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.

xxxxxxxxxxxxxcwj		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

SF-MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

ETH3D cwj APD-0.16		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

ETH3 D test6400		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

ETH3D-3000-0.1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

train_agg		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

agg_prior1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

HFP-MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

region2R		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

#test#		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_prior3		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

1314		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

1121		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

MVS		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

abl_6		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

QAPM		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

hse-mvs3		0.30 17	0.30 18	0.30 22	0.30 29	0.30 29	0.30 29	0.30 30	0.30 29	0.30 28	0.30 26	0.30 28	0.30 29	0.30 27	0.30 27	0.30 27

hse-mvs2		0.30 17	0.30 18	0.30 22	0.30 29	0.30 29	0.30 29	0.30 30	0.30 29	0.30 28	0.30 26	0.30 28	0.30 29	0.30 27	0.30 27	0.30 27

CL-MVSNet_2432*1600		0.30 17	0.30 18	0.30 22	0.30 29	0.30 29	0.30 29	0.30 30	0.30 29	0.30 28	0.30 26	0.30 28	0.30 29	0.30 27	0.30 27	0.30 27

AUN-MVS		0.30 17	0.30 18	0.30 22	0.30 29	0.30 29	0.30 29	0.30 30	0.30 29	0.30 28	0.30 26	0.30 28	0.30 29	0.30 27	0.30 27	0.30 27

LCM-MVSNet		0.37 21	0.36 22	0.37 26	0.37 33	0.37 33	0.37 33	0.32 34	0.37 33	0.37 32	0.37 30	0.37 32	0.37 33	0.37 31	0.37 31	0.37 31

v144192		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v1921920		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v1192		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v1144		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v148		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v7n		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v1240		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v8		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v10		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

v2v482		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

V42		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

GA-MVS		0.40 22	0.40 23	0.40 27	0.40 34	0.40 34	0.40 34	0.40 36	0.40 34	0.40 33	0.40 31	0.40 33	0.40 34	0.40 32	0.40 32	0.40 32

Fast-Effi-MVS+		0.41 34	0.40 23	0.41 39	0.41 46	0.41 46	0.41 46	0.35 35	0.41 46	0.41 45	0.41 43	0.41 45	0.41 46	0.41 44	0.41 44	0.41 44

Fast-Effi-MVS+-dtu		0.44 35	0.44 36	0.44 40	0.44 47	0.44 47	0.44 47	0.44 48	0.44 47	0.44 46	0.44 44	0.44 46	0.44 47	0.44 45	0.44 45	0.44 45

Effi-MVS+		0.58 36	0.56 37	0.62 43	0.53 48	0.62 50	0.53 48	0.53 49	0.53 48	0.62 49	0.62 47	0.53 47	0.62 50	0.62 47	0.53 46	0.62 48

Effi-MVS+-dtu		0.59 37	0.61 39	0.53 41	0.68 53	0.53 48	0.53 48	0.68 54	0.68 53	0.53 47	0.53 45	0.68 52	0.53 48	0.68 51	0.53 46	0.53 46

DIV-MVS_2432*1600		0.60 38	0.60 38	0.60 42	0.60 49	0.60 49	0.60 50	0.60 50	0.60 49	0.60 48	0.60 46	0.60 48	0.60 49	0.60 46	0.60 48	0.60 47

EIA-MVS		0.62 39	0.62 40	0.62 43	0.62 50	0.62 50	0.62 51	0.62 51	0.62 50	0.62 49	0.62 47	0.62 49	0.62 50	0.62 47	0.62 49	0.62 48

ETV-MVS		0.62 39	0.62 40	0.62 43	0.62 50	0.62 50	0.62 51	0.62 51	0.62 50	0.62 49	0.62 47	0.62 49	0.62 50	0.62 47	0.62 49	0.62 48

CS-MVS		0.62 39	0.62 40	0.62 43	0.62 50	0.62 50	0.62 51	0.62 51	0.62 50	0.62 49	0.62 47	0.62 49	0.62 50	0.62 47	0.62 49	0.62 48

mvs-test1		0.68 42	0.68 43	0.68 47	0.68 53	0.68 54	0.68 54	0.68 54	0.68 53	0.68 53	0.68 51	0.68 52	0.68 54	0.68 51	0.68 52	0.68 52

CDS-MVSNet		0.88 43	0.88 44	0.88 48	0.88 55	0.88 55	0.88 55	0.88 56	0.88 55	0.88 54	0.88 52	0.88 54	0.88 55	0.88 53	0.88 53	0.88 53
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		0.88 43	0.88 44	0.88 48	0.88 55	0.88 55	0.88 55	0.88 56	0.88 55	0.88 54	0.88 52	0.88 54	0.88 55	0.88 53	0.88 53	0.88 53

LCM-MVSNet-Re		0.89 45	0.89 46	0.89 50	0.89 57	0.89 57	0.89 57	0.89 58	0.89 57	0.89 56	0.89 54	0.89 56	0.89 57	0.89 55	0.89 55	0.89 55

MDA-MVSNet-bldmvs		1.20 46	1.20 47	1.20 52	1.20 59	1.20 60	1.20 58	1.20 61	1.20 59	1.20 58	1.20 56	1.20 58	1.20 59	1.20 57	1.20 57	1.20 57

YYNet1		1.20 46	1.20 47	1.20 52	1.20 59	1.20 60	1.20 58	1.20 61	1.20 59	1.20 58	1.20 56	1.20 58	1.20 59	1.20 57	1.20 57	1.20 57

MDA-MVSNet_test_wron		1.20 46	1.20 47	1.20 52	1.20 59	1.20 60	1.20 58	1.20 61	1.20 59	1.20 58	1.20 56	1.20 58	1.20 59	1.20 57	1.20 57	1.20 57

KD-MVS_2432*1600		1.30 49	1.30 50	1.30 55	1.30 62	1.30 63	1.30 61	1.30 64	1.30 62	1.30 61	1.30 59	1.30 61	1.30 62	1.30 60	1.30 60	1.30 60

miper_refine_blended		1.30 49	1.30 50	1.30 55	1.30 62	1.30 63	1.30 61	1.30 64	1.30 62	1.30 61	1.30 59	1.30 61	1.30 62	1.30 60	1.30 60	1.30 60

EI-MVSNet-UG-set		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

EI-MVSNet-Vis-set		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

Regformer-3		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

Regformer-4		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

Regformer-1		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

Regformer-2		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

EI-MVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

Regformer		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

CVMVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

EU-MVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

PS-CasMVS		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

UniMVSNet_NR-MVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

PEN-MVS		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

TransMVSNet (Re)		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

DTE-MVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

DU-MVS		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

UniMVSNet (Re)		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

CP-MVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

WR-MVS_H		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

WR-MVS		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

NR-MVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

Baseline_NR-MVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

TranMVSNet+NR-MVSNet		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

MVSFormer		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

jason		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62
jason: jason.
lupinMVS		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

test_djsdf		1.42 51	1.42 52	1.42 57	1.42 64	1.42 65	1.42 63	1.42 66	1.42 64	1.42 63	1.42 61	1.42 63	1.42 64	1.42 62	1.42 62	1.42 62

alignmvs		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

nrg030		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

LFMVS		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

VDD-MVS		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

VDDNet		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

VPNet		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

VNet		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

VPA-MVSNet		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

cascas		2.00 78	2.00 79	2.00 84	2.00 91	2.00 92	2.00 90	2.00 95	2.00 91	2.00 90	2.00 88	2.00 90	2.00 91	2.00 89	2.00 89	2.00 89

