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_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

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

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_prior				0.00 1	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

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 22	0.30 23	0.30 27	0.30 34	0.30 34	0.30 34	0.30 35	0.30 34	0.30 33	0.30 31	0.30 33	0.30 34	0.30 32	0.30 32	0.30 32

hse-mvs2		0.30 22	0.30 23	0.30 27	0.30 34	0.30 34	0.30 34	0.30 35	0.30 34	0.30 33	0.30 31	0.30 33	0.30 34	0.30 32	0.30 32	0.30 32

CL-MVSNet_self_test		0.30 22	0.30 23	0.30 27	0.30 34	0.30 34	0.30 34	0.30 35	0.30 34	0.30 33	0.30 31	0.30 33	0.30 34	0.30 32	0.30 32	0.30 32

AUN-MVS		0.30 22	0.30 23	0.30 27	0.30 34	0.30 34	0.30 34	0.30 35	0.30 34	0.30 33	0.30 31	0.30 33	0.30 34	0.30 32	0.30 32	0.30 32

LCM-MVSNet		0.37 26	0.36 27	0.37 31	0.37 38	0.37 38	0.37 38	0.32 39	0.37 38	0.37 37	0.37 35	0.37 37	0.37 38	0.37 36	0.37 36	0.37 36

v144192		0.40 27	0.40 28	0.40 32	0.40 39	0.40 39	0.40 39	0.40 41	0.40 39	0.40 38	0.40 36	0.40 38	0.40 39	0.40 37	0.40 37	0.40 37

v1921920		0.40 27	0.40 28	0.40 32	0.40 39	0.40 39	0.40 39	0.40 41	0.40 39	0.40 38	0.40 36	0.40 38	0.40 39	0.40 37	0.40 37	0.40 37

v1192		0.40 27	0.40 28	0.40 32	0.40 39	0.40 39	0.40 39	0.40 41	0.40 39	0.40 38	0.40 36	0.40 38	0.40 39	0.40 37	0.40 37	0.40 37

v1144		0.40 27	0.40 28	0.40 32	0.40 39	0.40 39	0.40 39	0.40 41	0.40 39	0.40 38	0.40 36	0.40 38	0.40 39	0.40 37	0.40 37	0.40 37

v148		0.40 27	0.40 28	0.40 32	0.40 39	0.40 39	0.40 39	0.40 41	0.40 39	0.40 38	0.40 36	0.40 38	0.40 39	0.40 37	0.40 37	0.40 37

v7n		0.40 27	0.40 28	0.40 32	0.40 39	0.40 39	0.40 39	0.40 41	0.40 39	0.40 38	0.40 36	0.40 38	0.40 39	0.40 37	0.40 37	0.40 37

v1240		0.40 27	0.40 28	0.40 32	0.40 39	0.40 39	0.40 39	0.40 41	0.40 39	0.40 38	0.40 36	0.40 38	0.40 39	0.40 37	0.40 37	0.40 37

v8		0.40 27	0.40 28	0.40 32	0.40 39	0.40 39	0.40 39	0.40 41	0.40 39	0.40 38	0.40 36	0.40 38	0.40 39	0.40 37	0.40 37	0.40 37

v10		0.40 27	0.40 28	0.40 32	0.40 39	0.40 39	0.40 39	0.40 41	0.40 39	0.40 38	0.40 36	0.40 38	0.40 39	0.40 37	0.40 37	0.40 37

v2v482		0.40 27	0.40 28	0.40 32	0.40 39	0.40 39	0.40 39	0.40 41	0.40 39	0.40 38	0.40 36	0.40 38	0.40 39	0.40 37	0.40 37	0.40 37

V42		0.40 27	0.40 28	0.40 32	0.40 39	0.40 39	0.40 39	0.40 41	0.40 39	0.40 38	0.40 36	0.40 38	0.40 39	0.40 37	0.40 37	0.40 37

GA-MVS		0.40 27	0.40 28	0.40 32	0.40 39	0.40 39	0.40 39	0.40 41	0.40 39	0.40 38	0.40 36	0.40 38	0.40 39	0.40 37	0.40 37	0.40 37

Fast-Effi-MVS+		0.41 39	0.40 28	0.41 44	0.41 51	0.41 51	0.41 51	0.35 40	0.41 51	0.41 50	0.41 48	0.41 50	0.41 51	0.41 49	0.41 49	0.41 49

Fast-Effi-MVS+-dtu		0.44 40	0.44 41	0.44 45	0.44 52	0.44 52	0.44 52	0.44 53	0.44 52	0.44 51	0.44 49	0.44 51	0.44 52	0.44 50	0.44 50	0.44 50

Effi-MVS+-dtu		0.59 42	0.61 44	0.53 46	0.68 60	0.53 53	0.53 53	0.68 61	0.68 60	0.53 52	0.53 50	0.68 59	0.53 53	0.68 58	0.53 51	0.53 51

KD-MVS_self_test		0.60 43	0.60 43	0.60 47	0.60 54	0.60 54	0.60 55	0.60 55	0.60 54	0.60 53	0.60 51	0.60 53	0.60 54	0.60 51	0.60 53	0.60 52

EIA-MVS		0.62 44	0.62 45	0.62 48	0.62 55	0.62 55	0.62 56	0.62 56	0.62 55	0.62 54	0.62 52	0.62 54	0.62 55	0.62 52	0.62 54	0.62 53

ETV-MVS		0.62 44	0.62 45	0.62 48	0.62 55	0.62 55	0.62 56	0.62 56	0.62 55	0.62 54	0.62 52	0.62 54	0.62 55	0.62 52	0.62 54	0.62 53

CS-MVS		0.62 44	0.62 45	0.62 48	0.62 55	0.62 55	0.62 56	0.62 56	0.62 55	0.62 54	0.62 52	0.62 54	0.62 55	0.62 52	0.62 54	0.62 53

CS-MVS-test		0.62 44	0.62 45	0.62 48	0.62 55	0.62 55	0.62 56	0.62 56	0.62 55	0.62 54	0.62 52	0.62 54	0.62 55	0.62 52	0.62 54	0.62 53

Effi-MVS+		0.58 41	0.56 42	0.62 48	0.53 53	0.62 55	0.53 53	0.53 54	0.53 53	0.62 54	0.62 52	0.53 52	0.62 55	0.62 52	0.53 51	0.62 53

DROMVSNet		0.62 44	0.62 45	0.62 48	0.62 55	0.62 55	0.62 56	0.62 56	0.62 55	0.62 54	0.62 52	0.62 54	0.62 55	0.62 52	0.62 54	0.62 53

CDS-MVSNet		0.88 49	0.88 50	0.88 54	0.88 61	0.88 61	0.88 61	0.88 62	0.88 61	0.88 60	0.88 58	0.88 60	0.88 61	0.88 59	0.88 59	0.88 59
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		0.88 49	0.88 50	0.88 54	0.88 61	0.88 61	0.88 61	0.88 62	0.88 61	0.88 60	0.88 58	0.88 60	0.88 61	0.88 59	0.88 59	0.88 59

LCM-MVSNet-Re		0.89 51	0.89 52	0.89 56	0.89 63	0.89 63	0.89 63	0.89 64	0.89 63	0.89 62	0.89 60	0.89 62	0.89 63	0.89 61	0.89 61	0.89 61

