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.

test_fmvsmconf0.1_n		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_fmvsmconf0.01_n		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_fmvsmconf_n		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_fmvsmvis_n_1920		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_fmvsm_n_1920		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_cas_vis1_n_1920		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_vis1_n_1920		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_vis1_n		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_fmvs1_n		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

mvsany_test1		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

APD_test1		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_vis1_rt		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_vis3_rt		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_fmvs2		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_fmvs1		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_fmvs3		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

mvsany_test3		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

testf1		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

APD_test2		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_f		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

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

MVS_0304		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

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

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

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_prior					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_prior2							0.00 1		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

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

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

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

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

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

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

h-mvs33		0.30 29	0.30 30	0.30 34	0.30 41	0.30 41	0.30 41	0.30 42	0.30 41	0.30 40	0.30 38	0.30 40	0.30 41	0.30 39	0.30 39	0.30 39

hse-mvs2		0.30 29	0.30 30	0.30 34	0.30 41	0.30 41	0.30 41	0.30 42	0.30 41	0.30 40	0.30 38	0.30 40	0.30 41	0.30 39	0.30 39	0.30 39

CL-MVSNet_self_test		0.30 29	0.30 30	0.30 34	0.30 41	0.30 41	0.30 41	0.30 42	0.30 41	0.30 40	0.30 38	0.30 40	0.30 41	0.30 39	0.30 39	0.30 39

AUN-MVS		0.30 29	0.30 30	0.30 34	0.30 41	0.30 41	0.30 41	0.30 42	0.30 41	0.30 40	0.30 38	0.30 40	0.30 41	0.30 39	0.30 39	0.30 39

LCM-MVSNet		0.37 33	0.36 34	0.37 38	0.37 45	0.37 45	0.37 45	0.32 46	0.37 45	0.37 44	0.37 42	0.37 44	0.37 45	0.37 43	0.37 43	0.37 43

v144192		0.40 34	0.40 35	0.40 39	0.40 46	0.40 46	0.40 46	0.40 48	0.40 46	0.40 45	0.40 43	0.40 45	0.40 46	0.40 44	0.40 44	0.40 44

v1921920		0.40 34	0.40 35	0.40 39	0.40 46	0.40 46	0.40 46	0.40 48	0.40 46	0.40 45	0.40 43	0.40 45	0.40 46	0.40 44	0.40 44	0.40 44

v1192		0.40 34	0.40 35	0.40 39	0.40 46	0.40 46	0.40 46	0.40 48	0.40 46	0.40 45	0.40 43	0.40 45	0.40 46	0.40 44	0.40 44	0.40 44

v1144		0.40 34	0.40 35	0.40 39	0.40 46	0.40 46	0.40 46	0.40 48	0.40 46	0.40 45	0.40 43	0.40 45	0.40 46	0.40 44	0.40 44	0.40 44

v148		0.40 34	0.40 35	0.40 39	0.40 46	0.40 46	0.40 46	0.40 48	0.40 46	0.40 45	0.40 43	0.40 45	0.40 46	0.40 44	0.40 44	0.40 44

v7n		0.40 34	0.40 35	0.40 39	0.40 46	0.40 46	0.40 46	0.40 48	0.40 46	0.40 45	0.40 43	0.40 45	0.40 46	0.40 44	0.40 44	0.40 44

v1240		0.40 34	0.40 35	0.40 39	0.40 46	0.40 46	0.40 46	0.40 48	0.40 46	0.40 45	0.40 43	0.40 45	0.40 46	0.40 44	0.40 44	0.40 44

v8		0.40 34	0.40 35	0.40 39	0.40 46	0.40 46	0.40 46	0.40 48	0.40 46	0.40 45	0.40 43	0.40 45	0.40 46	0.40 44	0.40 44	0.40 44

v10		0.40 34	0.40 35	0.40 39	0.40 46	0.40 46	0.40 46	0.40 48	0.40 46	0.40 45	0.40 43	0.40 45	0.40 46	0.40 44	0.40 44	0.40 44

v2v482		0.40 34	0.40 35	0.40 39	0.40 46	0.40 46	0.40 46	0.40 48	0.40 46	0.40 45	0.40 43	0.40 45	0.40 46	0.40 44	0.40 44	0.40 44

V42		0.40 34	0.40 35	0.40 39	0.40 46	0.40 46	0.40 46	0.40 48	0.40 46	0.40 45	0.40 43	0.40 45	0.40 46	0.40 44	0.40 44	0.40 44

GA-MVS		0.40 34	0.40 35	0.40 39	0.40 46	0.40 46	0.40 46	0.40 48	0.40 46	0.40 45	0.40 43	0.40 45	0.40 46	0.40 44	0.40 44	0.40 44

Fast-Effi-MVS+		0.41 46	0.40 35	0.41 51	0.41 58	0.41 58	0.41 58	0.35 47	0.41 58	0.41 57	0.41 55	0.41 57	0.41 58	0.41 56	0.41 56	0.41 56

Fast-Effi-MVS+-dtu		0.44 47	0.44 48	0.44 52	0.44 59	0.44 59	0.44 59	0.44 60	0.44 59	0.44 58	0.44 56	0.44 58	0.44 59	0.44 57	0.44 57	0.44 57

Effi-MVS+-dtu		0.59 49	0.61 51	0.53 53	0.68 67	0.53 60	0.53 60	0.68 68	0.68 67	0.53 59	0.53 57	0.68 66	0.53 60	0.68 65	0.53 58	0.53 58

KD-MVS_self_test		0.60 50	0.60 50	0.60 54	0.60 61	0.60 61	0.60 62	0.60 62	0.60 61	0.60 60	0.60 58	0.60 60	0.60 61	0.60 58	0.60 60	0.60 59

EIA-MVS		0.62 51	0.62 52	0.62 55	0.62 62	0.62 62	0.62 63	0.62 63	0.62 62	0.62 61	0.62 59	0.62 61	0.62 62	0.62 59	0.62 61	0.62 60

ETV-MVS		0.62 51	0.62 52	0.62 55	0.62 62	0.62 62	0.62 63	0.62 63	0.62 62	0.62 61	0.62 59	0.62 61	0.62 62	0.62 59	0.62 61	0.62 60

CS-MVS		0.62 51	0.62 52	0.62 55	0.62 62	0.62 62	0.62 63	0.62 63	0.62 62	0.62 61	0.62 59	0.62 61	0.62 62	0.62 59	0.62 61	0.62 60

CS-MVS-test		0.62 51	0.62 52	0.62 55	0.62 62	0.62 62	0.62 63	0.62 63	0.62 62	0.62 61	0.62 59	0.62 61	0.62 62	0.62 59	0.62 61	0.62 60

Effi-MVS+		0.58 48	0.56 49	0.62 55	0.53 60	0.62 62	0.53 60	0.53 61	0.53 60	0.62 61	0.62 59	0.53 59	0.62 62	0.62 59	0.53 58	0.62 60

EC-MVSNet		0.62 51	0.62 52	0.62 55	0.62 62	0.62 62	0.62 63	0.62 63	0.62 62	0.62 61	0.62 59	0.62 61	0.62 62	0.62 59	0.62 61	0.62 60

CDS-MVSNet		0.88 56	0.88 57	0.88 61	0.88 68	0.88 68	0.88 68	0.88 69	0.88 68	0.88 67	0.88 65	0.88 67	0.88 68	0.88 66	0.88 66	0.88 66
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		0.88 56	0.88 57	0.88 61	0.88 68	0.88 68	0.88 68	0.88 69	0.88 68	0.88 67	0.88 65	0.88 67	0.88 68	0.88 66	0.88 66	0.88 66

LCM-MVSNet-Re		0.89 58	0.89 59	0.89 63	0.89 70	0.89 70	0.89 70	0.89 71	0.89 70	0.89 69	0.89 67	0.89 69	0.89 70	0.89 68	0.89 68	0.89 68

DeepMVS_CX				1.00 64	1.00 71	1.00 71		1.00 72	1.00 71	1.00 70	1.00 68	1.00 70	1.00 71	1.00 69	1.00 69	1.00 69