UnsupCasMVSNet_eth		5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 107	5.90 101	5.90 99	5.90 97	5.90 101	5.90 100	5.90 98	5.90 101	5.90 101

UnsupCasMVSNet_bld		5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 107	5.90 101	5.90 99	5.90 97	5.90 101	5.90 100	5.90 98	5.90 101	5.90 101

WTY-MVS		5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 107	5.90 101	5.90 99	5.90 97	5.90 101	5.90 100	5.90 98	5.90 101	5.90 101

HY-MVS	5.90 1	5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 107	5.90 101	5.90 99	5.90 97	5.90 101	5.90 100	5.90 98	5.90 101	5.90 101

sss		5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 107	5.90 101	5.90 99	5.90 97	5.90 101	5.90 100	5.90 98	5.90 101	5.90 101

Test_1112_low_res		5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 107	5.90 101	5.90 99	5.90 97	5.90 101	5.90 100	5.90 98	5.90 101	5.90 101

1112_ss		5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 107	5.90 101	5.90 99	5.90 97	5.90 101	5.90 100	5.90 98	5.90 101	5.90 101

ab-mvs-re		5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 107	5.90 101	5.90 99	5.90 97	5.90 101	5.90 100	5.90 98	5.90 101	5.90 101

ab-mvs		5.90 87	5.90 88	5.90 93	5.90 100	5.90 101	5.90 100	5.90 107	5.90 101	5.90 99	5.90 97	5.90 101	5.90 100	5.90 98	5.90 101	5.90 101

CDPH-MVS		6.66 96	6.66 97	6.66 102	6.66 109	6.66 110	6.66 109	6.66 116	6.66 110	6.66 108	6.66 106	6.66 110	6.66 109	6.66 107	6.66 110	6.66 110

xiu_mvs_v1_base_debu		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 119	10.28 113	10.28 112	10.28 108	10.28 114	10.28 112	10.28 110	10.28 113	10.28 112

xiu_mvs_v2_base		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 119	10.28 113	10.28 112	10.28 108	10.28 114	10.28 112	10.28 110	10.28 113	10.28 112

xiu_mvs_v1_base		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 119	10.28 113	10.28 112	10.28 108	10.28 114	10.28 112	10.28 110	10.28 113	10.28 112

xiu_mvs_v1_base_debi		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 119	10.28 113	10.28 112	10.28 108	10.28 114	10.28 112	10.28 110	10.28 113	10.28 112

cdsmvs_eth3d_5k		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 119	10.28 113	10.28 112	10.28 108	10.28 114	10.28 112	10.28 110	10.28 113	10.28 112

pcd_1.5k_mvsjas		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 119	10.28 113	10.28 112	10.28 108	10.28 114	10.28 112	10.28 110	10.28 113	10.28 112

PS-MVSNAJss		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 119	10.28 113	10.28 112	10.28 108	10.28 114	10.28 112	10.28 110	10.28 113	10.28 112

PS-MVSNAJ		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 119	10.28 113	10.28 112	10.28 108	10.28 114	10.28 112	10.28 110	10.28 113	10.28 112

jajsoiax		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 119	10.28 113	10.28 112	10.28 108	10.28 114	10.28 112	10.28 110	10.28 113	10.28 112

mvs_tets		10.28 97	10.28 99	10.28 104	10.28 111	10.28 114	10.28 112	10.28 119	10.28 113	10.28 112	10.28 108	10.28 114	10.28 112	10.28 110	10.28 113	10.28 112

SR-MVS-dyc-post		11.55 107	11.55 109	11.55 116	11.55 122	11.55 125	11.55 122	11.55 131	11.55 123	11.55 123	11.55 118	11.55 125	11.55 122	11.55 120	11.55 123	11.55 122

XXY-MVS		15.00 108	15.00 110	15.00 117	15.00 123	15.00 127	15.00 123	15.00 133	15.00 124	15.00 125	15.00 119	15.00 130	15.00 124	15.00 122	15.00 125	15.00 124

test_method		18.29 109	20.89 111	10.50 114	15.00 123	13.00 126	55.00 130	3.00 105	34.00 126	11.50 122	32.50 120	5.00 100	13.50 123	27.00 124	5.00 100	5.00 100

GeoE		19.41 110	22.09 112	11.37 115	17.21 125	11.30 124	50.50 129	4.30 106	33.60 125	11.70 124	44.50 125	7.30 111	18.90 125	22.60 123	7.10 111	3.90 98

BH-w/o		40.00 111	40.00 113	40.00 119	40.00 126	40.00 128	40.00 125	40.00 150	40.00 127	40.00 127	40.00 121	40.00 148	40.00 127	40.00 125	40.00 141	40.00 136

BH-untuned		40.00 111	40.00 113	40.00 119	40.00 126	40.00 128	40.00 125	40.00 150	40.00 127	40.00 127	40.00 121	40.00 148	40.00 127	40.00 125	40.00 141	40.00 136

BH-RMVSNet		40.00 111	40.00 113	40.00 119	40.00 126	40.00 128	40.00 125	40.00 150	40.00 127	40.00 127	40.00 121	40.00 148	40.00 127	40.00 125	40.00 141	40.00 136

TR-MVS		40.00 111	40.00 113	40.00 119	40.00 126	40.00 128	40.00 125	40.00 150	40.00 127	40.00 127	40.00 121	40.00 148	40.00 127	40.00 125	40.00 141	40.00 136

GBi-Net		44.67 115	49.24 117	30.96 118	47.53 130	47.57 132	126.09 131	8.00 117	76.99 131	26.09 126	73.50 127	11.27 124	30.55 126	61.12 129	12.58 124	14.75 123

dp		87.20 116	113.80 120	7.42 103	10.50 121	8.88 111	298.82 139	2.70 104	510.35 155	7.79 109	172.93 130	3.37 99	9.16 110	14.00 121	3.71 99	4.23 99

new_pmnet		88.14 117	98.62 118	56.70 123	98.14 139	56.07 133	246.79 133	15.37 134	148.06 132	50.77 131	143.13 128	23.35 131	62.65 131	93.26 130	68.71 148	51.38 147

N_pmnet		88.14 117	98.62 118	56.70 123	98.14 139	56.07 133	246.79 133	15.37 134	148.06 132	50.77 131	143.13 128	23.35 131	62.65 131	93.26 130	68.71 148	51.38 147

CANet		110.62 119	124.04 121	70.34 127	82.03 135	74.27 139	325.54 140	25.25 136	207.16 135	69.28 137	194.38 131	27.53 133	95.79 141	147.76 134	37.43 130	40.97 140

CANet_DTU		110.62 119	124.04 121	70.34 127	82.03 135	74.27 139	325.54 140	25.25 136	207.16 135	69.28 137	194.38 131	27.53 133	95.79 141	147.76 134	37.43 130	40.97 140

