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.

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_prior3		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

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

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

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

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

test_prior4						0.00 1	0.00 1

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

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

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

testdata1							0.00 1		0.00 1

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

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

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

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

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

LCM-MVSNet		0.37 13	0.36 13	0.37 18	0.37 23	0.37 24	0.37 23	0.32 24	0.37 23	0.37 23	0.37 21	0.37 23	0.37 24	0.37 22	0.37 22	0.37 23

v144192		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v1921920		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v1192		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v1144		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v148		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v748		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v7n		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v1141		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v1neww		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v7new		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v1240		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v18		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v17		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v16		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

divwei89l23v2f112		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v15		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v13		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v12		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v8		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v7		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v6		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v11		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v52		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

V14		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v10		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

V4		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v2v482		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

v1		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

V42		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

V9		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

GA-MVS		0.40 14	0.40 14	0.40 19	0.40 24	0.40 25	0.40 24	0.40 26	0.40 24	0.40 24	0.40 22	0.40 24	0.40 25	0.40 23	0.40 23	0.40 24

Fast-Effi-MVS+		0.41 45	0.40 14	0.41 50	0.41 55	0.41 56	0.41 55	0.35 25	0.41 55	0.41 55	0.41 53	0.41 55	0.41 56	0.41 54	0.41 54	0.41 55

Fast-Effi-MVS+-dtu		0.44 46	0.44 46	0.44 51	0.44 56	0.44 57	0.44 56	0.44 57	0.44 56	0.44 56	0.44 54	0.44 56	0.44 57	0.44 55	0.44 55	0.44 56

Effi-MVS+-dtu		0.59 48	0.61 48	0.53 52	0.68 58	0.53 58	0.53 57	0.68 59	0.68 58	0.53 57	0.53 55	0.68 58	0.53 58	0.68 57	0.53 56	0.53 57

Effi-MVS+		0.58 47	0.56 47	0.62 53	0.53 57	0.62 59	0.53 57	0.53 58	0.53 57	0.62 58	0.62 56	0.53 57	0.62 59	0.62 56	0.53 56	0.62 58

mvs-test1		0.68 49	0.68 49	0.68 54	0.68 58	0.68 60	0.68 59	0.68 59	0.68 58	0.68 59	0.68 57	0.68 58	0.68 60	0.68 57	0.68 58	0.68 59

CDS-MVSNet		0.88 50	0.88 50	0.88 55	0.88 60	0.88 61	0.88 60	0.88 61	0.88 60	0.88 60	0.88 58	0.88 60	0.88 61	0.88 59	0.88 59	0.88 60
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		0.88 50	0.88 50	0.88 55	0.88 60	0.88 61	0.88 60	0.88 61	0.88 60	0.88 60	0.88 58	0.88 60	0.88 61	0.88 59	0.88 59	0.88 60

LCM-MVSNet-Re		0.89 52	0.89 52	0.89 57	0.89 62	0.89 63	0.89 62	0.89 63	0.89 62	0.89 62	0.89 60	0.89 62	0.89 63	0.89 61	0.89 61	0.89 62

MDA-MVSNet-bldmvs		1.20 53	1.20 53	1.20 59	1.20 64	1.20 66	1.20 63	1.20 66	1.20 64	1.20 64	1.20 62	1.20 64	1.20 65	1.20 63	1.20 63	1.20 64

YYNet1		1.20 53	1.20 53	1.20 59	1.20 64	1.20 66	1.20 63	1.20 66	1.20 64	1.20 64	1.20 62	1.20 64	1.20 65	1.20 63	1.20 63	1.20 64

MDA-MVSNet_test_wron		1.20 53	1.20 53	1.20 59	1.20 64	1.20 66	1.20 63	1.20 66	1.20 64	1.20 64	1.20 62	1.20 64	1.20 65	1.20 63	1.20 63	1.20 64

EI-MVSNet-UG-set		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

EI-MVSNet-Vis-set		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

Regformer-3		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

Regformer-4		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

Regformer-1		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

Regformer-2		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

EI-MVSNet		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

Regformer		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

CVMVSNet		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

EU-MVSNet		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

PS-CasMVS		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

UniMVSNet_NR-MVSNet		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

PEN-MVS		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

TransMVSNet (Re)		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

DTE-MVSNet		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

DU-MVS		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

UniMVSNet (Re)		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

CP-MVSNet		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

WR-MVS_H		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

WR-MVS		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

NR-MVSNet		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

Baseline_NR-MVSNet		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

TranMVSNet+NR-MVSNet		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

MVSFormer		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

jason		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67
jason: jason.
lupinMVS		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

test_djsdf		1.42 56	1.42 56	1.42 62	1.42 67	1.42 69	1.42 66	1.42 69	1.42 67	1.42 67	1.42 65	1.42 67	1.42 68	1.42 66	1.42 66	1.42 67

alignmvs		2.00 83	2.00 83	2.00 89	2.00 94	2.00 96	2.00 93	2.00 98	2.00 94	2.00 94	2.00 92	2.00 94	2.00 95	2.00 93	2.00 93	2.00 94

nrg030		2.00 83	2.00 83	2.00 89	2.00 94	2.00 96	2.00 93	2.00 98	2.00 94	2.00 94	2.00 92	2.00 94	2.00 95	2.00 93	2.00 93	2.00 94

LFMVS		2.00 83	2.00 83	2.00 89	2.00 94	2.00 96	2.00 93	2.00 98	2.00 94	2.00 94	2.00 92	2.00 94	2.00 95	2.00 93	2.00 93	2.00 94

VDD-MVS		2.00 83	2.00 83	2.00 89	2.00 94	2.00 96	2.00 93	2.00 98	2.00 94	2.00 94	2.00 92	2.00 94	2.00 95	2.00 93	2.00 93	2.00 94

VDDNet		2.00 83	2.00 83	2.00 89	2.00 94	2.00 96	2.00 93	2.00 98	2.00 94	2.00 94	2.00 92	2.00 94	2.00 95	2.00 93	2.00 93	2.00 94

VPNet		2.00 83	2.00 83	2.00 89	2.00 94	2.00 96	2.00 93	2.00 98	2.00 94	2.00 94	2.00 92	2.00 94	2.00 95	2.00 93	2.00 93	2.00 94