MDA-MVSNet-bldmvs		1.20 59	1.20 60	1.20 65	1.20 72	1.20 73	1.20 71	1.20 74	1.20 72	1.20 71	1.20 69	1.20 71	1.20 72	1.20 70	1.20 70	1.20 70

YYNet1		1.20 59	1.20 60	1.20 65	1.20 72	1.20 73	1.20 71	1.20 74	1.20 72	1.20 71	1.20 69	1.20 71	1.20 72	1.20 70	1.20 70	1.20 70

MDA-MVSNet_test_wron		1.20 59	1.20 60	1.20 65	1.20 72	1.20 73	1.20 71	1.20 74	1.20 72	1.20 71	1.20 69	1.20 71	1.20 72	1.20 70	1.20 70	1.20 70

KD-MVS_2432*1600		1.30 62	1.30 63	1.30 68	1.30 75	1.30 76	1.30 74	1.30 77	1.30 75	1.30 74	1.30 72	1.30 74	1.30 75	1.30 73	1.30 73	1.30 73

miper_refine_blended		1.30 62	1.30 63	1.30 68	1.30 75	1.30 76	1.30 74	1.30 77	1.30 75	1.30 74	1.30 72	1.30 74	1.30 75	1.30 73	1.30 73	1.30 73

EI-MVSNet-UG-set		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

EI-MVSNet-Vis-set		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

EI-MVSNet		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

Regformer		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

CVMVSNet		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

EU-MVSNet		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

PS-CasMVS		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

UniMVSNet_NR-MVSNet		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

PEN-MVS		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

TransMVSNet (Re)		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

DTE-MVSNet		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

DU-MVS		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

UniMVSNet (Re)		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

CP-MVSNet		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

WR-MVS_H		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

WR-MVS		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

NR-MVSNet		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

Baseline_NR-MVSNet		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

TranMVSNet+NR-MVSNet		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

MVSFormer		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

jason		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75
jason: jason.
lupinMVS		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

test_djsdf		1.42 64	1.42 65	1.42 70	1.42 77	1.42 78	1.42 76	1.42 79	1.42 77	1.42 76	1.42 74	1.42 76	1.42 77	1.42 75	1.42 75	1.42 75

alignmvs		2.00 87	2.00 88	2.00 93	2.00 101	2.00 101	2.00 99	2.00 104	2.00 100	2.00 99	2.00 97	2.00 99	2.00 100	2.00 98	2.00 98	2.00 98

nrg030		2.00 87	2.00 88	2.00 93	2.00 101	2.00 101	2.00 99	2.00 104	2.00 100	2.00 99	2.00 97	2.00 99	2.00 100	2.00 98	2.00 98	2.00 98

LFMVS		2.00 87	2.00 88	2.00 93	2.00 101	2.00 101	2.00 99	2.00 104	2.00 100	2.00 99	2.00 97	2.00 99	2.00 100	2.00 98	2.00 98	2.00 98

VDD-MVS		2.00 87	2.00 88	2.00 93	2.00 101	2.00 101	2.00 99	2.00 104	2.00 100	2.00 99	2.00 97	2.00 99	2.00 100	2.00 98	2.00 98	2.00 98

VDDNet		2.00 87	2.00 88	2.00 93	2.00 101	2.00 101	2.00 99	2.00 104	2.00 100	2.00 99	2.00 97	2.00 99	2.00 100	2.00 98	2.00 98	2.00 98

VPNet		2.00 87	2.00 88	2.00 93	2.00 101	2.00 101	2.00 99	2.00 104	2.00 100	2.00 99	2.00 97	2.00 99	2.00 100	2.00 98	2.00 98	2.00 98

VNet		2.00 87	2.00 88	2.00 93	2.00 101	2.00 101	2.00 99	2.00 104	2.00 100	2.00 99	2.00 97	2.00 99	2.00 100	2.00 98	2.00 98	2.00 98

VPA-MVSNet		2.00 87	2.00 88	2.00 93	2.00 101	2.00 101	2.00 99	2.00 104	2.00 100	2.00 99	2.00 97	2.00 99	2.00 100	2.00 98	2.00 98	2.00 98

cascas		2.00 87	2.00 88	2.00 93	2.00 101	2.00 101	2.00 99	2.00 104	2.00 100	2.00 99	2.00 97	2.00 99	2.00 100	2.00 98	2.00 98	2.00 98

UnsupCasMVSNet_eth		5.90 96	5.90 97	5.90 102	5.90 110	5.90 110	5.90 109	5.90 116	5.90 110	5.90 108	5.90 106	5.90 110	5.90 109	5.90 107	5.90 110	5.90 110

UnsupCasMVSNet_bld		5.90 96	5.90 97	5.90 102	5.90 110	5.90 110	5.90 109	5.90 116	5.90 110	5.90 108	5.90 106	5.90 110	5.90 109	5.90 107	5.90 110	5.90 110

WTY-MVS		5.90 96	5.90 97	5.90 102	5.90 110	5.90 110	5.90 109	5.90 116	5.90 110	5.90 108	5.90 106	5.90 110	5.90 109	5.90 107	5.90 110	5.90 110

HY-MVS	5.90 1	5.90 96	5.90 97	5.90 102	5.90 110	5.90 110	5.90 109	5.90 116	5.90 110	5.90 108	5.90 106	5.90 110	5.90 109	5.90 107	5.90 110	5.90 110

sss		5.90 96	5.90 97	5.90 102	5.90 110	5.90 110	5.90 109	5.90 116	5.90 110	5.90 108	5.90 106	5.90 110	5.90 109	5.90 107	5.90 110	5.90 110

Test_1112_low_res		5.90 96	5.90 97	5.90 102	5.90 110	5.90 110	5.90 109	5.90 116	5.90 110	5.90 108	5.90 106	5.90 110	5.90 109	5.90 107	5.90 110	5.90 110

1112_ss		5.90 96	5.90 97	5.90 102	5.90 110	5.90 110	5.90 109	5.90 116	5.90 110	5.90 108	5.90 106	5.90 110	5.90 109	5.90 107	5.90 110	5.90 110

ab-mvs-re		5.90 96	5.90 97	5.90 102	5.90 110	5.90 110	5.90 109	5.90 116	5.90 110	5.90 108	5.90 106	5.90 110	5.90 109	5.90 107	5.90 110	5.90 110

ab-mvs		5.90 96	5.90 97	5.90 102	5.90 110	5.90 110	5.90 109	5.90 116	5.90 110	5.90 108	5.90 106	5.90 110	5.90 109	5.90 107	5.90 110	5.90 110

CDPH-MVS		6.66 105	6.66 106	6.66 111	6.66 119	6.66 119	6.66 118	6.66 125	6.66 119	6.66 117	6.66 115	6.66 119	6.66 118	6.66 116	6.66 119	6.66 119

dp		87.20 125	113.80 129	7.42 112	10.50 131	8.88 120	298.82 146	2.70 113	510.35 163	7.79 118	172.93 139	3.37 108	9.16 119	14.00 130	3.71 108	4.23 108

MDTV_nov1_ep13_2view						9.99 121	9.99 119		9.99 120	9.99 119		9.99 121		9.99 117		9.99 120

MDTV_nov1_ep13			9.99 107		9.99 120	9.99 121	9.99 119	9.99 127	9.99 120	9.99 119	9.99 116	9.99 121	9.99 120	9.99 117	9.99 121

xiu_mvs_v1_base_debu		10.28 106	10.28 108	10.28 113	10.28 121	10.28 123	10.28 121	10.28 128	10.28 122	10.28 121	10.28 117	10.28 123	10.28 121	10.28 119	10.28 122	10.28 121

xiu_mvs_v2_base		10.28 106	10.28 108	10.28 113	10.28 121	10.28 123	10.28 121	10.28 128	10.28 122	10.28 121	10.28 117	10.28 123	10.28 121	10.28 119	10.28 122	10.28 121

xiu_mvs_v1_base		10.28 106	10.28 108	10.28 113	10.28 121	10.28 123	10.28 121	10.28 128	10.28 122	10.28 121	10.28 117	10.28 123	10.28 121	10.28 119	10.28 122	10.28 121

xiu_mvs_v1_base_debi		10.28 106	10.28 108	10.28 113	10.28 121	10.28 123	10.28 121	10.28 128	10.28 122	10.28 121	10.28 117	10.28 123	10.28 121	10.28 119	10.28 122	10.28 121

cdsmvs_eth3d_5k		10.28 106	10.28 108	10.28 113	10.28 121	10.28 123	10.28 121	10.28 128	10.28 122	10.28 121	10.28 117	10.28 123	10.28 121	10.28 119	10.28 122	10.28 121

pcd_1.5k_mvsjas		10.28 106	10.28 108	10.28 113	10.28 121	10.28 123	10.28 121	10.28 128	10.28 122	10.28 121	10.28 117	10.28 123	10.28 121	10.28 119	10.28 122	10.28 121