DeepMVS_CX				1.00 57	1.00 64	1.00 64		1.00 65	1.00 64	1.00 63	1.00 61	1.00 63	1.00 64	1.00 62	1.00 62	1.00 62

MDA-MVSNet-bldmvs		1.20 52	1.20 53	1.20 58	1.20 65	1.20 66	1.20 64	1.20 67	1.20 65	1.20 64	1.20 62	1.20 64	1.20 65	1.20 63	1.20 63	1.20 63

YYNet1		1.20 52	1.20 53	1.20 58	1.20 65	1.20 66	1.20 64	1.20 67	1.20 65	1.20 64	1.20 62	1.20 64	1.20 65	1.20 63	1.20 63	1.20 63

MDA-MVSNet_test_wron		1.20 52	1.20 53	1.20 58	1.20 65	1.20 66	1.20 64	1.20 67	1.20 65	1.20 64	1.20 62	1.20 64	1.20 65	1.20 63	1.20 63	1.20 63

KD-MVS_2432*1600		1.30 55	1.30 56	1.30 61	1.30 68	1.30 69	1.30 67	1.30 70	1.30 68	1.30 67	1.30 65	1.30 67	1.30 68	1.30 66	1.30 66	1.30 66

miper_refine_blended		1.30 55	1.30 56	1.30 61	1.30 68	1.30 69	1.30 67	1.30 70	1.30 68	1.30 67	1.30 65	1.30 67	1.30 68	1.30 66	1.30 66	1.30 66

EI-MVSNet-UG-set		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

EI-MVSNet-Vis-set		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

EI-MVSNet		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

Regformer		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

CVMVSNet		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

EU-MVSNet		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

PS-CasMVS		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

UniMVSNet_NR-MVSNet		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

PEN-MVS		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

TransMVSNet (Re)		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

DTE-MVSNet		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

DU-MVS		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

UniMVSNet (Re)		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

CP-MVSNet		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

WR-MVS_H		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

WR-MVS		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

NR-MVSNet		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

Baseline_NR-MVSNet		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

TranMVSNet+NR-MVSNet		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

MVSFormer		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

jason		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68
jason: jason.
lupinMVS		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

test_djsdf		1.42 57	1.42 58	1.42 63	1.42 70	1.42 71	1.42 69	1.42 72	1.42 70	1.42 69	1.42 67	1.42 69	1.42 70	1.42 68	1.42 68	1.42 68

alignmvs		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

nrg030		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

LFMVS		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

VDD-MVS		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

VDDNet		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

VPNet		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

VNet		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

VPA-MVSNet		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

cascas		2.00 80	2.00 81	2.00 86	2.00 94	2.00 94	2.00 92	2.00 97	2.00 93	2.00 92	2.00 90	2.00 92	2.00 93	2.00 91	2.00 91	2.00 91

UnsupCasMVSNet_eth		5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

UnsupCasMVSNet_bld		5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

WTY-MVS		5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

HY-MVS	5.90 1	5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

sss		5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

Test_1112_low_res		5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

1112_ss		5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

ab-mvs-re		5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

ab-mvs		5.90 89	5.90 90	5.90 95	5.90 103	5.90 103	5.90 102	5.90 109	5.90 103	5.90 101	5.90 99	5.90 103	5.90 102	5.90 100	5.90 103	5.90 103

CDPH-MVS		6.66 98	6.66 99	6.66 104	6.66 112	6.66 112	6.66 111	6.66 118	6.66 112	6.66 110	6.66 108	6.66 112	6.66 111	6.66 109	6.66 112	6.66 112

dp		87.20 118	113.80 122	7.42 105	10.50 124	8.88 113	298.82 139	2.70 106	510.35 157	7.79 111	172.93 132	3.37 101	9.16 112	14.00 123	3.71 101	4.23 101

xiu_mvs_v1_base_debu		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

xiu_mvs_v2_base		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

xiu_mvs_v1_base		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

xiu_mvs_v1_base_debi		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

cdsmvs_eth3d_5k		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

pcd_1.5k_mvsjas		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

PS-MVSNAJss		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

PS-MVSNAJ		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

jajsoiax		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

mvs_tets		10.28 99	10.28 101	10.28 106	10.28 114	10.28 116	10.28 114	10.28 121	10.28 115	10.28 114	10.28 110	10.28 116	10.28 114	10.28 112	10.28 115	10.28 114

test_method		18.29 111	20.89 113	10.50 116	15.00 126	13.00 128	55.00 131	3.00 107	34.00 128	11.50 124	32.50 122	5.00 102	13.50 125	27.00 126	5.00 102	5.00 102

GeoE		19.41 112	22.09 114	11.37 117	17.21 128	11.30 126	50.50 130	4.30 108	33.60 127	11.70 126	44.50 127	7.30 113	18.90 127	22.60 125	7.10 113	3.90 100

SR-MVS-dyc-post		11.55 109	11.55 111	11.55 118	11.55 125	11.55 127	11.55 124	11.55 133	11.55 125	11.55 125	11.55 120	11.55 127	11.55 124	11.55 122	11.55 125	11.55 124

XXY-MVS		15.00 110	15.00 112	15.00 119	15.00 126	15.00 129	15.00 125	15.00 135	15.00 126	15.00 127	15.00 121	15.00 131	15.00 126	15.00 124	15.00 127	15.00 126

GBi-Net		44.67 117	49.24 119	30.96 120	47.53 133	47.57 134	126.09 132	8.00 119	76.99 133	26.09 128	73.50 129	11.27 126	30.55 128	61.12 131	12.58 126	14.75 125

BH-w/o		40.00 113	40.00 115	40.00 121	40.00 129	40.00 130	40.00 126	40.00 153	40.00 129	40.00 129	40.00 123	40.00 149	40.00 129	40.00 127	40.00 142	40.00 137

BH-untuned		40.00 113	40.00 115	40.00 121	40.00 129	40.00 130	40.00 126	40.00 153	40.00 129	40.00 129	40.00 123	40.00 149	40.00 129	40.00 127	40.00 142	40.00 137

BH-RMVSNet		40.00 113	40.00 115	40.00 121	40.00 129	40.00 130	40.00 126	40.00 153	40.00 129	40.00 129	40.00 123	40.00 149	40.00 129	40.00 127	40.00 142	40.00 137

TR-MVS		40.00 113	40.00 115	40.00 121	40.00 129	40.00 130	40.00 126	40.00 153	40.00 129	40.00 129	40.00 123	40.00 149	40.00 129	40.00 127	40.00 142	40.00 137

new_pmnet		88.14 119	98.62 120	56.70 125	98.14 141	56.07 135	246.79 134	15.37 136	148.06 134	50.77 133	143.13 130	23.35 132	62.65 133	93.26 132	68.71 150	51.38 148

N_pmnet		88.14 119	98.62 120	56.70 125	98.14 141	56.07 135	246.79 134	15.37 136	148.06 134	50.77 133	143.13 130	23.35 132	62.65 133	93.26 132	68.71 150	51.38 148

MTAPA		833442.10 250	1111233.77 256	67.09 127	65.59 134	64.81 137	284.50 136	10000000.00 288	219.97 140	59.62 135	229.89 144	12.72 128	103.00 149	203.67 150	27.93 128	33.46 127

