67.25 333	59.66 255	83.54 303	85.92 250

EMVS		61.10 318	60.81 318	61.99 324	65.96 354	55.86 268	53.10 348	58.97 347	67.06 228	56.89 352	63.33 350	40.98 339	67.03 334	54.79 292	86.18 283	63.08 345

testgi		72.36 267	74.61 236	65.59 315	80.56 294	42.82 343	68.29 318	73.35 286	66.87 231	81.84 220	89.93 188	72.08 204	66.92 335	46.05 328	92.54 196	87.01 240

testpf		58.55 322	61.58 317	49.48 339	66.03 353	40.05 345	74.40 295	58.07 349	64.72 252	59.36 345	72.67 338	22.76 359	66.92 335	67.07 206	69.15 348	41.46 353

EPMVS		62.47 309	62.63 313	62.01 323	70.63 351	38.74 347	74.76 292	52.86 353	53.91 306	67.71 324	80.01 316	39.40 344	66.60 337	55.54 286	68.81 349	80.68 324

PMMVS		61.65 314	60.38 319	65.47 317	65.40 355	69.26 151	63.97 330	61.73 343	36.80 352	60.11 343	68.43 343	59.42 255	66.35 338	48.97 316	78.57 327	60.81 347

E-PMN		61.59 315	61.62 315	61.49 326	66.81 352	55.40 271	53.77 347	60.34 345	66.80 232	58.90 348	65.50 349	40.48 341	66.12 339	55.72 283	86.25 282	62.95 346

PVSNet_0	51.08 22	56.10 324	54.97 328	59.48 332	75.12 334	53.28 287	55.16 344	61.89 341	44.30 344	59.16 346	62.48 351	54.22 281	65.91 340	35.40 346	47.01 352	59.25 349

test2356		56.69 323	55.15 327	61.32 328	73.20 341	44.11 339	54.95 345	62.52 339	48.75 336	62.45 339	68.42 344	21.10 360	65.67 341	26.86 353	78.08 328	74.19 334

sss		66.92 299	67.26 297	65.90 314	77.23 315	51.10 308	64.79 328	71.72 303	52.12 318	70.13 314	80.18 315	57.96 262	65.36 342	50.21 309	81.01 319	81.25 317

TESTMET0.1,1		61.29 316	60.32 320	64.19 320	72.06 347	51.30 304	67.89 319	62.09 340	45.27 342	60.65 342	69.01 342	27.93 357	64.74 343	56.31 280	81.65 316	76.53 328

testus		62.33 311	63.03 311	60.20 331	78.78 305	40.74 344	59.14 338	69.80 315	49.26 334	71.41 307	74.72 337	52.33 285	63.52 344	29.84 351	82.01 313	76.36 329

PNet_i23d		52.13 328	51.24 330	54.79 337	75.56 327	45.26 335	54.54 346	52.55 354	66.95 229	57.19 351	65.82 348	13.15 363	63.40 345	36.39 345	39.04 354	55.71 352

ADS-MVSNet		61.90 312	62.19 314	61.03 329	73.16 343	36.42 349	67.10 324	61.75 342	49.74 332	66.04 328	82.97 285	46.71 297	63.21 346	42.29 333	69.96 345	83.46 282

DSMNet-mixed		60.98 319	61.61 316	59.09 333	72.88 345	45.05 337	74.70 293	46.61 357	26.20 353	65.34 331	90.32 182	55.46 276	63.12 347	41.72 335	81.30 318	69.09 342

test12356		54.91 327	57.14 325	48.22 340	75.83 326	17.47 357	52.31 349	69.20 317	51.66 321	60.11 343	75.40 334	29.77 355	62.62 348	27.64 352	72.37 339	64.59 344

Patchmatch-test		65.91 304	67.38 295	61.48 327	75.51 329	43.21 342	68.84 316	63.79 338	62.48 265	72.80 300	83.42 280	44.89 323	59.52 349	48.27 320	86.45 279	81.70 308

1111		61.71 313	63.77 309	55.55 336	78.05 310	25.74 355	60.62 334	67.52 326	66.09 236	74.68 289	86.50 235	16.00 361	59.22 350	38.79 339	85.65 286	81.70 308

.test1245		48.02 330	54.41 329	28.84 343	78.05 310	25.74 355	60.62 334	67.52 326	66.09 236	74.68 289	86.50 235	16.00 361	59.22 350	38.79 339	1.47 356	1.55 357

N_pmnet		70.20 282	68.80 289	74.38 273	80.91 288	84.81 35	59.12 340	76.45 267	55.06 300	75.31 286	82.36 300	55.74 274	54.82 352	47.02 324	87.24 273	83.52 281

wuyk23d		75.13 238	79.30 199	62.63 322	75.56 327	75.18 105	80.89 225	73.10 291	75.06 142	94.76 15	95.32 40	87.73 31	52.85 353	34.16 347	97.11 67	59.85 348

PMMVS2		55.64 326	59.27 323	44.74 341	64.30 356	12.32 359	40.60 351	49.79 356	53.19 309	65.06 335	84.81 264	53.60 283	49.76 354	32.68 350	89.41 247	72.15 337

new_pmnet		55.69 325	57.66 324	49.76 338	75.47 330	30.59 352	59.56 336	51.45 355	43.62 346	62.49 338	75.48 333	40.96 340	49.15 355	37.39 343	72.52 338	69.55 341