PS-MVSNAJss		10.28 106	10.28 108	10.28 113	10.28 121	10.28 123	10.28 121	10.28 128	10.28 122	10.28 121	10.28 117	10.28 123	10.28 121	10.28 119	10.28 122	10.28 121

PS-MVSNAJ		10.28 106	10.28 108	10.28 113	10.28 121	10.28 123	10.28 121	10.28 128	10.28 122	10.28 121	10.28 117	10.28 123	10.28 121	10.28 119	10.28 122	10.28 121

jajsoiax		10.28 106	10.28 108	10.28 113	10.28 121	10.28 123	10.28 121	10.28 128	10.28 122	10.28 121	10.28 117	10.28 123	10.28 121	10.28 119	10.28 122	10.28 121

mvs_tets		10.28 106	10.28 108	10.28 113	10.28 121	10.28 123	10.28 121	10.28 128	10.28 122	10.28 121	10.28 117	10.28 123	10.28 121	10.28 119	10.28 122	10.28 121

test_method		18.29 118	20.89 120	10.50 123	15.00 133	13.00 135	55.00 138	3.00 114	34.00 135	11.50 131	32.50 129	5.00 109	13.50 132	27.00 133	5.00 109	5.00 109

SR-MVS-dyc-post		11.55 116	11.55 118	11.55 125	11.55 132	11.55 134	11.55 131	11.55 140	11.55 132	11.55 132	11.55 127	11.55 134	11.55 131	11.55 129	11.55 132	11.55 131

GeoE		19.41 119	22.09 121	11.37 124	17.21 135	11.30 133	50.50 137	4.30 115	33.60 134	11.70 133	44.50 134	7.30 120	18.90 134	22.60 132	7.10 120	3.90 107

XXY-MVS		15.00 117	15.00 119	15.00 126	15.00 133	15.00 136	15.00 132	15.00 142	15.00 133	15.00 134	15.00 128	15.00 138	15.00 133	15.00 131	15.00 134	15.00 133

GBi-Net		44.67 124	49.24 126	30.96 127	47.53 140	47.57 141	126.09 139	8.00 126	76.99 140	26.09 135	73.50 136	11.27 133	30.55 135	61.12 138	12.58 133	14.75 132

BH-w/o		40.00 120	40.00 122	40.00 128	40.00 136	40.00 137	40.00 133	40.00 159	40.00 136	40.00 136	40.00 130	40.00 155	40.00 136	40.00 134	40.00 148	40.00 144

BH-untuned		40.00 120	40.00 122	40.00 128	40.00 136	40.00 137	40.00 133	40.00 159	40.00 136	40.00 136	40.00 130	40.00 155	40.00 136	40.00 134	40.00 148	40.00 144

BH-RMVSNet		40.00 120	40.00 122	40.00 128	40.00 136	40.00 137	40.00 133	40.00 159	40.00 136	40.00 136	40.00 130	40.00 155	40.00 136	40.00 134	40.00 148	40.00 144

TR-MVS		40.00 120	40.00 122	40.00 128	40.00 136	40.00 137	40.00 133	40.00 159	40.00 136	40.00 136	40.00 130	40.00 155	40.00 136	40.00 134	40.00 148	40.00 144

new_pmnet		88.14 126	98.62 127	56.70 132	98.14 147	56.07 142	246.79 141	15.37 143	148.06 141	50.77 140	143.13 137	23.35 139	62.65 140	93.26 139	68.71 156	51.38 154

N_pmnet		88.14 126	98.62 127	56.70 132	98.14 147	56.07 142	246.79 141	15.37 143	148.06 141	50.77 140	143.13 137	23.35 139	62.65 140	93.26 139	68.71 156	51.38 154

MTAPA		833442.10 261	1111233.77 267	67.09 134	65.59 141	64.81 144	284.50 143	10000000.00 299	219.97 146	59.62 142	229.89 150	12.72 135	103.00 155	203.67 156	27.93 135	33.46 134

MP-MVS-pluss		833433.63 260	1111219.60 266	75.70 138	74.28 142	73.29 145	284.50 143	11.35 138	238.58 147	65.86 143	255.35 155	14.55 136	115.69 157	10000000.00 293	31.94 136	38.12 142
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
ACMMP_NAP		118.81 131	133.18 133	75.70 138	74.28 142	73.29 145	284.50 143	11.35 138	238.58 147	65.86 143	255.35 155	14.55 136	115.69 157	222.18 157	31.94 136	38.12 142

CANet		110.62 128	124.04 130	70.34 135	82.03 144	74.27 147	325.54 147	25.25 145	207.16 143	69.28 145	194.38 140	27.53 141	95.79 149	147.76 143	37.43 138	40.97 148

CANet_DTU		110.62 128	124.04 130	70.34 135	82.03 144	74.27 147	325.54 147	25.25 145	207.16 143	69.28 145	194.38 140	27.53 141	95.79 149	147.76 143	37.43 138	40.97 148

UGNet		110.62 128	124.04 130	70.34 135	82.03 144	74.27 147	325.54 147	25.25 145	207.16 143	69.28 145	194.38 140	27.53 141	95.79 149	147.76 143	37.43 138	40.97 148
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
FMVSNet5		124.76 132	140.93 134	76.26 140	107.44 150	100.17 154	329.88 150	27.12 151	259.44 152	74.30 148	204.34 143	30.74 144	92.41 142	196.98 146	38.15 141	36.19 135

test1		124.76 132	140.93 134	76.26 140	107.44 150	100.17 154	329.88 150	27.12 151	259.44 152	74.30 148	204.34 143	30.74 144	92.41 142	196.98 146	38.15 141	36.19 135

FMVSNet3		124.76 132	140.93 134	76.26 140	107.44 150	100.17 154	329.88 150	27.12 151	259.44 152	74.30 148	204.34 143	30.74 144	92.41 142	196.98 146	38.15 141	36.19 135

FMVSNet2		124.76 132	140.93 134	76.26 140	107.44 150	100.17 154	329.88 150	27.12 151	259.44 152	74.30 148	204.34 143	30.74 144	92.41 142	196.98 146	38.15 141	36.19 135

FMVSNet1		124.76 132	140.93 134	76.26 140	107.44 150	100.17 154	329.88 150	27.12 151	259.44 152	74.30 148	204.34 143	30.74 144	92.41 142	196.98 146	38.15 141	36.19 135

MIMVSNet1		124.76 132	140.93 134	76.26 140	107.44 150	100.17 154	329.88 150	27.12 151	259.44 152	74.30 148	204.34 143	30.74 144	92.41 142	196.98 146	38.15 141	36.19 135

MIMVSNet		124.76 132	140.93 134	76.26 140	107.44 150	100.17 154	329.88 150	27.12 151	259.44 152	74.30 148	204.34 143	30.74 144	92.41 142	196.98 146	38.15 141	36.19 135

PVSNet_Blended_VisFu		136.90 140	155.40 142	81.40 147	111.00 157	96.20 151	407.00 157	25.90 148	251.60 149	85.10 155	240.50 151	37.00 151	99.90 152	199.80 153	40.70 152	48.10 151

PVSNet_BlendedMVS		136.90 140	155.40 142	81.40 147	111.00 157	96.20 151	407.00 157	25.90 148	251.60 149	85.10 155	240.50 151	37.00 151	99.90 152	199.80 153	40.70 152	48.10 151

PVSNet_Blended		136.90 140	155.40 142	81.40 147	111.00 157	96.20 151	407.00 157	25.90 148	251.60 149	85.10 155	240.50 151	37.00 151	99.90 152	199.80 153	40.70 152	48.10 151