VNet		2.00 83	2.00 83	2.00 89	2.00 94	2.00 96	2.00 93	2.00 98	2.00 94	2.00 94	2.00 92	2.00 94	2.00 95	2.00 93	2.00 93	2.00 94

VPA-MVSNet		2.00 83	2.00 83	2.00 89	2.00 94	2.00 96	2.00 93	2.00 98	2.00 94	2.00 94	2.00 92	2.00 94	2.00 95	2.00 93	2.00 93	2.00 94

plane_prior						1.00 64	2.00 93		2.00 94						2.00 93

cascas		2.00 83	2.00 83	2.00 89	2.00 94	2.00 96	2.00 93	2.00 98	2.00 94	2.00 94	2.00 92	2.00 94	2.00 95	2.00 93	2.00 93	2.00 94

UnsupCasMVSNet_eth		5.90 92	5.90 92	5.90 98	5.90 103	5.90 105	5.90 103	5.90 108	5.90 104	5.90 103	5.90 101	5.90 104	5.90 104	5.90 102	5.90 104	5.90 104

UnsupCasMVSNet_bld		5.90 92	5.90 92	5.90 98	5.90 103	5.90 105	5.90 103	5.90 108	5.90 104	5.90 103	5.90 101	5.90 104	5.90 104	5.90 102	5.90 104	5.90 104

WTY-MVS		5.90 92	5.90 92	5.90 98	5.90 103	5.90 105	5.90 103	5.90 108	5.90 104	5.90 103	5.90 101	5.90 104	5.90 104	5.90 102	5.90 104	5.90 104

HY-MVS	5.90 1	5.90 92	5.90 92	5.90 98	5.90 103	5.90 105	5.90 103	5.90 108	5.90 104	5.90 103	5.90 101	5.90 104	5.90 104	5.90 102	5.90 104	5.90 104

sss		5.90 92	5.90 92	5.90 98	5.90 103	5.90 105	5.90 103	5.90 108	5.90 104	5.90 103	5.90 101	5.90 104	5.90 104	5.90 102	5.90 104	5.90 104

Test_1112_low_res		5.90 92	5.90 92	5.90 98	5.90 103	5.90 105	5.90 103	5.90 108	5.90 104	5.90 103	5.90 101	5.90 104	5.90 104	5.90 102	5.90 104	5.90 104

1112_ss		5.90 92	5.90 92	5.90 98	5.90 103	5.90 105	5.90 103	5.90 108	5.90 104	5.90 103	5.90 101	5.90 104	5.90 104	5.90 102	5.90 104	5.90 104

ab-mvs-re		5.90 92	5.90 92	5.90 98	5.90 103	5.90 105	5.90 103	5.90 108	5.90 104	5.90 103	5.90 101	5.90 104	5.90 104	5.90 102	5.90 104	5.90 104

ab-mvs		5.90 92	5.90 92	5.90 98	5.90 103	5.90 105	5.90 103	5.90 108	5.90 104	5.90 103	5.90 101	5.90 104	5.90 104	5.90 102	5.90 104	5.90 104

CDPH-MVS		6.66 101	6.66 101	6.66 107	6.66 112	6.66 114	6.66 112	6.66 117	6.66 113	6.66 112	6.66 110	6.66 113	6.66 113	6.66 111	6.66 113	6.66 113

MDTV_nov1_ep13_2view						9.99 116	9.99 113		9.99 114	9.99 114		9.99 114		9.99 112		9.99 114

MDTV_nov1_ep13			9.99 102		9.99 113	9.99 116	9.99 113	9.99 119	9.99 114	9.99 114	9.99 111	9.99 114	9.99 115	9.99 112	9.99 114

xiu_mvs_v1_base_debu		10.28 102	10.28 103	10.28 109	10.28 114	10.28 118	10.28 115	10.28 120	10.28 116	10.28 116	10.28 112	10.28 116	10.28 116	10.28 114	10.28 115	10.28 115

xiu_mvs_v2_base		10.28 102	10.28 103	10.28 109	10.28 114	10.28 118	10.28 115	10.28 120	10.28 116	10.28 116	10.28 112	10.28 116	10.28 116	10.28 114	10.28 115	10.28 115

xiu_mvs_v1_base		10.28 102	10.28 103	10.28 109	10.28 114	10.28 118	10.28 115	10.28 120	10.28 116	10.28 116	10.28 112	10.28 116	10.28 116	10.28 114	10.28 115	10.28 115

xiu_mvs_v1_base_debi		10.28 102	10.28 103	10.28 109	10.28 114	10.28 118	10.28 115	10.28 120	10.28 116	10.28 116	10.28 112	10.28 116	10.28 116	10.28 114	10.28 115	10.28 115

cdsmvs_eth3d_5k		10.28 102	10.28 103	10.28 109	10.28 114	10.28 118	10.28 115	10.28 120	10.28 116	10.28 116	10.28 112	10.28 116	10.28 116	10.28 114	10.28 115	10.28 115

pcd_1.5k_mvsjas		10.28 102	10.28 103	10.28 109	10.28 114	10.28 118	10.28 115	10.28 120	10.28 116	10.28 116	10.28 112	10.28 116	10.28 116	10.28 114	10.28 115	10.28 115

pcd1.5k->3k		10.28 102	10.28 103	10.28 109	10.28 114	10.28 118	10.28 115	10.28 120	10.28 116	10.28 116	10.28 112	10.28 116	10.28 116	10.28 114	10.28 115	10.28 115

PS-MVSNAJss		10.28 102	10.28 103	10.28 109	10.28 114	10.28 118	10.28 115	10.28 120	10.28 116	10.28 116	10.28 112	10.28 116	10.28 116	10.28 114	10.28 115	10.28 115

PS-MVSNAJ		10.28 102	10.28 103	10.28 109	10.28 114	10.28 118	10.28 115	10.28 120	10.28 116	10.28 116	10.28 112	10.28 116	10.28 116	10.28 114	10.28 115	10.28 115

jajsoiax		10.28 102	10.28 103	10.28 109	10.28 114	10.28 118	10.28 115	10.28 120	10.28 116	10.28 116	10.28 112	10.28 116	10.28 116	10.28 114	10.28 115	10.28 115

mvs_tets		10.28 102	10.28 103	10.28 109	10.28 114	10.28 118	10.28 115	10.28 120	10.28 116	10.28 116	10.28 112	10.28 116	10.28 116	10.28 114	10.28 115	10.28 115