MVS_0304		110.62 119	124.04 121	70.34 127	82.03 135	74.27 139	325.54 140	25.25 136	207.16 135	69.28 137	194.38 131	27.53 133	95.79 141	147.76 134	37.43 130	40.97 140

UGNet		110.62 119	124.04 121	70.34 127	82.03 135	74.27 139	325.54 140	25.25 136	207.16 135	69.28 137	194.38 131	27.53 133	95.79 141	147.76 134	37.43 130	40.97 140
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
ACMMP_NAP		118.81 123	133.18 125	75.70 131	74.28 133	73.29 137	284.50 135	11.35 129	238.58 141	65.86 135	255.35 148	14.55 128	115.69 151	222.18 150	31.94 128	38.12 134

FMVSNet5		124.76 124	140.93 126	76.26 133	107.44 142	100.17 147	329.88 144	27.12 143	259.44 146	74.30 141	204.34 135	30.74 137	92.41 134	196.98 138	38.15 134	36.19 127

test1		124.76 124	140.93 126	76.26 133	107.44 142	100.17 147	329.88 144	27.12 143	259.44 146	74.30 141	204.34 135	30.74 137	92.41 134	196.98 138	38.15 134	36.19 127

FMVSNet3		124.76 124	140.93 126	76.26 133	107.44 142	100.17 147	329.88 144	27.12 143	259.44 146	74.30 141	204.34 135	30.74 137	92.41 134	196.98 138	38.15 134	36.19 127

FMVSNet2		124.76 124	140.93 126	76.26 133	107.44 142	100.17 147	329.88 144	27.12 143	259.44 146	74.30 141	204.34 135	30.74 137	92.41 134	196.98 138	38.15 134	36.19 127

FMVSNet1		124.76 124	140.93 126	76.26 133	107.44 142	100.17 147	329.88 144	27.12 143	259.44 146	74.30 141	204.34 135	30.74 137	92.41 134	196.98 138	38.15 134	36.19 127

MIMVSNet1		124.76 124	140.93 126	76.26 133	107.44 142	100.17 147	329.88 144	27.12 143	259.44 146	74.30 141	204.34 135	30.74 137	92.41 134	196.98 138	38.15 134	36.19 127

MIMVSNet		124.76 124	140.93 126	76.26 133	107.44 142	100.17 147	329.88 144	27.12 143	259.44 146	74.30 141	204.34 135	30.74 137	92.41 134	196.98 138	38.15 134	36.19 127

DSMNet-mixed		131.33 131	143.00 133	96.33 144	99.00 141	81.00 143	201.00 132	45.00 154	335.00 153	99.00 151	251.00 147	38.00 147	110.00 150	120.00 133	99.00 151	98.00 150

PVSNet_Blended_VisFu		136.90 132	155.40 134	81.40 140	111.00 149	96.20 144	407.00 151	25.90 140	251.60 143	85.10 148	240.50 144	37.00 144	99.90 145	199.80 145	40.70 145	48.10 144

PVSNet_BlendedMVS		136.90 132	155.40 134	81.40 140	111.00 149	96.20 144	407.00 151	25.90 140	251.60 143	85.10 148	240.50 144	37.00 144	99.90 145	199.80 145	40.70 145	48.10 144

PVSNet_Blended		136.90 132	155.40 134	81.40 140	111.00 149	96.20 144	407.00 151	25.90 140	251.60 143	85.10 148	240.50 144	37.00 144	99.90 145	199.80 145	40.70 145	48.10 144

test1172		216.26 135	257.16 137	93.57 143	310.10 156	111.10 154	31.10 124	45.10 155	192.73 134	176.39 152	512.31 151	66.33 154	78.35 133	891.20 175	89.18 150	91.27 149

DP-MVS		264.78 136	296.02 138	171.04 145	191.70 152	183.96 155	827.10 162	78.36 156	438.24 154	176.64 153	435.12 150	65.04 153	230.52 155	334.02 151	117.96 152	98.64 151

tmp_tt		371.08 137	412.78 139	246.00 147	231.00 153	197.00 156	1293.00 174	376.00 208	756.00 164	609.00 188	71.00 126	106.00 163	195.00 153	102.00 132	171.00 161	346.00 184

RPSCF		394.81 138	445.63 140	242.35 146	276.55 155	253.63 157	1207.27 172	90.69 161	715.56 162	241.57 155	684.87 159	111.96 164	320.02 156	548.38 158	133.81 153	153.39 153

EG-PatchMatch MVS		437.03 139	493.12 143	268.77 148	264.80 154	260.20 158	1491.80 177	98.00 165	723.20 163	238.80 154	722.40 160	63.10 152	382.00 159	629.00 162	207.00 168	164.10 156

ADS-MVSNet2		443.33 140	482.84 141	324.79 155	434.94 167	387.73 165	1110.57 170	87.69 159	887.02 168	282.92 156	779.29 161	98.57 161	422.76 164	502.40 152	162.19 159	163.87 154

ADS-MVSNet		443.33 140	482.84 141	324.79 155	434.94 167	387.73 165	1110.57 170	87.69 159	887.02 168	282.92 156	779.29 161	98.57 161	422.76 164	502.40 152	162.19 159	163.87 154

MVP-Stereo		473.58 142	533.67 144	293.33 149	376.00 160	318.00 159	1461.00 175	96.00 162	835.00 166	290.00 159	804.00 164	97.00 159	383.00 161	688.00 169	156.00 154	179.00 158
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MS-PatchMatch		473.58 142	533.67 144	293.33 149	376.00 160	318.00 159	1461.00 175	96.00 162	835.00 166	290.00 159	804.00 164	97.00 159	383.00 161	688.00 169	156.00 154	179.00 158

PatchmatchNet		492.52 144	551.22 146	316.40 153	400.20 163	357.90 163	1277.10 173	115.80 170	1034.60 178	315.90 161	874.00 167	155.10 169	402.20 163	629.50 163	158.80 156	189.10 160
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
tpmvs		501.65 145	567.42 147	304.33 152	395.39 162	356.32 162	1512.04 178	216.53 196	994.15 171	350.16 164	804.16 166	119.38 165	380.98 158	555.14 159	159.87 157	175.69 157

DELS-MVS		514.57 146	587.73 149	295.12 151	343.03 157	328.09 161	1540.48 179	116.22 171	988.59 170	325.44 162	906.22 168	119.86 166	365.72 157	788.60 171	161.09 158	191.55 161
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
DP-MVS Recon		516.25 147	581.17 148	321.48 154	361.02 158	429.00 169	1995.36 183	78.48 157	796.20 165	283.32 158	796.02 163	96.78 158	382.98 160	636.72 164	186.66 165	152.46 152

gg-mvs-nofinetune		594.69 148	605.37 150	562.67 175	617.29 183	500.33 173	772.30 158	413.12 216	579.21 156	552.71 182	567.40 152	662.54 233	531.67 168	503.93 154	779.80 214	656.02 199