CANet		110.62 121	124.04 123	70.34 128	82.03 137	74.27 140	325.54 140	25.25 138	207.16 136	69.28 138	194.38 133	27.53 134	95.79 142	147.76 136	37.43 131	40.97 141

CANet_DTU		110.62 121	124.04 123	70.34 128	82.03 137	74.27 140	325.54 140	25.25 138	207.16 136	69.28 138	194.38 133	27.53 134	95.79 142	147.76 136	37.43 131	40.97 141

MVS_0304		110.62 121	124.04 123	70.34 128	82.03 137	74.27 140	325.54 140	25.25 138	207.16 136	69.28 138	194.38 133	27.53 134	95.79 142	147.76 136	37.43 131	40.97 141

UGNet		110.62 121	124.04 123	70.34 128	82.03 137	74.27 140	325.54 140	25.25 138	207.16 136	69.28 138	194.38 133	27.53 134	95.79 142	147.76 136	37.43 131	40.97 141
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
MP-MVS-pluss		833433.63 249	1111219.60 255	75.70 132	74.28 135	73.29 138	284.50 136	11.35 131	238.58 141	65.86 136	255.35 149	14.55 129	115.69 151	10000000.00 281	31.94 129	38.12 135
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
ACMMP_NAP		118.81 125	133.18 127	75.70 132	74.28 135	73.29 138	284.50 136	11.35 131	238.58 141	65.86 136	255.35 149	14.55 129	115.69 151	222.18 151	31.94 129	38.12 135

FMVSNet5		124.76 126	140.93 128	76.26 134	107.44 144	100.17 148	329.88 144	27.12 145	259.44 146	74.30 142	204.34 137	30.74 138	92.41 135	196.98 140	38.15 135	36.19 128

test1		124.76 126	140.93 128	76.26 134	107.44 144	100.17 148	329.88 144	27.12 145	259.44 146	74.30 142	204.34 137	30.74 138	92.41 135	196.98 140	38.15 135	36.19 128

FMVSNet3		124.76 126	140.93 128	76.26 134	107.44 144	100.17 148	329.88 144	27.12 145	259.44 146	74.30 142	204.34 137	30.74 138	92.41 135	196.98 140	38.15 135	36.19 128

FMVSNet2		124.76 126	140.93 128	76.26 134	107.44 144	100.17 148	329.88 144	27.12 145	259.44 146	74.30 142	204.34 137	30.74 138	92.41 135	196.98 140	38.15 135	36.19 128

FMVSNet1		124.76 126	140.93 128	76.26 134	107.44 144	100.17 148	329.88 144	27.12 145	259.44 146	74.30 142	204.34 137	30.74 138	92.41 135	196.98 140	38.15 135	36.19 128

MIMVSNet1		124.76 126	140.93 128	76.26 134	107.44 144	100.17 148	329.88 144	27.12 145	259.44 146	74.30 142	204.34 137	30.74 138	92.41 135	196.98 140	38.15 135	36.19 128

MIMVSNet		124.76 126	140.93 128	76.26 134	107.44 144	100.17 148	329.88 144	27.12 145	259.44 146	74.30 142	204.34 137	30.74 138	92.41 135	196.98 140	38.15 135	36.19 128

PVSNet_Blended_VisFu		136.90 134	155.40 136	81.40 141	111.00 151	96.20 145	407.00 151	25.90 142	251.60 143	85.10 149	240.50 145	37.00 145	99.90 146	199.80 147	40.70 146	48.10 145

PVSNet_BlendedMVS		136.90 134	155.40 136	81.40 141	111.00 151	96.20 145	407.00 151	25.90 142	251.60 143	85.10 149	240.50 145	37.00 145	99.90 146	199.80 147	40.70 146	48.10 145

PVSNet_Blended		136.90 134	155.40 136	81.40 141	111.00 151	96.20 145	407.00 151	25.90 142	251.60 143	85.10 149	240.50 145	37.00 145	99.90 146	199.80 147	40.70 146	48.10 145

DSMNet-mixed		131.33 133	143.00 135	96.33 144	99.00 143	81.00 144	201.00 133	45.00 158	335.00 153	99.00 152	251.00 148	38.00 148	110.00 150	120.00 135	99.00 153	98.00 152

FE-MVS		207.10 137	234.26 139	125.61 145	180.34 154	153.23 155	635.64 158	30.05 152	378.38 154	127.68 153	377.08 151	48.95 153	154.43 153	266.67 152	63.56 149	69.18 150

FA-MVS(test-final)		261.15 138	293.29 140	164.72 146	236.23 157	199.99 158	800.05 163	42.35 157	475.87 156	155.47 154	470.67 153	58.49 154	205.24 155	319.44 153	81.03 152	88.93 151

DP-MVS		264.78 139	296.02 141	171.04 147	191.70 155	183.96 156	827.10 164	78.36 159	438.24 155	176.64 155	435.12 152	65.04 156	230.52 157	334.02 154	117.96 154	98.64 153

RPSCF		394.81 141	445.63 143	242.35 148	276.55 159	253.63 159	1207.27 174	90.69 164	715.56 164	241.57 157	684.87 161	111.96 166	320.02 158	548.38 161	133.81 155	153.39 155

tmp_tt		371.08 140	412.78 142	246.00 149	231.00 156	197.00 157	1293.00 176	376.00 213	756.00 166	609.00 191	71.00 128	106.00 165	195.00 154	102.00 134	171.00 163	346.00 187

EG-PatchMatch MVS		437.03 142	493.12 146	268.77 150	264.80 158	260.20 160	1491.80 179	98.00 168	723.20 165	238.80 156	722.40 162	63.10 155	382.00 161	629.00 165	207.00 170	164.10 158

MVP-Stereo		473.58 145	533.67 147	293.33 151	376.00 163	318.00 161	1461.00 177	96.00 165	835.00 168	290.00 161	804.00 166	97.00 161	383.00 163	688.00 172	156.00 156	179.00 160
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MS-PatchMatch		473.58 145	533.67 147	293.33 151	376.00 163	318.00 161	1461.00 177	96.00 165	835.00 168	290.00 161	804.00 166	97.00 161	383.00 163	688.00 172	156.00 156	179.00 160

DELS-MVS		514.57 149	587.73 152	295.12 153	343.03 160	328.09 163	1540.48 181	116.22 174	988.59 172	325.44 164	906.22 170	119.86 168	365.72 159	788.60 174	161.09 160	191.55 163
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
tpmvs		501.65 148	567.42 150	304.33 154	395.39 165	356.32 164	1512.04 180	216.53 200	994.15 173	350.16 166	804.16 168	119.38 167	380.98 160	555.14 162	159.87 159	175.69 159

PatchmatchNet		492.52 147	551.22 149	316.40 155	400.20 166	357.90 165	1277.10 175	115.80 173	1034.60 180	315.90 163	874.00 169	155.10 171	402.20 165	629.50 166	158.80 158	189.10 162
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
DP-MVS Recon		516.25 150	581.17 151	321.48 156	361.02 161	429.00 171	1995.36 185	78.48 160	796.20 167	283.32 160	796.02 165	96.78 160	382.98 162	636.72 167	186.66 167	152.46 154