XXY-MVS		15.00 113	15.00 114	15.00 120	15.00 126	15.00 129	15.00 126	15.00 134	15.00 127	15.00 127	15.00 123	15.00 132	15.00 127	15.00 126	15.00 127	15.00 127

BH-w/o		40.00 114	40.00 115	40.00 122	40.00 127	40.00 130	40.00 127	40.00 151	40.00 128	40.00 129	40.00 124	40.00 150	40.00 129	40.00 127	40.00 143	40.00 139

BH-untuned		40.00 114	40.00 115	40.00 122	40.00 127	40.00 130	40.00 127	40.00 151	40.00 128	40.00 129	40.00 124	40.00 150	40.00 129	40.00 127	40.00 143	40.00 139

BH-RMVSNet		40.00 114	40.00 115	40.00 122	40.00 127	40.00 130	40.00 127	40.00 151	40.00 128	40.00 129	40.00 124	40.00 150	40.00 129	40.00 127	40.00 143	40.00 139

TR-MVS		40.00 114	40.00 115	40.00 122	40.00 127	40.00 130	40.00 127	40.00 151	40.00 128	40.00 129	40.00 124	40.00 150	40.00 129	40.00 127	40.00 143	40.00 139

GBi-Net		44.67 118	49.24 119	30.96 121	47.53 131	47.57 134	126.09 131	8.00 118	76.99 132	26.09 128	73.50 129	11.27 127	30.55 128	61.12 131	12.58 126	14.75 126

DSMNet-mixed		131.33 134	143.00 135	96.33 146	99.00 142	81.00 145	201.00 132	45.00 155	335.00 153	99.00 153	251.00 149	38.00 149	110.00 151	120.00 135	99.00 152	98.00 152

new_pmnet		88.14 120	98.62 120	56.70 126	98.14 140	56.07 135	246.79 133	15.37 135	148.06 133	50.77 133	143.13 130	23.35 133	62.65 133	93.26 132	68.71 150	51.38 150

N_pmnet		88.14 120	98.62 120	56.70 126	98.14 140	56.07 135	246.79 133	15.37 135	148.06 133	50.77 133	143.13 130	23.35 133	62.65 133	93.26 132	68.71 150	51.38 150

MP-MVS-pluss		833433.63 235	1111219.60 239	75.70 134	74.28 134	73.29 139	284.50 135	11.35 131	238.58 141	65.86 137	255.35 150	14.55 130	115.69 152	10000000.00 257	31.94 130	38.12 137
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
ACMMP_Plus		118.81 126	133.18 127	75.70 134	74.28 134	73.29 139	284.50 135	11.35 131	238.58 141	65.86 137	255.35 150	14.55 130	115.69 152	222.18 152	31.94 130	38.12 137

zzz-MVS		833442.10 236	1111233.77 240	67.09 128	65.59 132	64.81 137	284.50 135	10000000.00 261	219.97 139	59.62 135	229.89 144	12.72 128	103.00 149	203.67 150	27.93 128	33.46 128

MTAPA		833442.10 236	1111233.77 240	67.09 128	65.59 132	64.81 137	284.50 135	10000000.00 261	219.97 139	59.62 135	229.89 144	12.72 128	103.00 149	203.67 150	27.93 128	33.46 128

dp		87.20 119	113.80 122	7.42 108	10.50 125	8.88 115	298.82 139	2.70 107	510.35 155	7.79 113	172.93 132	3.37 103	9.16 114	14.00 125	3.71 103	4.23 103

CANet		110.62 122	124.04 123	70.34 130	82.03 136	74.27 141	325.54 140	25.25 137	207.16 135	69.28 139	194.38 133	27.53 135	95.79 142	147.76 136	37.43 132	40.97 143

CANet_DTU		110.62 122	124.04 123	70.34 130	82.03 136	74.27 141	325.54 140	25.25 137	207.16 135	69.28 139	194.38 133	27.53 135	95.79 142	147.76 136	37.43 132	40.97 143

MVS_0304		110.62 122	124.04 123	70.34 130	82.03 136	74.27 141	325.54 140	25.25 137	207.16 135	69.28 139	194.38 133	27.53 135	95.79 142	147.76 136	37.43 132	40.97 143

UGNet		110.62 122	124.04 123	70.34 130	82.03 136	74.27 141	325.54 140	25.25 137	207.16 135	69.28 139	194.38 133	27.53 135	95.79 142	147.76 136	37.43 132	40.97 143
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		124.76 127	140.93 128	76.26 136	107.44 143	100.17 149	329.88 144	27.12 144	259.44 146	74.30 143	204.34 137	30.74 139	92.41 135	196.98 140	38.15 136	36.19 130

test1		124.76 127	140.93 128	76.26 136	107.44 143	100.17 149	329.88 144	27.12 144	259.44 146	74.30 143	204.34 137	30.74 139	92.41 135	196.98 140	38.15 136	36.19 130

FMVSNet3		124.76 127	140.93 128	76.26 136	107.44 143	100.17 149	329.88 144	27.12 144	259.44 146	74.30 143	204.34 137	30.74 139	92.41 135	196.98 140	38.15 136	36.19 130

FMVSNet2		124.76 127	140.93 128	76.26 136	107.44 143	100.17 149	329.88 144	27.12 144	259.44 146	74.30 143	204.34 137	30.74 139	92.41 135	196.98 140	38.15 136	36.19 130

FMVSNet1		124.76 127	140.93 128	76.26 136	107.44 143	100.17 149	329.88 144	27.12 144	259.44 146	74.30 143	204.34 137	30.74 139	92.41 135	196.98 140	38.15 136	36.19 130

MIMVSNet1		124.76 127	140.93 128	76.26 136	107.44 143	100.17 149	329.88 144	27.12 144	259.44 146	74.30 143	204.34 137	30.74 139	92.41 135	196.98 140	38.15 136	36.19 130

MIMVSNet		124.76 127	140.93 128	76.26 136	107.44 143	100.17 149	329.88 144	27.12 144	259.44 146	74.30 143	204.34 137	30.74 139	92.41 135	196.98 140	38.15 136	36.19 130