DSMNet-mixed		131.33 139	143.00 141	96.33 150	99.00 149	81.00 150	201.00 140	45.00 164	335.00 159	99.00 158	251.00 154	38.00 154	110.00 156	120.00 142	99.00 161	98.00 158

FE-MVS		207.10 143	234.26 145	125.61 151	180.34 160	153.23 161	635.64 164	30.05 158	378.38 160	127.68 159	377.08 157	48.95 159	154.43 159	266.67 158	63.56 155	69.18 156

FA-MVS(test-final)		261.15 144	293.29 146	164.72 152	236.23 163	199.99 165	800.05 169	42.35 163	475.87 162	155.47 160	470.67 159	58.49 160	205.24 161	319.44 159	81.03 158	88.93 157

DP-MVS		264.78 145	296.02 147	171.04 153	191.70 161	183.96 162	827.10 170	78.36 167	438.24 161	176.64 161	435.12 158	65.04 162	230.52 163	334.02 160	117.96 165	98.64 159

SSC-MVS		320.23 147	364.09 149	188.66 154	260.78 165	193.84 163	975.93 174	73.11 166	596.72 168	185.29 162	589.02 165	74.47 164	246.01 164	427.42 164	94.06 160	126.12 161

WB-MVS		316.44 146	357.41 148	193.51 155	257.06 164	213.32 167	914.45 171	49.03 165	600.77 169	186.42 163	634.00 168	75.03 165	251.35 165	411.39 162	88.55 159	115.87 160

testing3		418.10 152	469.06 154	265.23 160	335.69 170	290.63 172	1240.88 185	93.72 173	717.99 173	215.31 164	811.97 179	232.41 207	358.74 167	458.67 165	114.88 162	146.32 164

EG-PatchMatch MVS		437.03 153	493.12 157	268.77 161	264.80 166	260.20 171	1491.80 190	98.00 177	723.20 174	238.80 165	722.40 170	63.10 161	382.00 172	629.00 177	207.00 181	164.10 169

RPSCF		394.81 151	445.63 153	242.35 157	276.55 167	253.63 169	1207.27 184	90.69 172	715.56 172	241.57 166	684.87 169	111.96 175	320.02 166	548.38 173	133.81 166	153.39 166

Syy-MVS		370.76 148	415.60 151	236.25 156	310.54 168	210.76 166	965.13 172	98.58 178	746.06 175	266.26 167	788.85 173	91.37 168	364.76 168	357.17 161	116.42 163	133.22 162

myMVS_eth3d		390.90 150	437.44 152	251.28 159	310.54 168	255.86 170	965.13 172	98.58 178	746.06 175	266.26 167	788.85 173	154.95 180	364.76 168	490.19 166	116.42 163	133.22 162

ADS-MVSNet2		443.33 154	482.84 155	324.79 168	434.94 181	387.73 179	1110.57 182	87.69 170	887.02 181	282.92 169	779.29 171	98.57 172	422.76 177	502.40 167	162.19 172	163.87 167

ADS-MVSNet		443.33 154	482.84 155	324.79 168	434.94 181	387.73 179	1110.57 182	87.69 170	887.02 181	282.92 169	779.29 171	98.57 172	422.76 177	502.40 167	162.19 172	163.87 167

DP-MVS Recon		516.25 161	581.17 162	321.48 167	361.02 172	429.00 183	1995.36 196	78.48 168	796.20 178	283.32 171	796.02 175	96.78 169	382.98 173	636.72 179	186.66 178	152.46 165

MVP-Stereo		473.58 156	533.67 158	293.33 162	376.00 174	318.00 173	1461.00 188	96.00 174	835.00 179	290.00 172	804.00 176	97.00 170	383.00 174	688.00 184	156.00 167	179.00 171
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MS-PatchMatch		473.58 156	533.67 158	293.33 162	376.00 174	318.00 173	1461.00 188	96.00 174	835.00 179	290.00 172	804.00 176	97.00 170	383.00 174	688.00 184	156.00 167	179.00 171

PatchmatchNet		492.52 158	551.22 160	316.40 166	400.20 177	357.90 177	1277.10 186	115.80 184	1034.60 191	315.90 174	874.00 180	155.10 181	402.20 176	629.50 178	158.80 169	189.10 173
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
DELS-MVS		514.57 160	587.73 163	295.12 164	343.03 171	328.09 175	1540.48 192	116.22 185	988.59 183	325.44 175	906.22 181	119.86 177	365.72 170	788.60 186	161.09 171	191.55 174
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
ACMH+	729.97 2	661.38 167	754.00 170	383.51 171	368.96 173	376.38 178	2483.74 209	82.42 169	1089.25 192	333.39 176	1219.68 196	66.53 163	573.60 194	957.86 192	184.14 177	200.56 175

tpmvs		501.65 159	567.42 161	304.33 165	395.39 176	356.32 176	1512.04 191	216.53 211	994.15 184	350.16 177	804.16 178	119.38 176	380.98 171	555.14 174	159.87 170	175.69 170

IterMVS		615.05 165	691.66 168	385.23 172	516.40 184	454.80 184	1863.80 194	102.10 181	1142.20 193	364.10 178	1093.20 195	135.00 178	480.40 180	826.90 187	181.20 175	220.50 176
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
IB-MVS	872.44 4	616.41 166	700.96 169	362.78 170	426.10 180	409.25 181	1822.69 193	124.42 194	1186.23 194	366.85 179	1079.42 193	190.60 195	451.78 179	930.72 191	181.59 176	227.30 177
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
new-patchmatchnet		766.12 170	859.03 175	487.38 185	595.68 186	536.14 189	2346.27 199	142.51 199	1488.08 201	422.43 180	1361.32 200	163.65 184	628.60 199	1003.74 201	207.61 182	297.41 191

SixPastTwentyTwo		773.62 171	869.37 177	486.35 184	603.45 188	547.15 198	2532.14 210	106.92 183	1434.95 200	428.08 181	1360.56 199	165.15 185	628.96 200	984.09 193	209.01 183	282.94 188

lessismore_v0				569.20 190	667.25 207	644.68 207		96.45 176		428.86 182	1514.17 209	204.21 202	756.58 203	1061.60 203	197.79 180	306.34 192

IterMVS-LS		758.94 169	856.56 174	466.10 182	606.60 189	546.80 197	2309.90 198	122.20 193	1402.80 199	463.50 183	1348.20 198	192.60 196	574.60 195	1028.60 202	234.60 193	276.90 187
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
mvs_anonymous		774.90 172	882.28 178	452.77 174	636.50 198	537.20 190	2348.80 200	120.30 186	1504.30 202	474.40 184	1371.10 201	186.90 187	564.70 187	1078.90 204	219.30 184	256.40 178

casdiffmvs		774.90 172	882.28 178	452.77 174	636.50 198	537.20 190	2348.80 200	120.30 186	1504.30 202	474.40 184	1371.10 201	186.90 187	564.70 187	1078.90 204	219.30 184	256.40 178
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
diffmvs		774.90 172	882.28 178	452.77 174	636.50 198	537.20 190	2348.80 200	120.30 186	1504.30 202	474.40 184	1371.10 201	186.90 187	564.70 187	1078.90 204	219.30 184	256.40 178
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
baseline2		774.90 172	882.28 178	452.77 174	636.50 198	537.20 190	2348.80 200	120.30 186	1504.30 202	474.40 184	1371.10 201	186.90 187	564.70 187	1078.90 204	219.30 184	256.40 178

baseline1		774.90 172	882.28 178	452.77 174	636.50 198	537.20 190	2348.80 200	120.30 186	1504.30 202	474.40 184	1371.10 201	186.90 187	564.70 187	1078.90 204	219.30 184	256.40 178

casdiffmvs_mvg		774.90 172	882.28 178	452.77 174	636.50 198	537.20 190	2348.80 200	120.30 186	1504.30 202	474.40 184	1371.10 201	186.90 187	564.70 187	1078.90 204	219.30 184	256.40 178
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
baseline		774.90 172	882.28 178	452.77 174	636.50 198	537.20 190	2348.80 200	120.30 186	1504.30 202	474.40 184	1371.10 201	186.90 187	564.70 187	1078.90 204	219.30 184	256.40 178