ADS-MVSNet2		443.33 143	482.84 144	324.79 157	434.94 170	387.73 167	1110.57 172	87.69 162	887.02 170	282.92 158	779.29 163	98.57 163	422.76 166	502.40 155	162.19 161	163.87 156

ADS-MVSNet		443.33 143	482.84 144	324.79 157	434.94 170	387.73 167	1110.57 172	87.69 162	887.02 170	282.92 158	779.29 163	98.57 163	422.76 166	502.40 155	162.19 161	163.87 156

IB-MVS	872.44 4	616.41 155	700.96 158	362.78 159	426.10 169	409.25 169	1822.69 182	124.42 183	1186.23 183	366.85 168	1079.42 182	190.60 185	451.78 168	930.72 179	181.59 165	227.30 166
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	661.38 156	754.00 159	383.51 160	368.96 162	376.38 166	2483.74 198	82.42 161	1089.25 181	333.39 165	1219.68 185	66.53 157	573.60 183	957.86 180	184.14 166	200.56 164

IterMVS		615.05 154	691.66 157	385.23 161	516.40 173	454.80 172	1863.80 183	102.10 170	1142.20 182	364.10 167	1093.20 184	135.00 169	480.40 169	826.90 175	181.20 164	220.50 165
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CSCG		826.03 170	963.29 175	414.24 162	421.52 168	426.11 170	2230.35 186	179.52 196	1827.44 203	733.43 202	933.12 172	281.25 198	545.23 174	1800.35 209	262.64 184	271.38 175

mvs_anonymous		774.90 161	882.28 167	452.77 163	636.50 187	537.20 178	2348.80 189	120.30 175	1504.30 191	474.40 173	1371.10 190	186.90 177	564.70 176	1078.90 192	219.30 173	256.40 167

casdiffmvs		774.90 161	882.28 167	452.77 163	636.50 187	537.20 178	2348.80 189	120.30 175	1504.30 191	474.40 173	1371.10 190	186.90 177	564.70 176	1078.90 192	219.30 173	256.40 167
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		774.90 161	882.28 167	452.77 163	636.50 187	537.20 178	2348.80 189	120.30 175	1504.30 191	474.40 173	1371.10 190	186.90 177	564.70 176	1078.90 192	219.30 173	256.40 167
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		774.90 161	882.28 167	452.77 163	636.50 187	537.20 178	2348.80 189	120.30 175	1504.30 191	474.40 173	1371.10 190	186.90 177	564.70 176	1078.90 192	219.30 173	256.40 167

baseline1		774.90 161	882.28 167	452.77 163	636.50 187	537.20 178	2348.80 189	120.30 175	1504.30 191	474.40 173	1371.10 190	186.90 177	564.70 176	1078.90 192	219.30 173	256.40 167

casdiffmvs_mvg		774.90 161	882.28 167	452.77 163	636.50 187	537.20 178	2348.80 189	120.30 175	1504.30 191	474.40 173	1371.10 190	186.90 177	564.70 176	1078.90 192	219.30 173	256.40 167
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		774.90 161	882.28 167	452.77 163	636.50 187	537.20 178	2348.80 189	120.30 175	1504.30 191	474.40 173	1371.10 190	186.90 177	564.70 176	1078.90 192	219.30 173	256.40 167

Gipuma		689.75 157	767.00 160	458.00 170	613.00 185	549.00 187	1943.00 184	187.00 197	1230.00 184	518.00 182	1092.00 183	203.00 191	564.00 175	892.00 178	225.00 180	261.00 174
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
IterMVS-LS		758.94 158	856.56 163	466.10 171	606.60 178	546.80 185	2309.90 187	122.20 182	1402.80 188	463.50 172	1348.20 187	192.60 186	574.60 184	1028.60 190	234.60 182	276.90 176
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DeepC-MVS_fast	2190.19 12	1535.59 194	1886.82 198	481.89 172	847.73 201	830.16 205	7943.84 231	189.23 198	2398.83 211	691.73 198	2341.13 208	209.16 193	230.25 156	1999.25 213	360.46 194	385.25 192
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
SixPastTwentyTwo		773.62 160	869.37 166	486.35 173	603.45 177	547.15 186	2532.14 199	106.92 172	1434.95 189	428.08 170	1360.56 188	165.15 175	628.96 189	984.09 181	209.01 172	282.94 177

new-patchmatchnet		766.12 159	859.03 164	487.38 174	595.68 175	536.14 177	2346.27 188	142.51 188	1488.08 190	422.43 169	1361.32 189	163.65 174	628.60 188	1003.74 189	207.61 171	297.41 180

PVSNet	1207.94 6	829.56 171	937.18 174	506.69 175	645.55 194	585.72 188	2477.98 197	130.52 184	1578.29 199	509.50 181	1460.01 197	194.90 187	637.19 190	1170.78 200	267.07 186	297.17 179

MVSTER		890.06 174	1005.91 183	542.52 176	736.13 199	653.90 196	2616.56 201	145.22 190	1692.10 202	555.69 188	1554.72 199	266.25 197	660.02 191	1219.66 201	266.84 185	313.64 183

ACMH	993.80 5	967.92 176	1106.11 186	553.33 177	494.00 172	534.00 176	3581.00 204	136.00 185	1585.00 200	478.00 180	1871.00 203	90.00 158	839.00 195	1460.00 203	260.00 183	287.00 178
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
gg-mvs-nofinetune		594.69 151	605.37 153	562.67 178	617.29 186	500.33 175	772.30 159	413.12 221	579.21 158	552.71 185	567.40 154	662.54 240	531.67 170	503.93 157	779.80 218	656.02 202

lessismore_v0				569.20 179	667.25 196	644.68 195		96.45 167		428.86 171	1514.17 198	204.21 192	756.58 192	1061.60 191	197.79 169	306.34 181

K. test v3		877.74 173	980.16 176	570.46 180	1316.85 219	813.15 204	2565.52 200	103.78 171	1509.49 198	548.33 184	1258.90 186	219.93 196	587.82 185	1102.37 199	196.30 168	310.42 182

GG-mvs-BLEND				596.01 181	611.29 182	600.33 189	790.30 160	513.12 236		552.71 185	567.40 154	662.54 240	531.67 170	503.93 157	779.80 218	656.02 202

CR-MVSNet		612.36 153	617.81 156	596.01 181	611.29 182	600.33 189	790.30 160	513.12 236	579.21 158	552.71 185	567.40 154	662.54 240	531.67 170	503.93 157	779.80 218	656.02 202

SR-MVS		610.10 152	610.10 154	610.10 183	610.10 180	610.10 192	610.10 156	610.10 245	610.10 162	610.10 192	610.10 159	610.10 228	610.10 186	610.10 163	610.10 201	610.10 199

ACMP	1246.57 7	1086.24 184	1235.17 188	639.45 184	596.53 176	639.91 194	3904.24 207	152.04 191	1851.54 204	566.58 189	1997.95 205	138.50 170	938.30 199	1605.46 205	303.70 192	340.14 185
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
MVS_111021_LR		1136.45 187	1298.72 190	649.64 185	756.17 200	726.26 200	3785.94 205	138.15 187	2190.64 209	629.63 195	2064.39 206	165.45 176	874.83 197	1678.43 208	279.70 187	347.82 188

test_0402		1110.00 186	1260.00 189	660.00 186	900.00 205	780.00 203	3300.00 203	210.00 199	2040.00 207	690.00 197	1950.00 204	300.00 201	810.00 194	1620.00 206	330.00 193	390.00 193