SR-MVS		610.10 149	610.10 151	610.10 180	610.10 177	610.10 189	610.10 156	610.10 236	610.10 160	610.10 189	610.10 157	610.10 223	610.10 183	610.10 160	610.10 198	610.10 196

CR-MVSNet		612.36 150	617.81 153	596.01 178	611.29 179	600.33 186	790.30 159	513.12 227	579.21 156	552.71 182	567.40 152	662.54 233	531.67 168	503.93 154	779.80 214	656.02 199

IterMVS		615.05 151	691.66 154	385.23 159	516.40 170	454.80 170	1863.80 181	102.10 167	1142.20 180	364.10 165	1093.20 182	135.00 167	480.40 167	826.90 172	181.20 162	220.50 163
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
IB-MVS	872.44 4	616.41 152	700.96 155	362.78 157	426.10 166	409.25 167	1822.69 180	124.42 179	1186.23 181	366.85 166	1079.42 180	190.60 182	451.78 166	930.72 177	181.59 163	227.30 164
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
ACMH+	729.97 2	661.38 153	754.00 156	383.51 158	368.96 159	376.38 164	2483.74 195	82.42 158	1089.25 179	333.39 163	1219.68 183	66.53 155	573.60 180	957.86 178	184.14 164	200.56 162

Gipuma		689.75 154	767.00 157	458.00 167	613.00 182	549.00 184	1943.00 182	187.00 193	1230.00 182	518.00 179	1092.00 181	203.00 188	564.00 173	892.00 176	225.00 177	261.00 171
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
IterMVS-LS		758.94 155	856.56 160	466.10 168	606.60 175	546.80 182	2309.90 185	122.20 178	1402.80 186	463.50 170	1348.20 185	192.60 183	574.60 181	1028.60 188	234.60 179	276.90 173
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
new-patchmatchnet		766.12 156	859.03 161	487.38 171	595.68 172	536.14 175	2346.27 186	142.51 184	1488.08 188	422.43 167	1361.32 187	163.65 172	628.60 185	1003.74 187	207.61 169	297.41 177

SixPastTwentyTwo		773.62 157	869.37 163	486.35 170	603.45 174	547.15 183	2532.14 196	106.92 169	1434.95 187	428.08 168	1360.56 186	165.15 173	628.96 186	984.09 179	209.01 170	282.94 174

mvs_anonymous		774.90 158	882.28 164	452.77 161	636.50 184	537.20 176	2348.80 187	120.30 172	1504.30 189	474.40 171	1371.10 188	186.90 175	564.70 174	1078.90 190	219.30 171	256.40 165

casdiffmvs		774.90 158	882.28 164	452.77 161	636.50 184	537.20 176	2348.80 187	120.30 172	1504.30 189	474.40 171	1371.10 188	186.90 175	564.70 174	1078.90 190	219.30 171	256.40 165

diffmvs		774.90 158	882.28 164	452.77 161	636.50 184	537.20 176	2348.80 187	120.30 172	1504.30 189	474.40 171	1371.10 188	186.90 175	564.70 174	1078.90 190	219.30 171	256.40 165

baseline2		774.90 158	882.28 164	452.77 161	636.50 184	537.20 176	2348.80 187	120.30 172	1504.30 189	474.40 171	1371.10 188	186.90 175	564.70 174	1078.90 190	219.30 171	256.40 165

baseline1		774.90 158	882.28 164	452.77 161	636.50 184	537.20 176	2348.80 187	120.30 172	1504.30 189	474.40 171	1371.10 188	186.90 175	564.70 174	1078.90 190	219.30 171	256.40 165

baseline		774.90 158	882.28 164	452.77 161	636.50 184	537.20 176	2348.80 187	120.30 172	1504.30 189	474.40 171	1371.10 188	186.90 175	564.70 174	1078.90 190	219.30 171	256.40 165

RPMNet		787.26 164	829.13 158	661.63 184	885.90 198	895.90 206	455.98 154	610.10 236	1297.17 183	1002.26 211	1001.67 178	655.98 231	611.10 184	667.90 166	885.21 226	477.90 193

JIA-IIPM		804.30 165	835.64 159	710.26 189	885.90 198	895.90 206	455.98 154	668.73 240	1297.17 183	1002.26 211	1001.67 178	655.98 231	756.98 190	667.90 166	885.21 226	477.90 193

CSCG		826.03 166	963.29 171	414.24 160	421.52 165	426.11 168	2230.35 184	179.52 192	1827.44 200	733.43 199	933.12 170	281.25 195	545.23 172	1800.35 206	262.64 181	271.38 172

PVSNet	1207.94 6	829.56 167	937.18 170	506.69 172	645.55 190	585.72 185	2477.98 194	130.52 180	1578.29 196	509.50 178	1460.01 194	194.90 184	637.19 187	1170.78 197	267.07 183	297.17 176

PatchT		856.34 168	860.99 162	842.38 194	1290.90 213	880.90 204	790.30 159	1267.30 258	579.21 156	923.90 201	567.40 152	662.54 233	990.23 198	887.56 174	779.80 214	656.02 199

K. test v3		877.74 169	980.16 172	570.46 177	1316.85 215	813.15 201	2565.52 197	103.78 168	1509.49 195	548.33 181	1258.90 184	219.93 193	587.82 182	1102.37 196	196.30 166	310.42 179

MVSTER		890.06 170	1005.91 179	542.52 173	736.13 195	653.90 193	2616.56 198	145.22 186	1692.10 199	555.69 185	1554.72 196	266.25 194	660.02 188	1219.66 198	266.84 182	313.64 180

PMVS	863.65 3	957.08 171	1054.11 180	666.00 186	401.00 164	495.00 172	3790.00 203	279.00 198	1607.00 198	521.00 180	1745.00 198	90.00 156	1105.00 209	639.00 165	415.00 194	398.00 191
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
ACMH	993.80 5	967.92 172	1106.11 182	553.33 174	494.00 169	534.00 174	3581.00 201	136.00 181	1585.00 197	478.00 177	1871.00 200	90.00 156	839.00 192	1460.00 200	260.00 180	287.00 175
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PVSNet_0	1661.03 9	968.54 173	1066.82 181	673.70 187	706.94 193	695.69 194	2669.02 199	153.52 188	2108.17 205	605.54 187	1679.14 197	213.26 192	886.75 195	1236.76 199	229.01 178	438.67 192

OurMVSNet-221017-0		999.00 174	999.00 173	999.00 195	999.00 203	999.00 208	999.00 163	999.00 251	999.00 172	999.00 204	999.00 171	999.00 246	999.00 200	999.00 180	999.00 232	999.00 229

EPMVS		999.00 174	999.00 173	999.00 195	999.00 203	999.00 208	999.00 163	999.00 251	999.00 172	999.00 204	999.00 171	999.00 246	999.00 200	999.00 180	999.00 232	999.00 229

uanet_test		1000.00 176	1000.00 175	1000.00 198	1000.00 206	1000.00 211	1000.00 166	1000.00 254	1000.00 174	1000.00 207	1000.00 174	1000.00 249	1000.00 203	1000.00 183	1000.00 235	1000.00 232

sosnet		1000.00 176	1000.00 175	1000.00 198	1000.00 206	1000.00 211	1000.00 166	1000.00 254	1000.00 174	1000.00 207	1000.00 174	1000.00 249	1000.00 203	1000.00 183	1000.00 235	1000.00 232