ACMH	993.80 5	967.92 187	1106.11 197	553.33 188	494.00 183	534.00 188	3581.00 215	136.00 196	1585.00 211	478.00 191	1871.00 214	90.00 166	839.00 206	1460.00 215	260.00 194	287.00 189
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PVSNet	1207.94 6	829.56 182	937.18 185	506.69 186	645.55 205	585.72 200	2477.98 208	130.52 195	1578.29 210	509.50 192	1460.01 208	194.90 197	637.19 201	1170.78 212	267.07 197	297.17 190

Gipuma		689.75 168	767.00 171	458.00 181	613.00 196	549.00 199	1943.00 195	187.00 208	1230.00 195	518.00 193	1092.00 194	203.00 201	564.00 186	892.00 190	225.00 191	261.00 185
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMVS	863.65 3	957.08 186	1054.11 195	666.00 200	401.00 178	495.00 186	3790.00 217	279.00 213	1607.00 212	521.00 194	1745.00 212	90.00 166	1105.00 223	639.00 180	415.00 208	398.00 205
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
K. test v3		877.74 184	980.16 187	570.46 191	1316.85 230	813.15 216	2565.52 211	103.78 182	1509.49 209	548.33 195	1258.90 197	219.93 206	587.82 196	1102.37 211	196.30 179	310.42 193

GG-mvs-BLEND				596.01 192	611.29 193	600.33 201	790.30 166	513.12 247		552.71 196	567.40 160	662.54 251	531.67 181	503.93 169	779.80 229	656.02 213

gg-mvs-nofinetune		594.69 162	605.37 164	562.67 189	617.29 197	500.33 187	772.30 165	413.12 232	579.21 164	552.71 196	567.40 160	662.54 251	531.67 181	503.93 169	779.80 229	656.02 213

CR-MVSNet		612.36 164	617.81 167	596.01 192	611.29 193	600.33 201	790.30 166	513.12 247	579.21 164	552.71 196	567.40 160	662.54 251	531.67 181	503.93 169	779.80 229	656.02 213

MVSTER		890.06 185	1005.91 194	542.52 187	736.13 210	653.90 208	2616.56 212	145.22 201	1692.10 213	555.69 199	1554.72 210	266.25 208	660.02 202	1219.66 213	266.84 196	313.64 194

ACMP	1246.57 7	1086.24 195	1235.17 199	639.45 195	596.53 187	639.91 206	3904.24 218	152.04 202	1851.54 215	566.58 200	1997.95 216	138.50 179	938.30 210	1605.46 217	303.70 203	340.14 196
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PVSNet_0	1661.03 9	968.54 188	1066.82 196	673.70 201	706.94 208	695.69 209	2669.02 213	153.52 203	2108.17 219	605.54 201	1679.14 211	213.26 205	886.75 209	1236.76 214	229.01 192	438.67 206

tmp_tt		371.08 149	412.78 150	246.00 158	231.00 162	197.00 164	1293.00 187	376.00 224	756.00 177	609.00 202	71.00 135	106.00 174	195.00 160	102.00 141	171.00 174	346.00 198

RE-MVS-def			610.10 165		610.10 191	610.10 204	610.10 162	610.10 256	610.10 170	610.10 203	610.10 166	610.10 239		610.10 175	610.10 212	610.10 210

SR-MVS		610.10 163	610.10 165	610.10 194	610.10 191	610.10 204	610.10 162	610.10 256	610.10 170	610.10 203	610.10 166	610.10 239	610.10 197	610.10 175	610.10 212	610.10 210

MSLP-MVS++		1242.93 200	1411.08 203	738.48 205	712.71 209	712.68 210	4168.17 220	136.50 197	2276.40 221	613.28 205	2368.60 221	161.61 183	1130.38 224	1964.54 224	297.88 200	372.39 201

MVS_111021_LR		1136.45 198	1298.72 201	649.64 196	756.17 211	726.26 212	3785.94 216	138.15 198	2190.64 220	629.63 206	2064.39 217	165.45 186	874.83 208	1678.43 220	279.70 198	347.82 199

ACMMPR		1296.60 202	1480.82 205	743.96 206	899.25 215	763.47 214	4305.47 221	143.90 200	2530.94 224	683.99 207	2346.34 220	201.65 200	1098.25 222	1920.59 223	295.21 199	370.16 200

test_0402		1110.00 197	1260.00 200	660.00 197	900.00 216	780.00 215	3300.00 214	210.00 210	2040.00 218	690.00 208	1950.00 215	300.00 212	810.00 205	1620.00 218	330.00 204	390.00 204

DeepC-MVS_fast	2190.19 12	1535.59 205	1886.82 209	481.89 183	847.73 212	830.16 217	7943.84 242	189.23 209	2398.83 222	691.73 209	2341.13 219	209.16 203	230.25 162	1999.25 225	360.46 205	385.25 203
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ACMM	1311.08 8	1165.06 199	1332.72 202	662.07 199	584.90 185	715.99 211	4373.59 222	153.99 204	1880.27 216	709.02 210	2316.97 218	188.63 194	939.89 211	1484.30 216	302.78 202	330.34 195
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
TSAR-MVS + GP.		1386.84 203	1622.84 207	678.81 202	952.13 217	840.17 218	5358.21 226	170.75 206	2650.47 225	713.54 211	2394.28 222	209.42 204	855.56 207	1854.36 222	302.42 201	340.71 197

MG-MVS		1256.50 201	1432.00 204	730.00 204	610.00 190	760.00 213	4720.00 223	169.00 205	1920.00 217	723.00 212	2510.00 224	201.00 199	1050.00 221	1645.00 219	390.00 207	380.00 202

CSCG		826.03 181	963.29 186	414.24 173	421.52 179	426.11 182	2230.35 197	179.52 207	1827.44 214	733.43 213	933.12 183	281.25 209	545.23 185	1800.35 221	262.64 195	271.38 186

FPMVS		1407.00 204	1495.59 206	1141.23 217	648.01 206	893.85 220	4124.00 219	503.81 246	3219.04 227	742.72 214	2498.84 223	157.98 182	1727.83 230	832.93 188	732.98 228	802.00 222

Patchmtry		1090.75 196	1198.88 198	766.38 207	1290.90 228	485.90 185	2423.98 207	1267.30 279	1297.17 196	923.90 215	923.40 182	1215.54 272	990.23 212	667.90 181	779.80 229	823.02 227

PatchT		856.34 183	860.99 176	842.38 208	1290.90 228	880.90 219	790.30 166	1267.30 279	579.21 164	923.90 215	567.40 160	662.54 251	990.23 212	887.56 189	779.80 229	656.02 213

COLMAP_ROB	2144.59 11	1658.33 206	1869.33 208	1025.33 216	1030.00 225	1023.00 230	5311.00 225	359.00 222	3044.00 226	937.00 217	2892.00 225	332.00 216	1440.00 227	2312.00 227	607.00 211	613.00 212
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ambc				999.00 209	999.00 218	999.00 223	999.00 175	999.00 272		999.00 218	999.00 184	999.00 264	999.00 214	999.00 194	999.00 248	999.00 245

OurMVSNet-221017-0		999.00 189	999.00 188	999.00 209	999.00 218	999.00 223	999.00 175	999.00 272	999.00 185	999.00 218	999.00 184	999.00 264	999.00 214	999.00 194	999.00 248	999.00 245

EPMVS		999.00 189	999.00 188	999.00 209	999.00 218	999.00 223	999.00 175	999.00 272	999.00 185	999.00 218	999.00 184	999.00 264	999.00 214	999.00 194	999.00 248	999.00 245

uanet_test		1000.00 191	1000.00 190	1000.00 212	1000.00 221	1000.00 226	1000.00 178	1000.00 275	1000.00 187	1000.00 221	1000.00 187	1000.00 267	1000.00 217	1000.00 197	1000.00 251	1000.00 248

sosnet		1000.00 191	1000.00 190	1000.00 212	1000.00 221	1000.00 226	1000.00 178	1000.00 275	1000.00 187	1000.00 221	1000.00 187	1000.00 267	1000.00 217	1000.00 197	1000.00 251	1000.00 248