PVSNet_Blended_VisFu		136.90 135	155.40 136	81.40 143	111.00 150	96.20 146	407.00 151	25.90 141	251.60 143	85.10 150	240.50 146	37.00 146	99.90 146	199.80 147	40.70 147	48.10 147

PVSNet_BlendedMVS		136.90 135	155.40 136	81.40 143	111.00 150	96.20 146	407.00 151	25.90 141	251.60 143	85.10 150	240.50 146	37.00 146	99.90 146	199.80 147	40.70 147	48.10 147

PVSNet_Blended		136.90 135	155.40 136	81.40 143	111.00 150	96.20 146	407.00 151	25.90 141	251.60 143	85.10 150	240.50 146	37.00 146	99.90 146	199.80 147	40.70 147	48.10 147

JIA-IIPM		804.30 164	835.64 158	710.26 188	885.90 195	895.90 204	455.98 154	668.73 227	1297.17 180	1002.26 208	1001.67 177	655.98 223	756.98 188	667.90 167	885.21 219	477.90 194

RPMNet		804.30 164	835.64 158	710.26 188	885.90 195	895.90 204	455.98 154	668.73 227	1297.17 180	1002.26 208	1001.67 177	655.98 223	756.98 188	667.90 167	885.21 219	477.90 194

gg-mvs-nofinetune		594.69 151	605.37 152	562.67 176	617.29 182	500.33 175	772.30 156	413.12 210	579.21 156	552.71 182	567.40 153	662.54 225	531.67 170	503.93 156	779.80 207	656.02 198

GG-mvs-BLEND				596.01 179	611.29 178	600.33 186	790.30 157	513.12 220		552.71 182	567.40 153	662.54 225	531.67 170	503.93 156	779.80 207	656.02 198

CR-MVSNet		612.36 152	617.81 153	596.01 179	611.29 178	600.33 186	790.30 157	513.12 220	579.21 156	552.71 182	567.40 153	662.54 225	531.67 170	503.93 156	779.80 207	656.02 198

PatchT		856.34 168	860.99 162	842.38 194	1290.90 209	880.90 202	790.30 157	1267.30 246	579.21 156	923.90 199	567.40 153	662.54 225	990.23 197	887.56 175	779.80 207	656.02 198

DP-MVS		264.78 138	296.02 139	171.04 147	191.70 153	183.96 156	827.10 160	78.36 157	438.24 154	176.64 154	435.12 152	65.04 155	230.52 156	334.02 153	117.96 153	98.64 153

ambc				999.00 195	999.00 200	999.00 206	999.00 161	999.00 240		999.00 202	999.00 171	999.00 235	999.00 199	999.00 180	999.00 225	999.00 224

OurMVSNet-221017-0		999.00 174	999.00 171	999.00 195	999.00 200	999.00 206	999.00 161	999.00 240	999.00 170	999.00 202	999.00 171	999.00 235	999.00 199	999.00 180	999.00 225	999.00 224

EPMVS		999.00 174	999.00 171	999.00 195	999.00 200	999.00 206	999.00 161	999.00 240	999.00 170	999.00 202	999.00 171	999.00 235	999.00 199	999.00 180	999.00 225	999.00 224

sosnet		1000.00 176	1000.00 173	1000.00 198	1000.00 203	1000.00 209	1000.00 164	1000.00 243	1000.00 172	1000.00 205	1000.00 174	1000.00 238	1000.00 202	1000.00 183	1000.00 228	1000.00 227

USDC		1000.00 176	1000.00 173	1000.00 198	1000.00 203	1000.00 209	1000.00 164	1000.00 243	1000.00 172	1000.00 205	1000.00 174	1000.00 238	1000.00 202	1000.00 183	1000.00 228	1000.00 227

TinyColmap		1000.00 176	1000.00 173	1000.00 198	1000.00 203	1000.00 209	1000.00 164	1000.00 243	1000.00 172	1000.00 205	1000.00 174	1000.00 238	1000.00 202	1000.00 183	1000.00 228	1000.00 227

LP		495.57 147	552.82 148	323.82 157	377.78 162	343.94 163	1099.61 167	67.44 156	1450.39 185	417.42 168	790.39 162	130.18 168	472.61 168	519.53 160	122.60 154	154.91 156

ADS-MVSNet2		443.33 142	482.84 142	324.79 158	434.94 168	387.73 167	1110.57 168	87.69 160	887.02 166	282.92 157	779.29 160	98.57 162	422.76 165	502.40 154	162.19 161	163.87 157

ADS-MVSNet		443.33 142	482.84 142	324.79 158	434.94 168	387.73 167	1110.57 168	87.69 160	887.02 166	282.92 157	779.29 160	98.57 162	422.76 165	502.40 154	162.19 161	163.87 157

RPSCF		394.81 140	445.63 141	242.35 148	276.55 156	253.63 158	1207.27 170	90.69 162	715.56 160	241.57 156	684.87 158	111.96 165	320.02 157	548.38 161	133.81 155	153.39 155

PatchmatchNet		492.52 146	551.22 147	316.40 155	400.20 164	357.90 165	1277.10 171	115.80 171	1034.60 175	315.90 162	874.00 167	155.10 171	402.20 164	629.50 164	158.80 158	189.10 163
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
tmp_tt		371.08 139	412.78 140	246.00 149	231.00 154	197.00 157	1293.00 172	376.00 203	756.00 162	609.00 188	71.00 128	106.00 164	195.00 154	102.00 134	171.00 163	346.00 185

MVP-Stereo		473.58 144	533.67 145	293.33 151	376.00 160	318.00 160	1461.00 173	96.00 163	835.00 164	290.00 160	804.00 164	97.00 160	383.00 162	688.00 170	156.00 156	179.00 161
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MS-PatchMatch		473.58 144	533.67 145	293.33 151	376.00 160	318.00 160	1461.00 173	96.00 163	835.00 164	290.00 160	804.00 164	97.00 160	383.00 162	688.00 170	156.00 156	179.00 161

EG-PatchMatch MVS		437.03 141	493.12 144	268.77 150	264.80 155	260.20 159	1491.80 175	98.00 166	723.20 161	238.80 155	722.40 159	63.10 154	382.00 160	629.00 163	207.00 170	164.10 159

tpmvs		501.65 148	567.42 149	304.33 154	395.39 163	356.32 164	1512.04 176	216.53 195	994.15 169	350.16 165	804.16 166	119.38 166	380.98 159	555.14 162	159.87 159	175.69 160