USDC		1000.00 176	1000.00 175	1000.00 198	1000.00 206	1000.00 211	1000.00 166	1000.00 254	1000.00 174	1000.00 207	1000.00 174	1000.00 249	1000.00 203	1000.00 183	1000.00 235	1000.00 232

TinyColmap		1000.00 176	1000.00 175	1000.00 198	1000.00 206	1000.00 211	1000.00 166	1000.00 254	1000.00 174	1000.00 207	1000.00 174	1000.00 249	1000.00 203	1000.00 183	1000.00 235	1000.00 232

ACMP	1246.57 7	1086.24 180	1235.17 184	639.45 181	596.53 173	639.91 191	3904.24 204	152.04 187	1851.54 201	566.58 186	1997.95 202	138.50 168	938.30 196	1605.46 202	303.70 189	340.14 182
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
Patchmtry		1090.75 181	1198.88 183	766.38 193	1290.90 213	485.90 171	2423.98 193	1267.30 258	1297.17 183	923.90 201	923.40 169	1215.54 254	990.23 198	667.90 166	779.80 214	823.02 212

test_0402		1110.00 182	1260.00 185	660.00 183	900.00 201	780.00 200	3300.00 200	210.00 195	2040.00 204	690.00 194	1950.00 201	300.00 198	810.00 191	1620.00 203	330.00 190	390.00 190

MVS_111021_LR		1136.45 183	1298.72 186	649.64 182	756.17 196	726.26 197	3785.94 202	138.15 183	2190.64 206	629.63 192	2064.39 203	165.45 174	874.83 194	1678.43 205	279.70 184	347.82 185

ACMM	1311.08 8	1165.06 184	1332.72 187	662.07 185	584.90 171	715.99 196	4373.59 208	153.99 189	1880.27 202	709.02 196	2316.97 204	188.63 181	939.89 197	1484.30 201	302.78 188	330.34 181
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MSLP-MVS++		1242.93 185	1411.08 188	738.48 191	712.71 194	712.68 195	4168.17 206	136.50 182	2276.40 207	613.28 191	2368.60 207	161.61 171	1130.38 210	1964.54 209	297.88 186	372.39 187

MG-MVS		1256.50 186	1432.00 189	730.00 190	610.00 176	760.00 198	4720.00 209	169.00 190	1920.00 203	723.00 198	2510.00 210	201.00 186	1050.00 207	1645.00 204	390.00 193	380.00 188

ACMMPR		1296.60 187	1480.82 190	743.96 192	899.25 200	763.47 199	4305.47 207	143.90 185	2530.94 210	683.99 193	2346.34 206	201.65 187	1098.25 208	1920.59 208	295.21 185	370.16 186

TSAR-MVS + GP.		1386.84 188	1622.84 192	678.81 188	952.13 202	840.17 203	5358.21 212	170.75 191	2650.47 211	713.54 197	2394.28 208	209.42 191	855.56 193	1854.36 207	302.42 187	340.71 183

FPMVS		1407.00 189	1495.59 191	1141.23 203	648.01 191	893.85 205	4124.00 205	503.81 226	3219.04 213	742.72 200	2498.84 209	157.98 170	1727.83 216	832.93 173	732.98 213	802.00 208

DeepC-MVS_fast	2190.19 12	1535.59 190	1886.82 194	481.89 169	847.73 197	830.16 202	7943.84 228	189.23 194	2398.83 208	691.73 195	2341.13 205	209.16 190	230.25 154	1999.25 210	360.46 191	385.25 189
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
COLMAP_ROB	2144.59 11	1658.33 191	1869.33 193	1025.33 202	1030.00 210	1023.00 215	5311.00 211	359.00 206	3044.00 212	937.00 203	2892.00 211	332.00 202	1440.00 213	2312.00 212	607.00 197	613.00 198
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
F-COLMAP		1878.17 192	2113.11 195	1173.33 206	1231.00 211	1174.00 216	6297.00 214	392.00 211	3356.00 215	1087.00 213	3082.00 212	361.00 206	1670.00 215	2523.00 214	689.00 204	676.00 203

OpenMVS_ROB	1936.51 10	1959.51 193	2224.88 197	1163.39 205	1253.91 212	1434.22 219	7065.71 218	272.76 197	2472.29 209	1647.54 241	3538.72 215	200.37 185	1496.48 214	2575.17 215	997.45 231	559.48 195

CMPMVS	2623.62 15	1983.08 194	2156.14 196	1463.89 216	1414.80 217	1517.00 221	5239.20 210	867.40 245	3310.30 214	1128.70 215	3489.90 214	366.75 207	2030.20 227	2427.60 213	1160.60 241	844.46 215
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MVS-HIRNet		2125.39 195	2452.68 198	1143.53 204	2938.33 253	1446.92 220	6083.19 213	391.74 210	3801.71 218	1202.10 217	3439.72 213	492.73 215	1304.35 212	3048.25 218	676.32 203	679.32 204

PLC	2858.82 16	2192.92 196	2474.00 199	1349.67 208	1407.00 216	1356.00 218	7164.00 219	475.00 223	3970.00 219	1237.00 220	3765.00 218	451.00 212	1891.00 221	3006.00 217	791.00 219	802.00 208
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
OpenMVS	2352.88 13	2263.08 197	2530.89 200	1459.67 215	1767.00 228	1591.00 224	7932.00 227	399.00 212	3643.00 216	1176.00 216	3569.00 216	297.00 197	1927.00 223	3302.00 219	693.00 208	861.00 216

PCF-MVS	4335.85 20	2272.23 198	2597.03 201	1297.84 207	1701.20 220	1332.37 217	8105.11 229	451.45 219	4031.84 220	1099.10 214	3966.50 219	467.45 213	1734.05 217	2701.68 216	848.94 223	827.11 213
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
CHOSEN 280x420		2340.81 199	2643.03 202	1434.14 209	2025.55 237	1629.36 228	6542.40 215	412.49 213	4219.70 221	1547.02 231	4328.52 221	650.74 228	1798.26 218	3333.17 220	727.72 210	874.79 217

CHOSEN 1792x2688		2340.81 199	2643.03 202	1434.14 209	2025.55 237	1629.36 228	6542.40 215	412.49 213	4219.70 221	1547.02 231	4328.52 221	650.74 228	1798.26 218	3333.17 220	727.72 210	874.79 217

HyFIR lowres test		2340.81 199	2643.03 202	1434.14 209	2025.55 237	1629.36 228	6542.40 215	412.49 213	4219.70 221	1547.02 231	4328.52 221	650.74 228	1798.26 218	3333.17 220	727.72 210	874.79 217

3Dnovator	2482.06 14	2531.17 202	2839.56 205	1606.00 217	1732.00 224	1557.00 223	8375.00 231	483.00 224	4370.00 224	1371.00 226	4200.00 220	350.00 204	2207.00 228	3877.00 226	798.00 220	1054.00 236

tpmrst		2557.50 203	2847.12 206	1688.66 220	1784.08 229	1778.25 238	7445.50 225	342.14 204	4471.54 225	1534.55 230	4382.10 224	530.10 219	2361.21 231	4142.81 230	991.22 230	926.51 222