USDC		1000.00 191	1000.00 190	1000.00 212	1000.00 221	1000.00 226	1000.00 178	1000.00 275	1000.00 187	1000.00 221	1000.00 187	1000.00 267	1000.00 217	1000.00 197	1000.00 251	1000.00 248

TinyColmap		1000.00 191	1000.00 190	1000.00 212	1000.00 221	1000.00 226	1000.00 178	1000.00 275	1000.00 187	1000.00 221	1000.00 187	1000.00 267	1000.00 217	1000.00 197	1000.00 251	1000.00 248

JIA-IIPM		804.30 180	835.64 173	710.26 203	885.90 213	895.90 221	455.98 160	668.73 261	1297.17 196	1002.26 225	1001.67 191	655.98 249	756.98 204	667.90 181	885.21 241	477.90 207

RPMNet		787.26 179	829.13 172	661.63 198	885.90 213	895.90 221	455.98 160	610.10 256	1297.17 196	1002.26 225	1001.67 191	655.98 249	611.10 198	667.90 181	885.21 241	477.90 207

F-COLMAP		1878.17 207	2113.11 210	1173.33 220	1231.00 226	1174.00 231	6297.00 228	392.00 227	3356.00 229	1087.00 227	3082.00 226	361.00 220	1670.00 229	2523.00 229	689.00 218	676.00 217

PCF-MVS	4335.85 20	2272.23 213	2597.03 216	1297.84 221	1701.20 235	1332.37 232	8105.11 243	451.45 235	4031.84 234	1099.10 228	3966.50 233	467.45 228	1734.05 231	2701.68 232	848.94 238	827.11 228
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
CMPMVS	2623.62 15	1983.08 209	2156.14 211	1463.89 230	1414.80 232	1517.00 236	5239.20 224	867.40 266	3310.30 228	1128.70 229	3489.90 228	366.75 221	2030.20 241	2427.60 228	1160.60 260	844.46 230
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
OpenMVS	2352.88 13	2263.08 212	2530.89 215	1459.67 229	1767.00 243	1591.00 239	7932.00 241	399.00 228	3643.00 230	1176.00 230	3569.00 230	297.00 211	1927.00 237	3302.00 235	693.00 223	861.00 231

MVS-HIRNet		2125.39 210	2452.68 213	1143.53 218	2938.33 273	1446.92 235	6083.19 227	391.74 226	3801.71 232	1202.10 231	3439.72 227	492.73 230	1304.35 226	3048.25 234	676.32 217	679.32 218

ZD-MVS					1584.00 233	1821.00 256		378.00 225	3721.00 231	1231.00 232	1833.00 213	321.00 215	1224.00 225	2103.00 226	692.00 222

DeepPCF-MVS	3452.42 18	2670.71 221	3021.57 223	1618.12 232	2377.67 259	1751.39 252	8915.70 248	567.44 254	4569.74 241	1236.84 233	4615.63 239	513.23 231	2291.32 243	3515.48 239	882.39 240	811.66 224

PLC	2858.82 16	2192.92 211	2474.00 214	1349.67 222	1407.00 231	1356.00 233	7164.00 233	475.00 239	3970.00 233	1237.00 234	3765.00 232	451.00 227	1891.00 235	3006.00 233	791.00 234	802.00 222
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
Vis-MVSNet		2877.42 224	3170.00 227	1999.67 245	1673.00 234	2042.00 262	8593.00 246	474.00 238	6452.00 258	1268.00 235	5125.00 246	339.00 217	3004.00 259	4222.00 249	384.00 206	953.00 241
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
DeepC-MVS	3917.13 19	3155.06 227	3601.83 230	1814.72 240	2515.52 262	1941.53 257	10432.50 263	589.42 255	4789.45 242	1298.65 236	7677.31 264	578.35 238	2589.53 249	3611.78 241	923.52 243	913.10 236
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
test_0728_THIRD									5016.02 245	1363.85 237	4894.28 243	387.23 222	2023.43 238	3973.88 243	620.04 214	732.56 219

test0726					1725.60 236	1598.35 240	9203.30 249	315.86 216	5016.02 245	1363.85 237	4894.28 243	387.23 222

SD-MVS		2654.53 220	3055.56 225	1451.45 227	1725.60 236	1598.35 240	9203.30 249	315.86 216	5016.02 245	1363.85 237	4894.28 243	387.23 222	2023.43 238	3973.88 243	620.04 214	732.56 219
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
3Dnovator	2482.06 14	2531.17 217	2839.56 220	1606.00 231	1732.00 239	1557.00 238	8375.00 245	483.00 240	4370.00 239	1371.00 240	4200.00 234	350.00 218	2207.00 242	3877.00 242	798.00 235	1054.00 252

SteuartSystems-ACMMP		2891.50 225	3284.78 228	1711.67 235	1954.00 246	1655.00 246	10117.00 262	445.00 234	5102.00 248	1375.00 241	5126.00 247	351.00 219	2638.00 255	4402.00 250	691.00 221	842.00 229
Skip Steuart: Steuart Systems R&D Blog.
AdaColmap		2570.77 219	2948.61 222	1437.24 226	1873.64 245	1526.60 237	7819.77 240	373.97 223	4970.45 243	1479.29 242	4648.46 240	525.80 233	1904.97 236	4150.42 247	695.69 224	880.14 235

LF4IMVS		2699.50 222	3049.67 224	1649.00 233	1755.00 240	1689.00 247	8330.00 244	464.00 237	4997.00 244	1528.00 243	4763.00 242	568.00 237	2296.00 244	4215.00 248	827.00 237	962.00 242

tpmrst		2557.50 218	2847.12 221	1688.66 234	1784.08 244	1778.25 253	7445.50 239	342.14 219	4471.54 240	1534.55 244	4382.10 238	530.10 234	2361.21 245	4142.81 246	991.22 246	926.51 237

CHOSEN 280x420		2340.81 214	2643.03 217	1434.14 223	2025.55 252	1629.36 243	6542.40 229	412.49 229	4219.70 236	1547.02 245	4328.52 235	650.74 246	1798.26 232	3333.17 236	727.72 225	874.79 232

CHOSEN 1792x2688		2340.81 214	2643.03 217	1434.14 223	2025.55 252	1629.36 243	6542.40 229	412.49 229	4219.70 236	1547.02 245	4328.52 235	650.74 246	1798.26 232	3333.17 236	727.72 225	874.79 232

HyFIR lowres test		2340.81 214	2643.03 217	1434.14 223	2025.55 252	1629.36 243	6542.40 229	412.49 229	4219.70 236	1547.02 245	4328.52 235	650.74 246	1798.26 232	3333.17 236	727.72 225	874.79 232

DPM-MVS		3268.00 228	3762.89 231	1783.33 238	1756.00 241	1806.00 254	12319.00 265	307.00 214	6319.00 256	1557.00 248	5763.00 249	302.00 213	2609.00 251	5061.00 254	482.00 209	935.00 239

OPM-MVS		3268.00 228	3762.89 231	1783.33 238	1756.00 241	1806.00 254	12319.00 265	307.00 214	6319.00 256	1557.00 248	5763.00 249	302.00 213	2609.00 251	5061.00 254	482.00 209	935.00 239
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
EGC-MVSNET		2819.75 223	3096.89 226	1988.33 244	3105.00 274	2241.00 264	9480.00 253	640.00 260	4209.00 235	1583.00 250	4740.00 241	547.00 236	2797.00 257	2644.00 231	924.00 244	927.00 238

tpm2		3617.85 232	4007.23 234	2449.73 252	2012.71 248	1698.05 248	7351.19 235	869.29 267	6132.06 251	1588.28 251	8007.42 267	1281.09 273	3888.11 271	7472.04 272	1351.00 262	1763.02 268

tpm cat1		3617.85 232	4007.23 234	2449.73 252	2012.71 248	1698.05 248	7351.19 235	869.29 267	6132.06 251	1588.28 251	8007.42 267	1281.09 273	3888.11 271	7472.04 272	1351.00 262	1763.02 268