DELS-MVS		514.57 149	587.73 151	295.12 153	343.03 157	328.09 162	1540.48 177	116.22 172	988.59 168	325.44 163	906.22 168	119.86 167	365.72 158	788.60 172	161.09 160	191.55 164
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
IB-MVS	872.44 4	616.41 154	700.96 155	362.78 160	426.10 167	409.25 169	1822.69 178	124.42 178	1186.23 178	366.85 167	1079.42 179	190.60 182	451.78 167	930.72 177	181.59 165	227.30 167
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
IterMVS		615.05 153	691.66 154	385.23 162	516.40 171	454.80 172	1863.80 179	102.10 168	1142.20 177	364.10 166	1093.20 181	135.00 169	480.40 169	826.90 173	181.20 164	220.50 166
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Gipuma		689.75 156	767.00 157	458.00 168	613.00 181	549.00 184	1943.00 180	187.00 192	1230.00 179	518.00 179	1092.00 180	203.00 188	564.00 175	892.00 176	225.00 177	261.00 172
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
DP-MVS Recon		516.25 150	581.17 150	321.48 156	361.02 158	429.00 171	1995.36 181	78.48 158	796.20 163	283.32 159	796.02 163	96.78 159	382.98 161	636.72 165	186.66 167	152.46 154

CSCG		826.03 166	963.29 169	414.24 163	421.52 166	426.11 170	2230.35 182	179.52 191	1827.44 196	733.43 197	933.12 170	281.25 195	545.23 174	1800.35 203	262.64 181	271.38 173

IterMVS-LS		758.94 157	856.56 160	466.10 169	606.60 176	546.80 182	2309.90 183	122.20 177	1402.80 183	463.50 172	1348.20 184	192.60 183	574.60 181	1028.60 187	234.60 179	276.90 174
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
new-patchmatchnet		766.12 158	859.03 161	487.38 172	595.68 173	536.14 177	2346.27 184	142.51 183	1488.08 186	422.43 169	1361.32 186	163.65 174	628.60 183	1003.74 186	207.61 171	297.41 178

mvs_anonymous		774.90 160	882.28 164	452.77 164	636.50 183	537.20 178	2348.80 185	120.30 173	1504.30 187	474.40 173	1371.10 187	186.90 177	564.70 176	1078.90 189	219.30 173	256.40 168

casdiffmvs		774.90 160	882.28 164	452.77 164	636.50 183	537.20 178	2348.80 185	120.30 173	1504.30 187	474.40 173	1371.10 187	186.90 177	564.70 176	1078.90 189	219.30 173	256.40 168

diffmvs		774.90 160	882.28 164	452.77 164	636.50 183	537.20 178	2348.80 185	120.30 173	1504.30 187	474.40 173	1371.10 187	186.90 177	564.70 176	1078.90 189	219.30 173	256.40 168

casdiffmvs1		774.90 160	882.28 164	452.77 164	636.50 183	537.20 178	2348.80 185	120.30 173	1504.30 187	474.40 173	1371.10 187	186.90 177	564.70 176	1078.90 189	219.30 173	256.40 168

Patchmtry		1090.75 180	1198.88 180	766.38 193	1290.90 209	485.90 173	2423.98 189	1267.30 246	1297.17 180	923.90 199	923.40 169	1215.54 242	990.23 197	667.90 167	779.80 207	823.02 208

PVSNet	1207.94 6	829.56 167	937.18 168	506.69 173	645.55 187	585.72 185	2477.98 190	130.52 179	1578.29 192	509.50 178	1460.01 191	194.90 184	637.19 185	1170.78 194	267.07 183	297.17 177

ACMH+	729.97 2	661.38 155	754.00 156	383.51 161	368.96 159	376.38 166	2483.74 191	82.42 159	1089.25 176	333.39 164	1219.68 182	66.53 156	573.60 180	957.86 178	184.14 166	200.56 165

SixPastTwentyTwo		773.62 159	869.37 163	486.35 171	603.45 175	547.15 183	2532.14 192	106.92 170	1434.95 184	428.08 170	1360.56 185	165.15 175	628.96 184	984.09 179	209.01 172	282.94 175

K. test v3		877.74 169	980.16 170	570.46 178	1316.85 211	813.15 199	2565.52 193	103.78 169	1509.49 191	548.33 181	1258.90 183	219.93 193	587.82 182	1102.37 193	196.30 168	310.42 180

MVSTER		890.06 170	1005.91 176	542.52 174	736.13 192	653.90 191	2616.56 194	145.22 185	1692.10 195	555.69 185	1554.72 193	266.25 194	660.02 186	1219.66 195	266.84 182	313.64 181

PVSNet_0	1661.03 9	968.54 173	1066.82 178	673.70 186	706.94 190	695.69 192	2669.02 195	153.52 187	2108.17 201	605.54 187	1679.14 194	213.26 192	886.75 194	1236.76 196	229.01 178	438.67 193

test_0402		1110.00 181	1260.00 182	660.00 183	900.00 198	780.00 198	3300.00 196	210.00 194	2040.00 200	690.00 192	1950.00 197	300.00 198	810.00 190	1620.00 200	330.00 190	390.00 191

ACMH	993.80 5	967.92 172	1106.11 179	553.33 175	494.00 170	534.00 176	3581.00 197	136.00 180	1585.00 193	478.00 177	1871.00 196	90.00 157	839.00 191	1460.00 197	260.00 180	287.00 176
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MVS_111021_LR		1136.45 182	1298.72 183	649.64 182	756.17 193	726.26 195	3785.94 198	138.15 182	2190.64 202	629.63 190	2064.39 199	165.45 176	874.83 193	1678.43 202	279.70 184	347.82 186

PMVS	863.65 3	957.08 171	1054.11 177	666.00 185	401.00 165	495.00 174	3790.00 199	279.00 197	1607.00 194	521.00 180	1745.00 195	90.00 157	1105.00 207	639.00 166	415.00 194	398.00 192
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
ACMP	1246.57 7	1086.24 179	1235.17 181	639.45 181	596.53 174	639.91 189	3904.24 200	152.04 186	1851.54 197	566.58 186	1997.95 198	138.50 170	938.30 195	1605.46 199	303.70 189	340.14 183
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
FPMVS		1407.00 188	1495.59 188	1141.23 202	648.01 188	893.85 203	4124.00 201	503.81 219	3219.04 209	742.72 198	2498.84 205	157.98 172	1727.83 213	832.93 174	732.98 206	802.00 205