AdaColmap		2570.77 204	2948.61 207	1437.24 212	1873.64 230	1526.60 222	7819.77 226	373.97 207	4970.45 228	1479.29 228	4648.46 226	525.80 218	1904.97 222	4150.42 231	695.69 209	880.14 220

SD-MVS		2654.53 205	3055.56 210	1451.45 213	1725.60 221	1598.35 225	9203.30 235	315.86 201	5016.02 230	1363.85 223	4894.28 228	387.23 208	2023.43 224	3973.88 227	620.04 200	732.56 205
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
DeepPCF-MVS	3452.42 18	2670.71 206	3021.57 208	1618.12 218	2377.67 243	1751.39 237	8915.70 234	567.44 234	4569.74 226	1236.84 219	4615.63 225	513.23 216	2291.32 229	3515.48 223	882.39 225	811.66 210

LF4IMVS		2699.50 207	3049.67 209	1649.00 219	1755.00 225	1689.00 232	8330.00 230	464.00 221	4997.00 229	1528.00 229	4763.00 227	568.00 221	2296.00 230	4215.00 232	827.00 222	962.00 226

Vis-MVSNet		2877.42 208	3170.00 211	1999.67 229	1673.00 219	2042.00 246	8593.00 232	474.00 222	6452.00 243	1268.00 221	5125.00 231	339.00 203	3004.00 243	4222.00 233	384.00 192	953.00 225
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
SteuartSystems-ACMMP		2891.50 209	3284.78 212	1711.67 221	1954.00 231	1655.00 231	10117.00 244	445.00 218	5102.00 233	1375.00 227	5126.00 232	351.00 205	2638.00 240	4402.00 234	691.00 206	842.00 214
Skip Steuart: Steuart Systems R&D Blog.
3Dnovator+	3414.41 17	3146.67 210	3537.00 213	1975.67 227	2310.00 241	2005.00 245	10100.00 243	626.00 239	5753.00 234	1803.00 244	5179.00 233	487.00 214	2622.00 238	4550.00 235	1025.00 239	1300.00 240

DeepC-MVS	3917.13 19	3155.06 211	3601.83 214	1814.72 225	2515.52 246	1941.53 242	10432.50 245	589.42 235	4789.45 227	1298.65 222	7677.31 247	578.35 222	2589.53 234	3611.78 225	923.52 228	913.10 221
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DPM-MVS		3268.00 212	3762.89 215	1783.33 223	1756.00 226	1806.00 239	12319.00 247	307.00 199	6319.00 241	1557.00 234	5763.00 234	302.00 199	2609.00 236	5061.00 238	482.00 195	935.00 223

OPM-MVS		3268.00 212	3762.89 215	1783.33 223	1756.00 226	1806.00 239	12319.00 247	307.00 199	6319.00 241	1557.00 234	5763.00 234	302.00 199	2609.00 236	5061.00 238	482.00 195	935.00 223

TAPA-MVS	6309.84 21	3374.90 214	3806.99 217	2078.63 231	2535.47 247	2499.25 251	8816.16 233	456.05 220	6255.60 240	1664.52 242	6704.88 239	629.95 226	2768.38 241	6343.93 248	856.35 224	968.25 227
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
TSAR-MVS + MP.		3528.01 215	4065.89 222	1914.35 226	2349.10 242	2141.30 247	12362.70 249	417.60 217	6717.80 247	1759.40 243	6497.50 237	518.18 217	2629.38 239	5164.32 240	806.40 221	972.38 228
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
tpm2		3617.85 216	4007.23 218	2449.73 234	2012.71 233	1698.05 233	7351.19 221	869.29 246	6132.06 236	1588.28 236	8007.42 249	1281.09 255	3888.11 252	7472.04 252	1351.00 243	1763.02 249

tpm cat1		3617.85 216	4007.23 218	2449.73 234	2012.71 233	1698.05 233	7351.19 221	869.29 246	6132.06 236	1588.28 236	8007.42 249	1281.09 255	3888.11 252	7472.04 252	1351.00 243	1763.02 249

CostFormer		3617.85 216	4007.23 218	2449.73 234	2012.71 233	1698.05 233	7351.19 221	869.29 246	6132.06 236	1588.28 236	8007.42 249	1281.09 255	3888.11 252	7472.04 252	1351.00 243	1763.02 249

tpm		3617.85 216	4007.23 218	2449.73 234	2012.71 233	1698.05 233	7351.19 221	869.29 246	6132.06 236	1588.28 236	8007.42 249	1281.09 255	3888.11 252	7472.04 252	1351.00 243	1763.02 249

MVS_111021_HR		3742.80 220	4330.34 223	1980.20 228	2484.31 245	2259.52 248	14973.80 253	515.90 233	6500.13 244	1949.21 246	6146.89 236	535.66 220	2593.66 235	4880.76 237	986.37 229	1087.43 237

MAR-MVS		3973.16 221	4387.92 224	2728.86 240	3345.27 254	3341.39 258	11403.90 246	798.76 243	6555.62 246	2569.29 253	6514.86 238	834.97 240	3237.43 249	5891.08 242	1577.54 248	1607.76 241
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
DVP-MVS		3981.10 222	4731.32 227	1730.42 222	2191.51 240	1949.98 243	16473.90 255	355.33 205	7172.90 252	1622.98 240	7879.79 248	434.33 211	2428.11 233	5762.12 241	689.04 205	813.18 211
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
GST-MVS		4000.00 223	4533.33 225	2400.00 233	2400.00 244	2400.00 249	7200.00 220	2400.00 262	7200.00 253	2400.00 252	7200.00 244	2400.00 259	2400.00 232	7200.00 250	2400.00 255	2400.00 254

SED-MVS		4062.74 224	4671.13 226	2237.56 232	2643.17 248	2465.14 250	13996.40 251	493.26 225	7619.38 254	2107.24 247	7416.93 246	610.24 225	3088.29 248	6075.14 247	1078.39 240	1159.26 238

MSP-MVS		4296.20 225	4911.12 229	2451.45 238	2725.60 249	2598.35 252	16203.30 254	515.86 229	7016.02 248	2363.85 248	6894.28 240	887.23 241	3023.43 244	5973.88 243	1620.04 249	1732.56 245
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
API-MVS		4380.83 226	4906.56 228	2803.67 241	3844.00 255	3116.00 257	13454.00 250	901.00 250	6511.00 245	2794.00 254	7365.00 245	754.00 237	3634.00 250	6622.00 249	1914.00 254	1661.00 244

OMC-MVS		5022.26 227	5748.82 230	2842.58 242	4905.27 257	3101.27 256	14933.60 252	812.24 244	9278.40 255	2959.29 255	8800.17 253	1092.24 253	3806.30 251	7568.54 256	1389.60 247	1620.18 243