CostFormer		3617.85 232	4007.23 234	2449.73 252	2012.71 248	1698.05 248	7351.19 235	869.29 267	6132.06 251	1588.28 251	8007.42 267	1281.09 273	3888.11 271	7472.04 272	1351.00 262	1763.02 268

tpm		3617.85 232	4007.23 234	2449.73 252	2012.71 248	1698.05 248	7351.19 235	869.29 267	6132.06 251	1588.28 251	8007.42 267	1281.09 273	3888.11 271	7472.04 272	1351.00 262	1763.02 268

DVP-MVS++		3981.10 238	4731.32 243	1730.42 236	2191.51 255	1949.98 258	16473.90 274	355.33 220	7172.90 267	1622.98 255	7879.79 265	434.33 225	2428.11 247	5762.12 257	689.04 219	813.18 225

DVP-MVS		3981.10 238	4731.32 243	1730.42 236	2191.51 255	1949.98 258	16473.90 274	355.33 220	7172.90 267	1622.98 255	7879.79 265	434.33 225	2428.11 247	5762.12 257	689.04 219	813.18 225
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
OpenMVS_ROB	1936.51 10	1959.51 208	2224.88 212	1163.39 219	1253.91 227	1434.22 234	7065.71 232	272.76 212	2472.29 223	1647.54 257	3538.72 229	200.37 198	1496.48 228	2575.17 230	997.45 247	559.48 209

TAPA-MVS	6309.84 21	3374.90 230	3806.99 233	2078.63 247	2535.47 263	2499.25 272	8816.16 247	456.05 236	6255.60 255	1664.52 258	6704.88 254	629.95 244	2768.38 256	6343.93 268	856.35 239	968.25 243
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
TSAR-MVS + MP.		3528.01 231	4065.89 238	1914.35 241	2349.10 258	2141.30 263	12362.70 267	417.60 233	6717.80 262	1759.40 259	6497.50 252	518.18 232	2629.38 254	5164.32 256	806.40 236	972.38 244
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
3Dnovator+	3414.41 17	3146.67 226	3537.00 229	1975.67 242	2310.00 257	2005.00 261	10100.00 261	626.00 259	5753.00 249	1803.00 260	5179.00 248	487.00 229	2622.00 253	4550.00 251	1025.00 255	1300.00 259

ITE_SJBPF				2014.00 246	1998.00 247	1992.00 260		701.00 262	5989.00 250	1812.00 261	3612.00 231	650.00 245	2852.00 258	4601.00 252	1195.00 261	1198.00 258

MVS_111021_HR		3742.80 236	4330.34 239	1980.20 243	2484.31 261	2259.52 265	14973.80 272	515.90 253	6500.13 259	1949.21 262	6146.89 251	535.66 235	2593.66 250	4880.76 253	986.37 245	1087.43 253

FOURS1					2643.17 264	2465.14 267	13996.40 269	493.26 241	7619.38 270	2107.24 263

PC_three_1452									7619.38 270	2107.24 263	7416.93 261	610.24 241	3088.29 264	6075.14 264	1078.39 256	1159.26 254

test_one_0601					2643.17 264	2465.14 267		493.26 241	7619.38 270	2107.24 263	7416.93 261	610.24 241

SED-MVS		4062.74 241	4671.13 242	2237.56 248	2643.17 264	2465.14 267	13996.40 269	493.26 241	7619.38 270	2107.24 263	7416.93 261	610.24 241	3088.29 264	6075.14 264	1078.39 256	1159.26 254

IU-MVS					2725.60 269	2598.35 273		515.86 249	7016.02 263	2363.85 267				5973.88 260	1620.04 268	1732.56 264

test_241102_TWO								515.86 249	7016.02 263	2363.85 267	6894.28 255	887.23 259	3023.43 260	5973.88 260	1620.04 268	1732.56 264

test_241102_ONE					2725.60 269	2598.35 273		515.86 249	7016.02 263	2363.85 267	6894.28 255	887.23 259	3023.43 260

MSP-MVS		4296.20 242	4911.12 246	2451.45 256	2725.60 269	2598.35 273	16203.30 273	515.86 249	7016.02 263	2363.85 267	6894.28 255	887.23 259	3023.43 260	5973.88 260	1620.04 268	1732.56 264
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
GST-MVS		4000.00 240	4533.33 241	2400.00 251	2400.00 260	2400.00 266	7200.00 234	2400.00 283	7200.00 269	2400.00 271	7200.00 259	2400.00 277	2400.00 246	7200.00 270	2400.00 274	2400.00 273

MAR-MVS		3973.16 237	4387.92 240	2728.86 258	3345.27 275	3341.39 279	11403.90 264	798.76 264	6555.62 261	2569.29 272	6514.86 253	834.97 258	3237.43 268	5891.08 259	1577.54 267	1607.76 260
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
API-MVS		4380.83 243	4906.56 245	2803.67 259	3844.00 276	3116.00 278	13454.00 268	901.00 271	6511.00 260	2794.00 273	7365.00 260	754.00 255	3634.00 269	6622.00 269	1914.00 273	1661.00 263

OMC-MVS		5022.26 244	5748.82 247	2842.58 260	4905.27 278	3101.27 277	14933.60 271	812.24 265	9278.40 274	2959.29 274	8800.17 271	1092.24 271	3806.30 270	7568.54 276	1389.60 266	1620.18 262

LS3D		7684.71 246	8776.23 249	4410.16 262	5298.55 279	5631.53 281	34329.90 279	1504.57 281	11554.00 283	3896.41 275	15111.00 280	812.19 256	5985.63 276	3516.20 240	2963.23 275	1613.31 261

CLD-MVS		7338.25 245	8341.00 248	4330.00 261	4902.00 277	4991.00 280	23318.00 277	728.00 263	14437.00 284	4378.00 276	13379.00 279	824.00 257	5708.00 275	11429.00 285	1674.00 272	2291.00 272
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
MVE	10021.00 22	10550.67 254	10002.44 257	12195.33 271	6242.00 280	8768.00 283	30896.00 278	4451.00 284	10331.00 282	6247.00 277	18296.00 281	283.00 210	21484.00 285	7364.00 271	5912.00 277	6334.00 275
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CNLPA		10738.67 255	11772.44 258	7637.33 263	9120.00 281	8206.00 282	22252.00 276	2010.00 282	24984.00 285	7458.00 278	22596.00 282	2940.00 278	10260.00 284	11100.00 284	3492.00 276	4446.00 274

ZNCC-MVS		9999.00 247	9999.00 250	9999.00 264	9999.00 282	9999.00 284	9999.00 254	9999.00 287	9999.00 275	9999.00 279	9999.00 272	9999.00 280	9999.00 277	9999.00 277	9999.00 278	9999.00 276

patch_mono-2		10000.00 248	10000.00 251	10000.00 265	10000.00 283	10000.00 285	10000.00 255	10000.00 288	10000.00 276	10000.00 280	10000.00 273	10000.00 281	10000.00 278	10000.00 278	10000.00 279	10000.00 277

dcpmvs_2		10000.00 248	10000.00 251	10000.00 265	10000.00 283	10000.00 285	10000.00 255	10000.00 288	10000.00 276	10000.00 280	10000.00 273	10000.00 281	10000.00 278	10000.00 278	10000.00 279	10000.00 277

DCPMVS		10000.00 248	10000.00 251	10000.00 265	10000.00 283	10000.00 285	10000.00 255	10000.00 288	10000.00 276	10000.00 280	10000.00 273	10000.00 281	10000.00 278	10000.00 278	10000.00 279	10000.00 277

UA-Net		10000.00 248	10000.00 251	10000.00 265	10000.00 283	10000.00 285	10000.00 255	10000.00 288	10000.00 276	10000.00 280	10000.00 273	10000.00 281	10000.00 278	10000.00 278	10000.00 279	10000.00 277

uncertanet		10000.00 248	10000.00 251	10000.00 265	10000.00 283	10000.00 285	10000.00 255	10000.00 288	10000.00 276	10000.00 280	10000.00 273	10000.00 281	10000.00 278	10000.00 278	10000.00 279	10000.00 277

uanet		10000.00 248	10000.00 251	10000.00 265	10000.00 283	10000.00 285	10000.00 255	10000.00 288	10000.00 276	10000.00 280	10000.00 273	10000.00 281	10000.00 278	10000.00 278	10000.00 279	10000.00 277