MSLP-MVS++		1242.93 184	1411.08 185	738.48 191	712.71 191	712.68 193	4168.17 202	136.50 181	2276.40 203	613.28 189	2368.60 203	161.61 173	1130.38 208	1964.54 206	297.88 186	372.39 188

ACMMPR		1296.60 186	1480.82 187	743.96 192	899.25 197	763.47 197	4305.47 203	143.90 184	2530.94 206	683.99 191	2346.34 202	201.65 187	1098.25 206	1920.59 205	295.21 185	370.16 187

ACMM	1311.08 8	1165.06 183	1332.72 184	662.07 184	584.90 172	715.99 194	4373.59 204	153.99 188	1880.27 198	709.02 194	2316.97 200	188.63 181	939.89 196	1484.30 198	302.78 188	330.34 182
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MG-MVS		1256.50 185	1432.00 186	730.00 190	610.00 177	760.00 196	4720.00 205	169.00 189	1920.00 199	723.00 196	2510.00 206	201.00 186	1050.00 205	1645.00 201	390.00 193	380.00 189

CMPMVS	2623.62 15	1983.08 193	2156.14 193	1463.89 214	1414.80 213	1517.00 218	5239.20 206	867.40 233	3310.30 210	1128.70 212	3489.90 210	366.75 205	2030.20 222	2427.60 209	1160.60 232	844.46 211
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
COLMAP_ROB	2144.59 11	1658.33 190	1869.33 190	1025.33 201	1030.00 206	1023.00 212	5311.00 207	359.00 201	3044.00 208	937.00 201	2892.00 207	332.00 200	1440.00 210	2312.00 208	607.00 196	613.00 197
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
TSAR-MVS + GP.		1386.84 187	1622.84 189	678.81 187	952.13 199	840.17 201	5358.21 208	170.75 190	2650.47 207	713.54 195	2394.28 204	209.42 191	855.56 192	1854.36 204	302.42 187	340.71 184

MVS-HIRNet		2125.39 194	2452.68 195	1143.53 203	2938.33 240	1446.92 217	6083.19 209	391.74 204	3801.71 213	1202.10 214	3439.72 209	492.73 210	1304.35 209	3048.25 214	676.32 198	679.32 203

F-COLMAP		1878.17 191	2113.11 192	1173.33 205	1231.00 207	1174.00 213	6297.00 210	392.00 205	3356.00 211	1087.00 210	3082.00 208	361.00 204	1670.00 212	2523.00 210	689.00 199	676.00 202

CHOSEN 280x420		2340.81 198	2643.03 199	1434.14 208	2025.55 230	1629.36 223	6542.40 211	412.49 207	4219.70 216	1547.02 225	4328.52 217	650.74 220	1798.26 215	3333.17 216	727.72 203	874.79 213

CHOSEN 1792x2688		2340.81 198	2643.03 199	1434.14 208	2025.55 230	1629.36 223	6542.40 211	412.49 207	4219.70 216	1547.02 225	4328.52 217	650.74 220	1798.26 215	3333.17 216	727.72 203	874.79 213

HyFIR lowres test		2340.81 198	2643.03 199	1434.14 208	2025.55 230	1629.36 223	6542.40 211	412.49 207	4219.70 216	1547.02 225	4328.52 217	650.74 220	1798.26 215	3333.17 216	727.72 203	874.79 213

OpenMVS_ROB	1936.51 10	1959.51 192	2224.88 194	1163.39 204	1253.91 208	1434.22 216	7065.71 214	272.76 196	2472.29 205	1647.54 234	3538.72 211	200.37 185	1496.48 211	2575.17 211	997.45 224	559.48 196

PLC	2858.82 16	2192.92 195	2474.00 196	1349.67 207	1407.00 212	1356.00 215	7164.00 215	475.00 217	3970.00 214	1237.00 216	3765.00 214	451.00 207	1891.00 218	3006.00 213	791.00 212	802.00 205
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
tpm2		3617.85 214	4007.23 214	2449.73 228	2012.71 225	1698.05 228	7351.19 216	869.29 234	6132.06 229	1588.28 229	8007.42 236	1281.09 243	3888.11 240	7472.04 239	1351.00 234	1763.02 239

tpm cat1		3617.85 214	4007.23 214	2449.73 228	2012.71 225	1698.05 228	7351.19 216	869.29 234	6132.06 229	1588.28 229	8007.42 236	1281.09 243	3888.11 240	7472.04 239	1351.00 234	1763.02 239

tpmp4_e23		3617.85 214	4007.23 214	2449.73 228	2012.71 225	1698.05 228	7351.19 216	869.29 234	6132.06 229	1588.28 229	8007.42 236	1281.09 243	3888.11 240	7472.04 239	1351.00 234	1763.02 239

CostFormer		3617.85 214	4007.23 214	2449.73 228	2012.71 225	1698.05 228	7351.19 216	869.29 234	6132.06 229	1588.28 229	8007.42 236	1281.09 243	3888.11 240	7472.04 239	1351.00 234	1763.02 239

tpm		3617.85 214	4007.23 214	2449.73 228	2012.71 225	1698.05 228	7351.19 216	869.29 234	6132.06 229	1588.28 229	8007.42 236	1281.09 243	3888.11 240	7472.04 239	1351.00 234	1763.02 239

tpmrst		2557.50 202	2847.12 203	1688.66 218	1784.08 221	1778.25 234	7445.50 221	342.14 200	4471.54 220	1534.55 224	4382.10 220	530.10 214	2361.21 226	4142.81 224	991.22 223	926.51 218

AdaColmap		2570.77 203	2948.61 204	1437.24 211	1873.64 222	1526.60 219	7819.77 222	373.97 202	4970.45 223	1479.29 222	4648.46 222	525.80 213	1904.97 219	4150.42 225	695.69 202	880.14 216

OpenMVS	2352.88 13	2263.08 196	2530.89 197	1459.67 213	1767.00 220	1591.00 221	7932.00 223	399.00 206	3643.00 212	1176.00 213	3569.00 212	297.00 197	1927.00 220	3302.00 215	693.00 201	861.00 212