CLD-MVS		7338.25 228	8341.00 231	4330.00 243	4902.00 256	4991.00 259	23318.00 257	728.00 242	14437.00 262	4378.00 257	13379.00 258	824.00 239	5708.00 256	11429.00 262	1674.00 253	2291.00 253
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
LS3D		7684.71 229	8776.23 232	4410.16 244	5298.55 258	5631.53 260	34329.90 259	1504.57 260	11554.00 261	3896.41 256	15111.00 259	812.19 238	5985.63 257	3516.20 224	2963.23 256	1613.31 242

ZNCC-MVS		9999.00 230	9999.00 233	9999.00 246	9999.00 261	9999.00 263	9999.00 239	9999.00 266	9999.00 256	9999.00 260	9999.00 254	9999.00 262	9999.00 258	9999.00 257	9999.00 259	9999.00 257

UA-Net		10000.00 231	10000.00 234	10000.00 247	10000.00 262	10000.00 264	10000.00 240	10000.00 267	10000.00 257	10000.00 261	10000.00 255	10000.00 263	10000.00 259	10000.00 258	10000.00 260	10000.00 258

uncertanet		10000.00 231	10000.00 234	10000.00 247	10000.00 262	10000.00 264	10000.00 240	10000.00 267	10000.00 257	10000.00 261	10000.00 255	10000.00 263	10000.00 259	10000.00 258	10000.00 260	10000.00 258

uanet		10000.00 231	10000.00 234	10000.00 247	10000.00 262	10000.00 264	10000.00 240	10000.00 267	10000.00 257	10000.00 261	10000.00 255	10000.00 263	10000.00 259	10000.00 258	10000.00 260	10000.00 258

MVE	10021.00 22	10550.67 234	10002.44 237	12195.33 250	6242.00 259	8768.00 262	30896.00 258	4451.00 263	10331.00 260	6247.00 258	18296.00 260	283.00 196	21484.00 263	7364.00 251	5912.00 258	6334.00 256
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CNLPA		10738.67 235	11772.44 238	7637.33 245	9120.00 260	8206.00 261	22252.00 256	2010.00 261	24984.00 263	7458.00 259	22596.00 261	2940.00 260	10260.00 262	11100.00 261	3492.00 257	4446.00 255

LTVRE_ROB	20565.47 23	23378.08 236	22805.00 239	25097.33 251	15500.00 265	19201.00 267	42712.00 260	6055.00 264	38388.00 264	16926.00 264	38534.00 262	7071.00 261	35653.00 264	29475.00 263	10584.00 263	20438.00 262
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
MSDG		32606.17 237	34443.44 240	27094.33 252	29249.00 266	25246.00 268	51144.00 261	6705.00 265	42886.00 265	22888.00 265	48534.00 263	13263.00 266	37507.00 265	79298.00 264	16024.00 264	18530.00 261

114514_t		99999.00 238	99999.00 241	99999.00 253	99999.00 267	99999.00 269	99999.00 262	99999.00 270	99999.00 266	99999.00 266	99999.00 264	99999.00 267	99999.00 266	99999.00 265	99999.00 265	99999.00 263

PHI-MVS		99999.00 238	99999.00 241	99999.00 253	99999.00 267	99999.00 269	99999.00 262	99999.00 270	99999.00 266	99999.00 266	99999.00 264	99999.00 267	99999.00 266	99999.00 265	99999.00 265	99999.00 263

MP-MVS-pluss		833433.63 240	1111219.60 246	75.70 131	74.28 133	73.29 137	284.50 135	11.35 129	238.58 141	65.86 135	255.35 148	14.55 128	115.69 151	10000000.00 270	31.94 128	38.12 134
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
zzz-MVS		833442.10 241	1111233.77 247	67.09 125	65.59 131	64.81 135	284.50 135	10000000.00 275	219.97 139	59.62 133	229.89 142	12.72 126	103.00 148	203.67 148	27.93 126	33.46 125

MTAPA		833442.10 241	1111233.77 247	67.09 125	65.59 131	64.81 135	284.50 135	10000000.00 275	219.97 139	59.62 133	229.89 142	12.72 126	103.00 148	203.67 148	27.93 126	33.46 125

XVG-OURS-SEG-HR		999999.00 243	999999.00 243	999999.00 255	999999.00 269	999999.00 271	999999.00 264	999999.00 272	999999.00 268	999999.00 268	999999.00 266	999999.00 269	999999.00 268	999999.00 267	999999.00 267	999999.00 265

XVG-OURS		999999.00 243	999999.00 243	999999.00 255	999999.00 269	999999.00 271	999999.00 264	999999.00 272	999999.00 268	999999.00 268	999999.00 266	999999.00 269	999999.00 268	999999.00 267	999999.00 267	999999.00 265

XVG-ACMP-BASELINE		999999.00 243	999999.00 243	999999.00 255	999999.00 269	999999.00 271	999999.00 264	999999.00 272	999999.00 268	999999.00 268	999999.00 266	999999.00 269	999999.00 268	999999.00 267	999999.00 267	999999.00 265

Anonymous20240521		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

cl-mvsnet2		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

miper_ehance_all_eth		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

miper_enhance_ethall		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

cl-mvsnet____		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

cl-mvsnet1		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

eth_miper_zixun_eth		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

testtj		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

ET-MVSNet_ETH3D		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

UniMVSNet_ETH3D		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

miper_lstm_enhance		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

D2MVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

test_yl		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

thisisatest0530		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

Anonymous20240529		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

Anonymous202405211		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

DCV-MVSNet		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

tttt0517		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

our_test_3		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

thisisatest0515		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

ppachtmachnet_test		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

SMA-MVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268
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
DPE-MVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part1		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

thres100view900		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

tfpnnormal		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

tfpn200view9		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

cl_fuxian		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

IterMVS-SCA-FT		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

pmmvs6		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

pmmvs5		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

Anonymous20231211		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

pmmvs-eth3d		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

Anonymous20231206		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

SCA		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

Patchmatch-test		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

Patchmatch-RL test		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

canonicalmvs		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

anonymousdsp		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

FIs		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

FC-MVSNet-test		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

sosnet-low-res		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

AllTest		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

bset_n11_16_dypcd		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

RRT_MVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

HPM-MVS++		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

XVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

pm-mvs1		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

X-MVStestdata		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

APDe-MVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

APD-MVS_3200maxsize		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

pmmvs4		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

test-LLR		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

TESTMET0.1,1		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

test-mter		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

testgi		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

test20.03		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

thres600view7		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

MP-MVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

thres400		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

test123		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

thres200		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

test0.0.03 1		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

pmmvs3		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

EMVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

E-PMN		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

PGM-MVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

MCST-MVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

MVS_Test		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

PMMVS2		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

PM-MVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

HQP_MVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

mPP-MVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

DWT-MVSNet_test		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

HPM-MVS_fast		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

RRT_test8_iter05		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

HPM-MVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
LPG-MVS_test		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

EPNet_dtu		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

NCCC		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

CP-MVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

CPTT-MVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

HQP-MVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

IS-MVSNet		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

PAPM_NR		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

PAPR		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

Vis-MVSNet (Re-imp)		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

PatchMatch-RL		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

TDRefinement		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

EPP-MVSNet		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

PMMVS		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

PAPM		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

ACMMP		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268
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
ANet_high		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

wuyk23d		10000000.00 246	10000000.00 249	10000000.00 258	10000000.00 272	10000000.00 274	10000000.00 267	10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