LTVRE_ROB	20565.47 23	23378.08 256	22805.00 259	25097.33 272	15500.00 289	19201.00 291	42712.00 280	6055.00 285	38388.00 286	16926.00 286	38534.00 283	7071.00 279	35653.00 286	29475.00 286	10584.00 285	20438.00 284
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		32606.17 257	34443.44 260	27094.33 273	29249.00 290	25246.00 292	51144.00 281	6705.00 286	42886.00 287	22888.00 287	48534.00 284	13263.00 287	37507.00 287	79298.00 287	16024.00 286	18530.00 283

114514_t		99999.00 258	99999.00 261	99999.00 274	99999.00 291	99999.00 293	99999.00 282	99999.00 294	99999.00 288	99999.00 288	99999.00 285	99999.00 288	99999.00 288	99999.00 288	99999.00 287	99999.00 285

PHI-MVS		99999.00 258	99999.00 261	99999.00 274	99999.00 291	99999.00 293	99999.00 282	99999.00 294	99999.00 288	99999.00 288	99999.00 285	99999.00 288	99999.00 288	99999.00 288	99999.00 287	99999.00 285

XVG-OURS-SEG-HR		999999.00 262	999999.00 263	999999.00 276	999999.00 293	999999.00 295	999999.00 284	999999.00 296	999999.00 290	999999.00 290	999999.00 287	999999.00 290	999999.00 290	999999.00 290	999999.00 289	999999.00 287

XVG-OURS		999999.00 262	999999.00 263	999999.00 276	999999.00 293	999999.00 295	999999.00 284	999999.00 296	999999.00 290	999999.00 290	999999.00 287	999999.00 290	999999.00 290	999999.00 290	999999.00 289	999999.00 287

XVG-ACMP-BASELINE		999999.00 262	999999.00 263	999999.00 276	999999.00 293	999999.00 295	999999.00 284	999999.00 296	999999.00 290	999999.00 290	999999.00 287	999999.00 290	999999.00 290	999999.00 290	999999.00 289	999999.00 287

dmvs_re		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

SDMVSNet		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

dmvs_testset		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

sd_testset		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

iter_conf_final		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

bld_raw_dy_0_64		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

test2506		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

test1111		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

ECVR-MVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

test_blank		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

tt0805		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

Anonymous20240521		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

cl22		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

miper_ehance_all_eth		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

miper_enhance_ethall		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

cl____		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

DIV-MVS_self_test		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

eth_miper_zixun_eth		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

ET-MVSNet_ETH3D		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

UniMVSNet_ETH3D		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

miper_lstm_enhance		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

D2MVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

test_yl		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

thisisatest0530		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

Anonymous20240529		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

Anonymous202405211		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

DCV-MVSNet		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

tttt0517		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

our_test_3		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

thisisatest0515		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

ppachtmachnet_test		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

SMA-MVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290
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		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part2					10000000.00 296	10000000.00 298				10000000.00 293

thres100view900		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

tfpnnormal		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

tfpn200view9		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

c3_l		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

IterMVS-SCA-FT		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

pmmvs6		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

pmmvs5		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

Anonymous20231211		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

pmmvs-eth3d		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

Anonymous20231206		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

SCA		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

Patchmatch-test		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

Patchmatch-RL test		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

canonicalmvs		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

anonymousdsp		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

FIs		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

FC-MVSNet-test		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

sosnet-low-res		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

AllTest		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

TestCases				10000000.00 279	10000000.00 296	10000000.00 298		10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

iter_conf05		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

RRT_MVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

HPM-MVS++		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

XVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

pm-mvs1		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

X-MVStestdata		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

APDe-MVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
APD-MVS_3200maxsize		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

pmmvs4		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

test-LLR		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

TESTMET0.1,1		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

test-mter		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

testgi		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

test20.03		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

thres600view7		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

MP-MVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

thres400		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

test123		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

thres200		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

test0.0.03 1		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

pmmvs3		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

EMVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

E-PMN		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

PGM-MVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

MCST-MVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

MVS_Test		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

PMMVS2		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

PM-MVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

HQP_MVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

plane_prior3						10000000.00 298			10000000.00 293	10000000.00 293

mPP-MVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

mvsmamba		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

HPM-MVS_fast		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

HPM-MVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
LPG-MVS_test		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

LGP-MVS_train				10000000.00 279	10000000.00 296	10000000.00 298		10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

EPNet_dtu		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP-NCC					10000000.00 296		10000000.00 287		10000000.00 293	10000000.00 293

ACMP_Plane					10000000.00 296		10000000.00 287		10000000.00 293	10000000.00 293

HQP4-MVS										10000000.00 293			10000000.00 293			10000000.00 290

CNVR-MVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

NCCC		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

CP-MVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

CPTT-MVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

HQP-MVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

IS-MVSNet		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

PAPM_NR		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

PAPR		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

Vis-MVSNet (Re-imp)		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

PatchMatch-RL		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

TDRefinement		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

EPP-MVSNet		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

PMMVS		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

PAPM		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

ACMMP		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290
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		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

wuyk23d		10000000.00 265	10000000.00 268	10000000.00 279	10000000.00 296	10000000.00 298	10000000.00 287	10000000.00 299	10000000.00 293	10000000.00 293	10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

APD-MVS		1000000000.00 371	1000000000.00 374	1000000000.00 387	1000000000.00 412	1000000000.00 412	1000000000.00 398	1000000000.00 412	1000000000.00 405	1000000000.00 406	1000000000.00 403	1000000000.00 408	1000000000.00 406	1000000000.00 405	1000000000.00 404	1000000000.00 402
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
WAC-MVS						248.46 168								422.23 163

MSC_two_6792asdad				2237.56 248	2643.17 264	2465.14 267		493.26 241					3088.29 264	6075.14 264	1078.39 256	1159.26 254

No_MVS				2237.56 248	2643.17 264	2465.14 267		493.26 241					3088.29 264	6075.14 264	1078.39 256	1159.26 254

eth-test2					1.42 77

eth-test					10000000.00 296

OPU-MVS				2451.45 256	2725.60 269	2598.35 273	9203.30 249				6894.28 255	887.23 259	3023.43 260	5973.88 260	1620.04 268	1732.56 264

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

test_0728_SECOND				1451.45 227	1725.60 236	1598.35 240	9203.30 249	315.86 216					2023.43 238	3973.88 243	620.04 214	732.56 219

GSMVS																10000000.00 290

sam_mvs1												10000000.00 293				10000000.00 290

sam_mvs												10000000.00 293

MTGPA								10000000.00 299

test_post1							10000000.00 287				10000000.00 290	10000000.00 293	10000000.00 293	10000000.00 293

test_post											10000000.00 290	10000000.00 293	10000000.00 293

patchmatchnet-post											10000000.00 290	10000000.00 293	10000000.00 293

MTMP							10000000.00 287	10000000.00 299

gm-plane-assit					611.29 193	600.33 201			579.21 164		567.40 160		531.67 181	503.93 169

test9_res														0.00 1	0.00 1	0.00 1

agg_prior2														0.00 1	0.00 1	0.00 1

test_prior4						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

新几何2							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

testdata2													0.00 1	0.00 1

segment_acmp												0.00 1

testdata1							0.00 1		0.00 1

plane_prior7					10000000.00 296	10000000.00 298

plane_prior6					10000000.00 296	10000000.00 298						10000000.00 293

plane_prior5								10000000.00 299					10000000.00 293	10000000.00 293	10000000.00 292	10000000.00 290

plane_prior4											10000000.00 290

plane_prior2							10000000.00 287		10000000.00 293

plane_prior1					10000000.00 296

plane_prior						1.00 71	2.00 99		2.00 100						2.00 98

n2								14.20 141

nn								1.42 79

door-mid								1.42 79

test11								1.00 72

door								99.00 180

HQP5-MVS						10000000.00 298

BP-MVS														10000000.00 293

HQP3-MVS								10000000.00 299							10000000.00 292

HQP2-MVS												10000000.00 293

NP-MVS					10000000.00 296	10000000.00 298					10000000.00 290

ACMMP++_ref															10000000.00 292

ACMMP++															10000000.00 292

Test By Simon												990.00 263

High-resolution multi-view benchmark