DeepC-MVS_fast	2190.19 12	1535.59 189	1886.82 191	481.89 170	847.73 194	830.16 200	7943.84 224	189.23 193	2398.83 204	691.73 193	2341.13 201	209.16 190	230.25 155	1999.25 207	360.46 191	385.25 190
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
PCF-MVS	4335.85 20	2272.23 197	2597.03 198	1297.84 206	1701.20 215	1332.37 214	8105.11 225	451.45 213	4031.84 215	1099.10 211	3966.50 215	467.45 208	1734.05 214	2701.68 212	848.94 216	827.11 209
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
LF4IMVS		2699.50 206	3049.67 206	1649.00 217	1755.00 218	1689.00 227	8330.00 226	464.00 215	4997.00 224	1528.00 223	4763.00 223	568.00 216	2296.00 225	4215.00 226	827.00 215	962.00 221

3Dnovator	2482.06 14	2531.17 201	2839.56 202	1606.00 215	1732.00 217	1557.00 220	8375.00 227	483.00 218	4370.00 219	1371.00 220	4200.00 216	350.00 202	2207.00 223	3877.00 222	798.00 213	1054.00 230

Vis-MVSNet		2877.42 207	3170.00 208	1999.67 225	1673.00 214	2042.00 239	8593.00 228	474.00 216	6452.00 236	1268.00 217	5125.00 225	339.00 201	3004.00 235	4222.00 227	384.00 192	953.00 220
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
TAPA-MVS	6309.84 21	3374.90 212	3806.99 213	2078.63 227	2535.47 238	2499.25 242	8816.16 229	456.05 214	6255.60 234	1664.52 235	6704.88 232	629.95 218	2768.38 233	6343.93 236	856.35 217	968.25 222
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
DeepPCF-MVS	3452.42 18	2670.71 205	3021.57 205	1618.12 216	2377.67 235	1751.39 233	8915.70 230	567.44 224	4569.74 221	1236.84 215	4615.63 221	513.23 211	2291.32 224	3515.48 219	882.39 218	811.66 207

SD-MVS		2654.53 204	3055.56 207	1451.45 212	1725.60 216	1598.35 222	9203.30 231	315.86 199	5016.02 225	1363.85 219	4894.28 224	387.23 206	2023.43 221	3973.88 223	620.04 197	732.56 204

UA-Net		10000.00 226	10000.00 227	10000.00 240	10000.00 248	10000.00 251	10000.00 232	10000.00 253	10000.00 243	10000.00 248	10000.00 242	10000.00 250	10000.00 247	10000.00 245	10000.00 247	10000.00 247

uncertanet		10000.00 226	10000.00 227	10000.00 240	10000.00 248	10000.00 251	10000.00 232	10000.00 253	10000.00 243	10000.00 248	10000.00 242	10000.00 250	10000.00 247	10000.00 245	10000.00 247	10000.00 247

uanet		10000.00 226	10000.00 227	10000.00 240	10000.00 248	10000.00 251	10000.00 232	10000.00 253	10000.00 243	10000.00 248	10000.00 242	10000.00 250	10000.00 247	10000.00 245	10000.00 247	10000.00 247

3Dnovator+	3414.41 17	3146.67 209	3537.00 210	1975.67 223	2310.00 233	2005.00 238	10100.00 235	626.00 226	5753.00 227	1803.00 237	5179.00 227	487.00 209	2622.00 230	4550.00 229	1025.00 231	1300.00 233

SteuartSystems-ACMMP		2891.50 208	3284.78 209	1711.67 219	1954.00 223	1655.00 226	10117.00 236	445.00 212	5102.00 226	1375.00 221	5126.00 226	351.00 203	2638.00 232	4402.00 228	691.00 200	842.00 210
Skip Steuart: Steuart Systems R&D Blog.
DeepC-MVS	3917.13 19	3155.06 210	3601.83 211	1814.72 221	2515.52 237	1941.53 236	10432.50 237	589.42 225	4789.45 222	1298.65 218	7677.31 235	578.35 217	2589.53 227	3611.78 221	923.52 221	913.10 217
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MAR-MVS		3973.16 220	4387.92 221	2728.86 234	3345.27 241	3341.39 246	11403.90 238	798.76 231	6555.62 239	2569.29 241	6514.86 231	834.97 232	3237.43 237	5891.08 234	1577.54 240	1607.76 234
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
OPM-MVS		3268.00 211	3762.89 212	1783.33 220	1756.00 219	1806.00 235	12319.00 239	307.00 198	6319.00 235	1557.00 228	5763.00 228	302.00 199	2609.00 229	5061.00 232	482.00 195	935.00 219

TSAR-MVS + MP.		3528.01 213	4065.89 219	1914.35 222	2349.10 234	2141.30 240	12362.70 240	417.60 211	6717.80 240	1759.40 236	6497.50 230	518.18 212	2629.38 231	5164.32 233	806.40 214	972.38 223

API-MVS		4380.83 222	4906.56 222	2803.67 235	3844.00 242	3116.00 245	13454.00 241	901.00 239	6511.00 238	2794.00 242	7365.00 234	754.00 229	3634.00 238	6622.00 237	1914.00 243	1661.00 237

OMC-MVS		5022.26 223	5748.82 224	2842.58 236	4905.27 244	3101.27 244	14933.60 242	812.24 232	9278.40 242	2959.29 243	8800.17 241	1092.24 241	3806.30 239	7568.54 244	1389.60 239	1620.18 236

MVS_111021_HR		3742.80 219	4330.34 220	1980.20 224	2484.31 236	2259.52 241	14973.80 243	515.90 223	6500.13 237	1949.21 239	6146.89 229	535.66 215	2593.66 228	4880.76 231	986.37 222	1087.43 231

HSP-MVS		4296.20 221	4911.12 223	2451.45 233	2725.60 239	2598.35 243	16203.30 244	515.86 222	7016.02 241	2363.85 240	6894.28 233	887.23 233	3023.43 236	5973.88 235	1620.04 241	1732.56 238

CNLPA		10738.67 230	11772.44 231	7637.33 239	9120.00 247	8206.00 249	22252.00 245	2010.00 249	24984.00 249	7458.00 247	22596.00 248	2940.00 248	10260.00 250	11100.00 248	3492.00 245	4446.00 245