RPMNet		787.26 168	829.13 161	661.63 187	885.90 202	895.90 209	455.98 154	610.10 245	1297.17 185	1002.26 214	1001.67 180	655.98 238	611.10 187	667.90 169	885.21 230	477.90 196

ACMM	1311.08 8	1165.06 188	1332.72 191	662.07 188	584.90 174	715.99 199	4373.59 211	153.99 193	1880.27 205	709.02 199	2316.97 207	188.63 184	939.89 200	1484.30 204	302.78 191	330.34 184
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PMVS	863.65 3	957.08 175	1054.11 184	666.00 189	401.00 167	495.00 174	3790.00 206	279.00 202	1607.00 201	521.00 183	1745.00 201	90.00 158	1105.00 212	639.00 168	415.00 197	398.00 194
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PVSNet_0	1661.03 9	968.54 177	1066.82 185	673.70 190	706.94 197	695.69 197	2669.02 202	153.52 192	2108.17 208	605.54 190	1679.14 200	213.26 195	886.75 198	1236.76 202	229.01 181	438.67 195

TSAR-MVS + GP.		1386.84 192	1622.84 196	678.81 191	952.13 206	840.17 206	5358.21 215	170.75 195	2650.47 214	713.54 200	2394.28 211	209.42 194	855.56 196	1854.36 210	302.42 190	340.71 186

JIA-IIPM		804.30 169	835.64 162	710.26 192	885.90 202	895.90 209	455.98 154	668.73 250	1297.17 185	1002.26 214	1001.67 180	655.98 238	756.98 193	667.90 169	885.21 230	477.90 196

MG-MVS		1256.50 190	1432.00 193	730.00 193	610.00 179	760.00 201	4720.00 212	169.00 194	1920.00 206	723.00 201	2510.00 213	201.00 189	1050.00 210	1645.00 207	390.00 196	380.00 191

MSLP-MVS++		1242.93 189	1411.08 192	738.48 194	712.71 198	712.68 198	4168.17 209	136.50 186	2276.40 210	613.28 194	2368.60 210	161.61 173	1130.38 213	1964.54 212	297.88 189	372.39 190

ACMMPR		1296.60 191	1480.82 194	743.96 195	899.25 204	763.47 202	4305.47 210	143.90 189	2530.94 213	683.99 196	2346.34 209	201.65 190	1098.25 211	1920.59 211	295.21 188	370.16 189

Patchmtry		1090.75 185	1198.88 187	766.38 196	1290.90 217	485.90 173	2423.98 196	1267.30 268	1297.17 185	923.90 204	923.40 171	1215.54 261	990.23 201	667.90 169	779.80 218	823.02 216

PatchT		856.34 172	860.99 165	842.38 197	1290.90 217	880.90 207	790.30 160	1267.30 268	579.21 158	923.90 204	567.40 154	662.54 240	990.23 201	887.56 177	779.80 218	656.02 202

ambc				999.00 198	999.00 207	999.00 211	999.00 165	999.00 261		999.00 207	999.00 173	999.00 253	999.00 203	999.00 182	999.00 237	999.00 234

OurMVSNet-221017-0		999.00 178	999.00 177	999.00 198	999.00 207	999.00 211	999.00 165	999.00 261	999.00 174	999.00 207	999.00 173	999.00 253	999.00 203	999.00 182	999.00 237	999.00 234

EPMVS		999.00 178	999.00 177	999.00 198	999.00 207	999.00 211	999.00 165	999.00 261	999.00 174	999.00 207	999.00 173	999.00 253	999.00 203	999.00 182	999.00 237	999.00 234

uanet_test		1000.00 180	1000.00 179	1000.00 201	1000.00 210	1000.00 214	1000.00 168	1000.00 264	1000.00 176	1000.00 210	1000.00 176	1000.00 256	1000.00 206	1000.00 185	1000.00 240	1000.00 237

sosnet		1000.00 180	1000.00 179	1000.00 201	1000.00 210	1000.00 214	1000.00 168	1000.00 264	1000.00 176	1000.00 210	1000.00 176	1000.00 256	1000.00 206	1000.00 185	1000.00 240	1000.00 237

USDC		1000.00 180	1000.00 179	1000.00 201	1000.00 210	1000.00 214	1000.00 168	1000.00 264	1000.00 176	1000.00 210	1000.00 176	1000.00 256	1000.00 206	1000.00 185	1000.00 240	1000.00 237

TinyColmap		1000.00 180	1000.00 179	1000.00 201	1000.00 210	1000.00 214	1000.00 168	1000.00 264	1000.00 176	1000.00 210	1000.00 176	1000.00 256	1000.00 206	1000.00 185	1000.00 240	1000.00 237

COLMAP_ROB	2144.59 11	1658.33 195	1869.33 197	1025.33 205	1030.00 214	1023.00 218	5311.00 214	359.00 211	3044.00 215	937.00 206	2892.00 214	332.00 205	1440.00 216	2312.00 215	607.00 200	613.00 201
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
FPMVS		1407.00 193	1495.59 195	1141.23 206	648.01 195	893.85 208	4124.00 208	503.81 235	3219.04 216	742.72 203	2498.84 212	157.98 172	1727.83 219	832.93 176	732.98 217	802.00 211

MVS-HIRNet		2125.39 199	2452.68 202	1143.53 207	2938.33 262	1446.92 223	6083.19 216	391.74 215	3801.71 221	1202.10 220	3439.72 216	492.73 219	1304.35 215	3048.25 222	676.32 206	679.32 207

OpenMVS_ROB	1936.51 10	1959.51 197	2224.88 201	1163.39 208	1253.91 216	1434.22 222	7065.71 221	272.76 201	2472.29 212	1647.54 246	3538.72 218	200.37 188	1496.48 217	2575.17 218	997.45 236	559.48 198

F-COLMAP		1878.17 196	2113.11 199	1173.33 209	1231.00 215	1174.00 219	6297.00 217	392.00 216	3356.00 218	1087.00 216	3082.00 215	361.00 209	1670.00 218	2523.00 217	689.00 207	676.00 206

PCF-MVS	4335.85 20	2272.23 202	2597.03 205	1297.84 210	1701.20 224	1332.37 220	8105.11 232	451.45 224	4031.84 223	1099.10 217	3966.50 222	467.45 217	1734.05 220	2701.68 220	848.94 227	827.11 217
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
PLC	2858.82 16	2192.92 200	2474.00 203	1349.67 211	1407.00 220	1356.00 221	7164.00 222	475.00 228	3970.00 222	1237.00 223	3765.00 221	451.00 216	1891.00 224	3006.00 221	791.00 223	802.00 211
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
CHOSEN 280x420		2340.81 203	2643.03 206	1434.14 212	2025.55 241	1629.36 231	6542.40 218	412.49 218	4219.70 225	1547.02 234	4328.52 224	650.74 235	1798.26 221	3333.17 224	727.72 214	874.79 221

CHOSEN 1792x2688		2340.81 203	2643.03 206	1434.14 212	2025.55 241	1629.36 231	6542.40 218	412.49 218	4219.70 225	1547.02 234	4328.52 224	650.74 235	1798.26 221	3333.17 224	727.72 214	874.79 221