MVE	40.22 23	51.82 329	50.47 331	55.87 334	62.66 357	51.91 296	31.61 353	39.28 358	40.65 348	50.76 354	74.98 336	56.24 272	44.67 356	33.94 348	64.11 350	71.04 340
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
DeepMVS_CX				24.13 344	32.95 358	29.49 353		21.63 361	12.07 354	37.95 355	45.07 353	30.84 352	19.21 357	17.94 355	33.06 355	23.69 354

tmp_tt		20.25 333	24.50 334	7.49 345	4.47 359	8.70 360	34.17 352	25.16 360	1.00 355	32.43 356	18.49 354	39.37 345	9.21 358	21.64 354	43.75 353	4.57 355

test123		6.27 336	8.08 337	0.84 346	1.11 361	0.57 361	62.90 331	0.82 362	0.54 356	1.07 358	2.75 359	1.26 364	0.30 359	1.04 356	1.26 358	1.66 356

testmvs		5.91 337	7.65 338	0.72 347	1.20 360	0.37 362	59.14 338	0.67 363	0.49 357	1.11 357	2.76 358	0.94 365	0.24 360	1.02 357	1.47 356	1.55 357

cdsmvs_eth3d_5k		20.81 332	27.75 333	0.00 348	0.00 362	0.00 363	0.00 354	85.44 215	0.00 358	0.00 359	82.82 289	81.46 93	0.00 361	0.00 358	0.00 359	0.00 359

pcd_1.5k_mvsjas		6.41 335	8.55 336	0.00 348	0.00 362	0.00 363	0.00 354	0.00 364	0.00 358	0.00 359	0.00 360	76.94 133	0.00 361	0.00 358	0.00 359	0.00 359

pcd1.5k->3k		38.83 331	41.11 332	32.01 342	93.13 63	0.00 363	0.00 354	91.38 113	0.00 358	0.00 359	0.00 360	89.24 16	0.00 361	0.00 358	96.24 95	96.02 48

sosnet-low-res		0.00 338	0.00 339	0.00 348	0.00 362	0.00 363	0.00 354	0.00 364	0.00 358	0.00 359	0.00 360	0.00 366	0.00 361	0.00 358	0.00 359	0.00 359

sosnet		0.00 338	0.00 339	0.00 348	0.00 362	0.00 363	0.00 354	0.00 364	0.00 358	0.00 359	0.00 360	0.00 366	0.00 361	0.00 358	0.00 359	0.00 359

uncertanet		0.00 338	0.00 339	0.00 348	0.00 362	0.00 363	0.00 354	0.00 364	0.00 358	0.00 359	0.00 360	0.00 366	0.00 361	0.00 358	0.00 359	0.00 359

Regformer		0.00 338	0.00 339	0.00 348	0.00 362	0.00 363	0.00 354	0.00 364	0.00 358	0.00 359	0.00 360	0.00 366	0.00 361	0.00 358	0.00 359	0.00 359

ab-mvs-re		6.65 334	8.87 335	0.00 348	0.00 362	0.00 363	0.00 354	0.00 364	0.00 358	0.00 359	79.80 318	0.00 366	0.00 361	0.00 358	0.00 359	0.00 359

uanet		0.00 338	0.00 339	0.00 348	0.00 362	0.00 363	0.00 354	0.00 364	0.00 358	0.00 359	0.00 360	0.00 366	0.00 361	0.00 358	0.00 359	0.00 359

GSMVS																83.88 275

test_part2					93.86 48	77.77 80				92.84 43

test_part1								93.93 25				87.19 36			97.61 55	91.48 173

sam_mvs1												46.11 301				83.88 275

sam_mvs												45.92 306

MTGPA								91.81 91

MTMP								33.14 359

test9_res														80.83 90	96.45 88	90.57 195

agg_prior2														79.68 107	96.16 97	90.22 203

test_prior4						78.97 72	84.59 130

test_prior2							83.37 164		75.43 137	84.58 185	91.57 140	81.92 88		79.54 109	96.97 70

新几何2							81.72 210

旧先验1					91.97 93	71.77 132		81.78 241			91.84 133	73.92 169			93.65 172	83.61 280

原ACMM2							82.26 196

test222					93.31 58	76.54 95	79.38 249	77.79 258	52.59 312	82.36 213	90.84 168	66.83 225			91.69 208	81.25 317

segment_acmp												81.94 85

testdata1							79.62 238		73.95 152

plane_prior7					93.45 54	77.31 88

plane_prior6					92.61 74	76.54 95						74.84 154

plane_prior4											92.95 108

plane_prior3						76.85 93			77.79 101	86.55 153

plane_prior2							89.45 59		79.44 79

plane_prior1					92.83 72

plane_prior						76.42 98	87.15 92		75.94 129						95.03 135

n2								0.00 364

nn								0.00 364

door-mid								74.45 279

test11								91.46 104

door								72.57 294

HQP5-MVS						70.66 142

HQP-NCC					91.19 114		84.77 125		73.30 161	80.55 245

ACMP_Plane					91.19 114		84.77 125		73.30 161	80.55 245

BP-MVS														77.30 130

HQP3-MVS								92.68 68							94.47 154

HQP2-MVS												72.10 202

NP-MVS					91.95 94	74.55 108					90.17 186

MDTV_nov1_ep13_2view						27.60 354	70.76 310		46.47 340	61.27 340		45.20 316		49.18 315		83.75 279

ACMMP++_ref															95.74 117

ACMMP++															97.35 61

Test By Simon												79.09 111

High-resolution multi-view benchmark