APD-MVS		1000000000.00 344	1000000000.00 347	1000000000.00 358	1000000000.00 379	1000000000.00 380	1000000000.00 370	1000000000.00 381	1000000000.00 375	1000000000.00 376	1000000000.00 374	1000000000.00 379	1000000000.00 376	1000000000.00 374	1000000000.00 374	1000000000.00 372
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
ZD-MVS					1584.00 218	1821.00 241		378.00 209	3721.00 217	1231.00 218	1833.00 199	321.00 201	1224.00 211	2103.00 211	692.00 207

RE-MVS-def			610.10 151		610.10 177	610.10 189	610.10 156	610.10 236	610.10 160	610.10 189	610.10 157	610.10 223		610.10 160	610.10 198	610.10 196

IU-MVS					2725.60 249	2598.35 252		515.86 229	7016.02 248	2363.85 248				5973.88 243	1620.04 249	1732.56 245

OPU-MVS				2451.45 238	2725.60 249	2598.35 252	9203.30 235				6894.28 240	887.23 241	3023.43 244	5973.88 243	1620.04 249	1732.56 245

test_241102_TWO								515.86 229	7016.02 248	2363.85 248	6894.28 240	887.23 241	3023.43 244	5973.88 243	1620.04 249	1732.56 245

test_241102_ONE					2725.60 249	2598.35 252		515.86 229	7016.02 248	2363.85 248	6894.28 240	887.23 241	3023.43 244

9.14			0.00 1		0.00 1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

save fliter					0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_0728_THIRD									5016.02 230	1363.85 223	4894.28 228	387.23 208	2023.43 224	3973.88 227	620.04 200	732.56 205

test_0728_SECOND				1451.45 213	1725.60 221	1598.35 225	9203.30 235	315.86 201					2023.43 224	3973.88 227	620.04 200	732.56 205

test0726					1725.60 221	1598.35 225	9203.30 235	315.86 201	5016.02 230	1363.85 223	4894.28 228	387.23 208

GSMVS																10000000.00 268

test_part2					10000000.00 272	10000000.00 274				10000000.00 271

sam_mvs1												10000000.00 272				10000000.00 268

sam_mvs												10000000.00 272

ambc				999.00 195	999.00 203	999.00 208	999.00 163	999.00 251		999.00 204	999.00 171	999.00 246	999.00 200	999.00 180	999.00 232	999.00 229

MTGPA								10000000.00 275

test_post1							10000000.00 267				10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270

test_post											10000000.00 269	10000000.00 272	10000000.00 271

patchmatchnet-post											10000000.00 269	10000000.00 272	10000000.00 271

GG-mvs-BLEND				596.01 178	611.29 179	600.33 186	790.30 159	513.12 227		552.71 182	567.40 152	662.54 233	531.67 168	503.93 154	779.80 214	656.02 199

MTMP							10000000.00 267	10000000.00 275

gm-plane-assit					611.29 179	600.33 186			579.21 156		567.40 152		531.67 168	503.93 154

test9_res														0.00 1	0.00 1	0.00 1

TEST9					0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_8					0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

agg_prior2														0.00 1	0.00 1	0.00 1

agg_prior					0.00 1	0.00 1		0.00 1		0.00 1			0.00 1

TestCases				10000000.00 258	10000000.00 272	10000000.00 274		10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

test_prior4						0.00 1	0.00 1

test_prior2							0.00 1		0.00 1	0.00 1	0.00 1	0.00 1		0.00 1	0.00 1

test_prior				0.00 1	0.00 1	0.00 1		0.00 1					0.00 1			0.00 1

旧先验2							0.00 1		0.00 1	0.00 1			0.00 1	0.00 1

新几何2							0.00 1

新几何1				0.00 1	0.00 1	0.00 1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

旧先验1					0.00 1	0.00 1		0.00 1			0.00 1	0.00 1			0.00 1	0.00 1

无先验							0.00 1	0.00 1	0.00 1				0.00 1	0.00 1		0.00 1

原ACMM2							0.00 1

原ACMM1				0.00 1	0.00 1	0.00 1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test222					0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1			0.00 1	0.00 1

testdata2													0.00 1	0.00 1

segment_acmp												0.00 1

testdata				0.00 1	0.00 1	0.00 1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

testdata1							0.00 1		0.00 1

test12				0.00 1	0.00 1	0.00 1		0.00 1		0.00 1		0.00 1	0.00 1		0.00 1	0.00 1

plane_prior7					10000000.00 272	10000000.00 274

plane_prior6					10000000.00 272	10000000.00 274						10000000.00 272

plane_prior5								10000000.00 275					10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

plane_prior4											10000000.00 269

plane_prior3						10000000.00 274			10000000.00 271	10000000.00 271

plane_prior2							10000000.00 267		10000000.00 271

plane_prior1					10000000.00 272

plane_prior						1.00 58	2.00 90		2.00 91						2.00 89

n2								14.20 132

nn								1.42 66

door-mid								1.42 66

lessismore_v0				569.20 176	667.25 192	644.68 192		96.45 164		428.86 169	1514.17 195	204.21 189	756.58 189	1061.60 189	197.79 167	306.34 178

LGP-MVS_train				10000000.00 258	10000000.00 272	10000000.00 274		10000000.00 275	10000000.00 271	10000000.00 271	10000000.00 269	10000000.00 272	10000000.00 271	10000000.00 270	10000000.00 270	10000000.00 268

test11								1.00 59

door								99.00 166

HQP5-MVS						10000000.00 274

HQP-NCC					10000000.00 272		10000000.00 267		10000000.00 271	10000000.00 271

ACMP_Plane					10000000.00 272		10000000.00 267		10000000.00 271	10000000.00 271

BP-MVS														10000000.00 270

HQP4-MVS										10000000.00 271			10000000.00 271			10000000.00 268

HQP3-MVS								10000000.00 275							10000000.00 270

HQP2-MVS												10000000.00 272

NP-MVS					10000000.00 272	10000000.00 274					10000000.00 269

MDTV_nov1_ep13_2view						9.99 112	9.99 110		9.99 111	9.99 110		9.99 112		9.99 108		9.99 111

MDTV_nov1_ep13			9.99 98		9.99 110	9.99 112	9.99 110	9.99 118	9.99 111	9.99 110	9.99 107	9.99 112	9.99 111	9.99 108	9.99 112

ACMMP++_ref															10000000.00 270

ACMMP++															10000000.00 270

Test By Simon												990.00 245

ITE_SJBPF				2014.00 230	1998.00 232	1992.00 244		701.00 241	5989.00 235	1812.00 245	3612.00 217	650.00 227	2852.00 242	4601.00 236	1195.00 242	1198.00 239

DeepMVS_CX				1.00 51	1.00 58	1.00 58		1.00 59	1.00 58	1.00 57	1.00 55	1.00 57	1.00 58	1.00 56	1.00 56	1.00 56

High-resolution multi-view benchmark