HyFIR lowres test		2340.81 203	2643.03 206	1434.14 212	2025.55 241	1629.36 231	6542.40 218	412.49 218	4219.70 225	1547.02 234	4328.52 224	650.74 235	1798.26 221	3333.17 224	727.72 214	874.79 221

AdaColmap		2570.77 208	2948.61 211	1437.24 215	1873.64 234	1526.60 225	7819.77 229	373.97 212	4970.45 232	1479.29 231	4648.46 229	525.80 222	1904.97 225	4150.42 235	695.69 213	880.14 224

test_0728_SECOND				1451.45 216	1725.60 225	1598.35 228	9203.30 238	315.86 205					2023.43 227	3973.88 231	620.04 203	732.56 208

SD-MVS		2654.53 209	3055.56 214	1451.45 216	1725.60 225	1598.35 228	9203.30 238	315.86 205	5016.02 234	1363.85 226	4894.28 232	387.23 211	2023.43 227	3973.88 231	620.04 203	732.56 208
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
OpenMVS	2352.88 13	2263.08 201	2530.89 204	1459.67 218	1767.00 232	1591.00 227	7932.00 230	399.00 217	3643.00 219	1176.00 219	3569.00 219	297.00 200	1927.00 226	3302.00 223	693.00 212	861.00 220

CMPMVS	2623.62 15	1983.08 198	2156.14 200	1463.89 219	1414.80 221	1517.00 224	5239.20 213	867.40 255	3310.30 217	1128.70 218	3489.90 217	366.75 210	2030.20 230	2427.60 216	1160.60 249	844.46 219
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
3Dnovator	2482.06 14	2531.17 206	2839.56 209	1606.00 220	1732.00 228	1557.00 226	8375.00 234	483.00 229	4370.00 228	1371.00 229	4200.00 223	350.00 207	2207.00 231	3877.00 230	798.00 224	1054.00 241

DeepPCF-MVS	3452.42 18	2670.71 210	3021.57 212	1618.12 221	2377.67 248	1751.39 240	8915.70 237	567.44 243	4569.74 230	1236.84 222	4615.63 228	513.23 220	2291.32 232	3515.48 227	882.39 229	811.66 213

LF4IMVS		2699.50 211	3049.67 213	1649.00 222	1755.00 229	1689.00 235	8330.00 233	464.00 226	4997.00 233	1528.00 232	4763.00 231	568.00 226	2296.00 233	4215.00 236	827.00 226	962.00 231

tpmrst		2557.50 207	2847.12 210	1688.66 223	1784.08 233	1778.25 241	7445.50 228	342.14 208	4471.54 229	1534.55 233	4382.10 227	530.10 223	2361.21 234	4142.81 234	991.22 235	926.51 226

SteuartSystems-ACMMP		2891.50 214	3284.78 217	1711.67 224	1954.00 235	1655.00 234	10117.00 251	445.00 223	5102.00 237	1375.00 230	5126.00 236	351.00 208	2638.00 244	4402.00 238	691.00 210	842.00 218
Skip Steuart: Steuart Systems R&D Blog.
DVP-MVS++		3981.10 227	4731.32 232	1730.42 225	2191.51 244	1949.98 246	16473.90 263	355.33 209	7172.90 256	1622.98 244	7879.79 254	434.33 214	2428.11 236	5762.12 245	689.04 208	813.18 214

DVP-MVS		3981.10 227	4731.32 232	1730.42 225	2191.51 244	1949.98 246	16473.90 263	355.33 209	7172.90 256	1622.98 244	7879.79 254	434.33 214	2428.11 236	5762.12 245	689.04 208	813.18 214
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
DPM-MVS		3268.00 217	3762.89 220	1783.33 227	1756.00 230	1806.00 242	12319.00 254	307.00 203	6319.00 245	1557.00 237	5763.00 238	302.00 202	2609.00 240	5061.00 242	482.00 198	935.00 228

OPM-MVS		3268.00 217	3762.89 220	1783.33 227	1756.00 230	1806.00 242	12319.00 254	307.00 203	6319.00 245	1557.00 237	5763.00 238	302.00 202	2609.00 240	5061.00 242	482.00 198	935.00 228
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
DeepC-MVS	3917.13 19	3155.06 216	3601.83 219	1814.72 229	2515.52 251	1941.53 245	10432.50 252	589.42 244	4789.45 231	1298.65 225	7677.31 253	578.35 227	2589.53 238	3611.78 229	923.52 232	913.10 225
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
TSAR-MVS + MP.		3528.01 220	4065.89 227	1914.35 230	2349.10 247	2141.30 251	12362.70 256	417.60 222	6717.80 251	1759.40 248	6497.50 241	518.18 221	2629.38 243	5164.32 244	806.40 225	972.38 233
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	3146.67 215	3537.00 218	1975.67 231	2310.00 246	2005.00 249	10100.00 250	626.00 248	5753.00 238	1803.00 249	5179.00 237	487.00 218	2622.00 242	4550.00 239	1025.00 244	1300.00 248

MVS_111021_HR		3742.80 225	4330.34 228	1980.20 232	2484.31 250	2259.52 253	14973.80 261	515.90 242	6500.13 248	1949.21 251	6146.89 240	535.66 224	2593.66 239	4880.76 241	986.37 234	1087.43 242

EGC-MVSNET		2819.75 212	3096.89 215	1988.33 233	3105.00 263	2241.00 252	9480.00 242	640.00 249	4209.00 224	1583.00 239	4740.00 230	547.00 225	2797.00 246	2644.00 219	924.00 233	927.00 227

Vis-MVSNet		2877.42 213	3170.00 216	1999.67 234	1673.00 223	2042.00 250	8593.00 235	474.00 227	6452.00 247	1268.00 224	5125.00 235	339.00 206	3004.00 248	4222.00 237	384.00 195	953.00 230
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
ITE_SJBPF				2014.00 235	1998.00 236	1992.00 248		701.00 251	5989.00 239	1812.00 250	3612.00 220	650.00 234	2852.00 247	4601.00 240	1195.00 250	1198.00 247

TAPA-MVS	6309.84 21	3374.90 219	3806.99 222	2078.63 236	2535.47 252	2499.25 260	8816.16 236	456.05 225	6255.60 244	1664.52 247	6704.88 243	629.95 233	2768.38 245	6343.93 256	856.35 228	968.25 232
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
MSC_two_6792asdad				2237.56 237	2643.17 253	2465.14 255		493.26 230					3088.29 253	6075.14 252	1078.39 245	1159.26 243

No_MVS				2237.56 237	2643.17 253	2465.14 255		493.26 230					3088.29 253	6075.14 252	1078.39 245	1159.26 243

SED-MVS		4062.74 230	4671.13 231	2237.56 237	2643.17 253	2465.14 255	13996.40 258	493.26 230	7619.38 259	2107.24 252	7416.93 250	610.24 230	3088.29 253	6075.14 252	1078.39 245	1159.26 243

GST-MVS		4000.00 229	4533.33 230	2400.00 240	2400.00 249	2400.00 254	7200.00 223	2400.00 272	7200.00 258	2400.00 260	7200.00 248	2400.00 266	2400.00 235	7200.00 258	2400.00 263	2400.00 262

tpm2		3617.85 221	4007.23 223	2449.73 241	2012.71 237	1698.05 236	7351.19 224	869.29 256	6132.06 240	1588.28 240	8007.42 256	1281.09 262	3888.11 260	7472.04 260	1351.00 251	1763.02 257

tpm cat1		3617.85 221	4007.23 223	2449.73 241	2012.71 237	1698.05 236	7351.19 224	869.29 256	6132.06 240	1588.28 240	8007.42 256	1281.09 262	3888.11 260	7472.04 260	1351.00 251	1763.02 257

CostFormer		3617.85 221	4007.23 223	2449.73 241	2012.71 237	1698.05 236	7351.19 224	869.29 256	6132.06 240	1588.28 240	8007.42 256	1281.09 262	3888.11 260	7472.04 260	1351.00 251	1763.02 257

tpm		3617.85 221	4007.23 223	2449.73 241	2012.71 237	1698.05 236	7351.19 224	869.29 256	6132.06 240	1588.28 240	8007.42 256	1281.09 262	3888.11 260	7472.04 260	1351.00 251	1763.02 257

OPU-MVS				2451.45 245	2725.60 258	2598.35 261	9203.30 238				6894.28 244	887.23 248	3023.43 249	5973.88 248	1620.04 257	1732.56 253

MSP-MVS		4296.20 231	4911.12 235	2451.45 245	2725.60 258	2598.35 261	16203.30 262	515.86 238	7016.02 252	2363.85 256	6894.28 244	887.23 248	3023.43 249	5973.88 248	1620.04 257	1732.56 253
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
MAR-MVS		3973.16 226	4387.92 229	2728.86 247	3345.27 264	3341.39 267	11403.90 253	798.76 253	6555.62 250	2569.29 261	6514.86 242	834.97 247	3237.43 257	5891.08 247	1577.54 256	1607.76 249
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		4380.83 232	4906.56 234	2803.67 248	3844.00 265	3116.00 266	13454.00 257	901.00 260	6511.00 249	2794.00 262	7365.00 249	754.00 244	3634.00 258	6622.00 257	1914.00 262	1661.00 252

OMC-MVS		5022.26 233	5748.82 236	2842.58 249	4905.27 267	3101.27 265	14933.60 260	812.24 254	9278.40 263	2959.29 263	8800.17 260	1092.24 260	3806.30 259	7568.54 264	1389.60 255	1620.18 251

CLD-MVS		7338.25 234	8341.00 237	4330.00 250	4902.00 266	4991.00 268	23318.00 266	728.00 252	14437.00 273	4378.00 265	13379.00 268	824.00 246	5708.00 264	11429.00 273	1674.00 261	2291.00 261
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
LS3D		7684.71 235	8776.23 238	4410.16 251	5298.55 268	5631.53 269	34329.90 268	1504.57 270	11554.00 272	3896.41 264	15111.00 269	812.19 245	5985.63 265	3516.20 228	2963.23 264	1613.31 250

CNLPA		10738.67 244	11772.44 247	7637.33 252	9120.00 270	8206.00 270	22252.00 265	2010.00 271	24984.00 274	7458.00 267	22596.00 271	2940.00 267	10260.00 273	11100.00 272	3492.00 265	4446.00 263

ZNCC-MVS		9999.00 236	9999.00 239	9999.00 253	9999.00 271	9999.00 272	9999.00 243	9999.00 276	9999.00 264	9999.00 268	9999.00 261	9999.00 269	9999.00 266	9999.00 265	9999.00 267	9999.00 265

patch_mono-2		10000.00 237	10000.00 240	10000.00 254	10000.00 272	10000.00 273	10000.00 244	10000.00 277	10000.00 265	10000.00 269	10000.00 262	10000.00 270	10000.00 267	10000.00 266	10000.00 268	10000.00 266

dcpmvs_2		10000.00 237	10000.00 240	10000.00 254	10000.00 272	10000.00 273	10000.00 244	10000.00 277	10000.00 265	10000.00 269	10000.00 262	10000.00 270	10000.00 267	10000.00 266	10000.00 268	10000.00 266

DCPMVS		10000.00 237	10000.00 240	10000.00 254	10000.00 272	10000.00 273	10000.00 244	10000.00 277	10000.00 265	10000.00 269	10000.00 262	10000.00 270	10000.00 267	10000.00 266	10000.00 268	10000.00 266

UA-Net		10000.00 237	10000.00 240	10000.00 254	10000.00 272	10000.00 273	10000.00 244	10000.00 277	10000.00 265	10000.00 269	10000.00 262	10000.00 270	10000.00 267	10000.00 266	10000.00 268	10000.00 266

uncertanet		10000.00 237	10000.00 240	10000.00 254	10000.00 272	10000.00 273	10000.00 244	10000.00 277	10000.00 265	10000.00 269	10000.00 262	10000.00 270	10000.00 267	10000.00 266	10000.00 268	10000.00 266

uanet		10000.00 237	10000.00 240	10000.00 254	10000.00 272	10000.00 273	10000.00 244	10000.00 277	10000.00 265	10000.00 269	10000.00 262	10000.00 270	10000.00 267	10000.00 266	10000.00 268	10000.00 266

MVE	10021.00 22	10550.67 243	10002.44 246	12195.33 260	6242.00 269	8768.00 271	30896.00 267	4451.00 273	10331.00 271	6247.00 266	18296.00 270	283.00 199	21484.00 274	7364.00 259	5912.00 266	6334.00 264
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
LTVRE_ROB	20565.47 23	23378.08 245	22805.00 248	25097.33 261	15500.00 278	19201.00 279	42712.00 269	6055.00 274	38388.00 275	16926.00 275	38534.00 272	7071.00 268	35653.00 275	29475.00 274	10584.00 274	20438.00 273
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		32606.17 246	34443.44 249	27094.33 262	29249.00 279	25246.00 280	51144.00 270	6705.00 275	42886.00 276	22888.00 276	48534.00 273	13263.00 276	37507.00 276	79298.00 275	16024.00 275	18530.00 272

114514_t		99999.00 247	99999.00 250	99999.00 263	99999.00 280	99999.00 281	99999.00 271	99999.00 283	99999.00 277	99999.00 277	99999.00 274	99999.00 277	99999.00 277	99999.00 276	99999.00 276	99999.00 274

PHI-MVS		99999.00 247	99999.00 250	99999.00 263	99999.00 280	99999.00 281	99999.00 271	99999.00 283	99999.00 277	99999.00 277	99999.00 274	99999.00 277	99999.00 277	99999.00 276	99999.00 276	99999.00 274

XVG-OURS-SEG-HR		999999.00 251	999999.00 252	999999.00 265	999999.00 282	999999.00 283	999999.00 273	999999.00 285	999999.00 279	999999.00 279	999999.00 276	999999.00 279	999999.00 279	999999.00 278	999999.00 278	999999.00 276

XVG-OURS		999999.00 251	999999.00 252	999999.00 265	999999.00 282	999999.00 283	999999.00 273	999999.00 285	999999.00 279	999999.00 279	999999.00 276	999999.00 279	999999.00 279	999999.00 278	999999.00 278	999999.00 276

XVG-ACMP-BASELINE		999999.00 251	999999.00 252	999999.00 265	999999.00 282	999999.00 283	999999.00 273	999999.00 285	999999.00 279	999999.00 279	999999.00 276	999999.00 279	999999.00 279	999999.00 278	999999.00 278	999999.00 276

iter_conf_final		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

bld_raw_dy_0_64		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

test2506		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

test1111		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

ECVR-MVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

test_blank		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

tt0805		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

Anonymous20240521		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

cl22		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

miper_ehance_all_eth		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

miper_enhance_ethall		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

cl____		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

DIV-MVS_self_test		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

eth_miper_zixun_eth		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

ET-MVSNet_ETH3D		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

UniMVSNet_ETH3D		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

miper_lstm_enhance		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

D2MVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

test_yl		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

thisisatest0530		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

Anonymous20240529		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

Anonymous202405211		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

DCV-MVSNet		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

tttt0517		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

our_test_3		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

thisisatest0515		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

ppachtmachnet_test		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

SMA-MVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279
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		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
thres100view900		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

tfpnnormal		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

tfpn200view9		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

c3_l		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

IterMVS-SCA-FT		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

pmmvs6		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

pmmvs5		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

Anonymous20231211		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

pmmvs-eth3d		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

Anonymous20231206		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

SCA		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

Patchmatch-test		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

Patchmatch-RL test		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

canonicalmvs		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

anonymousdsp		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

FIs		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

FC-MVSNet-test		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

sosnet-low-res		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

AllTest		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

TestCases				10000000.00 268	10000000.00 285	10000000.00 286		10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

iter_conf05		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

RRT_MVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

HPM-MVS++		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

XVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

pm-mvs1		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

X-MVStestdata		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

APDe-MVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

APD-MVS_3200maxsize		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

pmmvs4		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

test-LLR		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

TESTMET0.1,1		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

test-mter		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

testgi		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

test20.03		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

thres600view7		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

MP-MVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

thres400		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

test123		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

thres200		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

test0.0.03 1		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

pmmvs3		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

EMVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

E-PMN		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

PGM-MVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

MCST-MVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

MVS_Test		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

PMMVS2		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

PM-MVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

HQP_MVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

mPP-MVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

mvsmamba		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

HPM-MVS_fast		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

HPM-MVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
LPG-MVS_test		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

LGP-MVS_train				10000000.00 268	10000000.00 285	10000000.00 286		10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

EPNet_dtu		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

NCCC		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

CP-MVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

CPTT-MVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

HQP-MVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

IS-MVSNet		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

PAPM_NR		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

PAPR		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

Vis-MVSNet (Re-imp)		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

PatchMatch-RL		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

TDRefinement		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

EPP-MVSNet		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

PMMVS		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

PAPM		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

ACMMP		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279
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		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

wuyk23d		10000000.00 254	10000000.00 257	10000000.00 268	10000000.00 285	10000000.00 286	10000000.00 276	10000000.00 288	10000000.00 282	10000000.00 282	10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

APD-MVS		1000000000.00 356	1000000000.00 359	1000000000.00 372	1000000000.00 397	1000000000.00 396	1000000000.00 383	1000000000.00 397	1000000000.00 390	1000000000.00 391	1000000000.00 388	1000000000.00 393	1000000000.00 391	1000000000.00 389	1000000000.00 389	1000000000.00 387
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
FOURS1					2643.17 253	2465.14 255	13996.40 258	493.26 230	7619.38 259	2107.24 252

PC_three_1452									7619.38 259	2107.24 252	7416.93 250	610.24 230	3088.29 253	6075.14 252	1078.39 245	1159.26 243

test_one_0601					2643.17 253	2465.14 255		493.26 230	7619.38 259	2107.24 252	7416.93 250	610.24 230

eth-test2					1.42 70

eth-test					10000000.00 285

ZD-MVS					1584.00 222	1821.00 244		378.00 214	3721.00 220	1231.00 221	1833.00 202	321.00 204	1224.00 214	2103.00 214	692.00 211

RE-MVS-def			610.10 154		610.10 180	610.10 192	610.10 156	610.10 245	610.10 162	610.10 192	610.10 159	610.10 228		610.10 163	610.10 201	610.10 199

IU-MVS					2725.60 258	2598.35 261		515.86 238	7016.02 252	2363.85 256				5973.88 248	1620.04 257	1732.56 253

test_241102_TWO								515.86 238	7016.02 252	2363.85 256	6894.28 244	887.23 248	3023.43 249	5973.88 248	1620.04 257	1732.56 253

test_241102_ONE					2725.60 258	2598.35 261		515.86 238	7016.02 252	2363.85 256	6894.28 244	887.23 248	3023.43 249

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									5016.02 234	1363.85 226	4894.28 232	387.23 211	2023.43 227	3973.88 231	620.04 203	732.56 208

test0726					1725.60 225	1598.35 228	9203.30 238	315.86 205	5016.02 234	1363.85 226	4894.28 232	387.23 211

GSMVS																10000000.00 279

test_part2					10000000.00 285	10000000.00 286				10000000.00 282

sam_mvs1												10000000.00 282				10000000.00 279

sam_mvs												10000000.00 282

MTGPA								10000000.00 288

test_post1							10000000.00 276				10000000.00 279	10000000.00 282	10000000.00 282	10000000.00 281

test_post											10000000.00 279	10000000.00 282	10000000.00 282

patchmatchnet-post											10000000.00 279	10000000.00 282	10000000.00 282

MTMP							10000000.00 276	10000000.00 288

gm-plane-assit					611.29 182	600.33 189			579.21 158		567.40 154		531.67 170	503.93 157

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

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

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

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

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

testdata1							0.00 1		0.00 1

plane_prior7					10000000.00 285	10000000.00 286

plane_prior6					10000000.00 285	10000000.00 286						10000000.00 282

plane_prior5								10000000.00 288					10000000.00 282	10000000.00 281	10000000.00 281	10000000.00 279

plane_prior4											10000000.00 279

plane_prior3						10000000.00 286			10000000.00 282	10000000.00 282

plane_prior2							10000000.00 276		10000000.00 282

plane_prior1					10000000.00 285

plane_prior						1.00 64	2.00 92		2.00 93						2.00 91

n2								14.20 134

nn								1.42 72

door-mid								1.42 72

test11								1.00 65

door								99.00 169

HQP5-MVS						10000000.00 286

HQP-NCC					10000000.00 285		10000000.00 276		10000000.00 282	10000000.00 282

ACMP_Plane					10000000.00 285		10000000.00 276		10000000.00 282	10000000.00 282

BP-MVS														10000000.00 281

HQP4-MVS										10000000.00 282			10000000.00 282			10000000.00 279

HQP3-MVS								10000000.00 288							10000000.00 281

HQP2-MVS												10000000.00 282

NP-MVS					10000000.00 285	10000000.00 286					10000000.00 279

MDTV_nov1_ep13_2view						9.99 114	9.99 112		9.99 113	9.99 112		9.99 114		9.99 110		9.99 113

MDTV_nov1_ep13			9.99 100		9.99 113	9.99 114	9.99 112	9.99 120	9.99 113	9.99 112	9.99 109	9.99 114	9.99 113	9.99 110	9.99 114

ACMMP++_ref															10000000.00 281

ACMMP++															10000000.00 281

Test By Simon												990.00 252

High-resolution multi-view benchmark