CLD-MVS		7338.25 224	8341.00 225	4330.00 237	4902.00 243	4991.00 247	23318.00 246	728.00 230	14437.00 248	4378.00 245	13379.00 245	824.00 231	5708.00 245	11429.00 249	1674.00 242	2291.00 244
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	10550.67 229	10002.44 230	12195.33 243	6242.00 246	8768.00 250	30896.00 247	4451.00 250	10331.00 246	6247.00 246	18296.00 247	283.00 196	21484.00 251	7364.00 238	5912.00 246	6334.00 246
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
LS3D		7684.71 225	8776.23 226	4410.16 238	5298.55 245	5631.53 248	34329.90 248	1504.57 248	11554.00 247	3896.41 244	15111.00 246	812.19 230	5985.63 246	3516.20 220	2963.23 244	1613.31 235

LTVRE_ROB	20565.47 23	23378.08 231	22805.00 232	25097.33 244	15500.00 251	19201.00 254	42712.00 249	6055.00 251	38388.00 250	16926.00 251	38534.00 249	7071.00 249	35653.00 252	29475.00 250	10584.00 250	20438.00 251
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		32606.17 232	34443.44 233	27094.33 245	29249.00 252	25246.00 255	51144.00 250	6705.00 252	42886.00 251	22888.00 252	48534.00 250	13263.00 253	37507.00 253	79298.00 251	16024.00 251	18530.00 250

114514_t		99999.00 233	99999.00 234	99999.00 246	99999.00 253	99999.00 256	99999.00 251	99999.00 256	99999.00 252	99999.00 253	99999.00 251	99999.00 254	99999.00 254	99999.00 252	99999.00 252	99999.00 252

PHI-MVS		99999.00 233	99999.00 234	99999.00 246	99999.00 253	99999.00 256	99999.00 251	99999.00 256	99999.00 252	99999.00 253	99999.00 251	99999.00 254	99999.00 254	99999.00 252	99999.00 252	99999.00 252

XVG-OURS-SEG-HR		999999.00 238	999999.00 236	999999.00 248	999999.00 255	999999.00 258	999999.00 253	999999.00 258	999999.00 254	999999.00 255	999999.00 253	999999.00 256	999999.00 256	999999.00 254	999999.00 254	999999.00 254

XVG-OURS		999999.00 238	999999.00 236	999999.00 248	999999.00 255	999999.00 258	999999.00 253	999999.00 258	999999.00 254	999999.00 255	999999.00 253	999999.00 256	999999.00 256	999999.00 254	999999.00 254	999999.00 254

XVG-ACMP-BASELINE		999999.00 238	999999.00 236	999999.00 248	999999.00 255	999999.00 258	999999.00 253	999999.00 258	999999.00 254	999999.00 255	999999.00 253	999999.00 256	999999.00 256	999999.00 254	999999.00 254	999999.00 254

0601test		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

Anonymous20240529		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

Anonymous202405211		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

Anonymous20240521		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

our_test_3		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

ppachtmachnet_test		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

SMA-MVS		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

tfpn111		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

conf0.01		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

ESAPD		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

conf0.002		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

thresconf0.02		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

tfpn_n400		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

tfpnconf		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

tfpnview11		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

tfpn1000		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

tfpn_ndepth		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

test_part1				10000000.00 251		10000000.00 261	10000000.00 256	10000000.00 261				10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

conf200view11		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

thres100view900		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

tfpnnormal		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

tfpn200view9		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

view600		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

view800		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

conf0.05thres1000		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

tfpn		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

v1.0		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

pmmvs6		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

pmmvs5		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

test_post1							10000000.00 256				10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257

Anonymous20231211		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

pmmvs-eth3d		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

Anonymous20231206		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

MTMP							10000000.00 256	10000000.00 261

Patchmatch-test1		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

Patchmatch-test		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

Patchmatch-RL test		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

canonicalmvs		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

anonymousdsp		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

FIs		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

FC-MVSNet-test		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

sosnet-low-res		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

AllTest		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

testing_2		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

test_normal		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

HPM-MVS++		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

XVS		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

pm-mvs1		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

X-MVStestdata		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

APDe-MVS		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

APD-MVS_3200maxsize		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

pmmvs4		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

test-LLR		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

TESTMET0.1,1		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

test-mter		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

testgi		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

test20.03		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

thres600view7		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

1111		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

.test1245		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

MP-MVS		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

thres400		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

test123		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

thres200		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

test0.0.03 1		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

test12356		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

testus		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

pmmvs3		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

testmv		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

EMVS		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

E-PMN		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

test2356		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

test1235678		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

PGM-MVS		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

MCST-MVS		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

MVS_Test		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

PMMVS2		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

PM-MVS		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

HQP_MVS		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

plane_prior2							10000000.00 256		10000000.00 257

mPP-MVS		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

DI_MVS_plusplus_test		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

DWT-MVSNet_test		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

Test4		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

HPM-MVS_fast		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

PatchFormer-LS_test		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

testpf		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

HPM-MVS		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
LPG-MVS_test		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

EPNet_dtu		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP-NCC					10000000.00 258		10000000.00 256		10000000.00 257	10000000.00 258

ACMP_Plane					10000000.00 258		10000000.00 256		10000000.00 257	10000000.00 258

CNVR-MVS		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

NCCC		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

CP-MVS		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

no-one		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

CPTT-MVS		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

HQP-MVS		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

IS-MVSNet		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

PAPM_NR		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

PAPR		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

Vis-MVSNet (Re-imp)		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

PatchMatch-RL		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

TDRefinement		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

EPP-MVSNet		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

PMMVS		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

PAPM		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

ACMMP		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257
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		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

PNet_i23d		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

wuyk23d		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

wuykxyi23d		10000000.00 241	10000000.00 242	10000000.00 251	10000000.00 258	10000000.00 261	10000000.00 256	10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

APD-MVS		1000000000.00 349	1000000000.00 350	1000000000.00 363	1000000000.00 376	1000000000.00 379	1000000000.00 370	1000000000.00 379	1000000000.00 372	1000000000.00 374	1000000000.00 372	1000000000.00 378	1000000000.00 376	1000000000.00 373	1000000000.00 373	1000000000.00 373
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
GSMVS																10000000.00 257

test_part2					10000000.00 258	10000000.00 261				10000000.00 258

sam_mvs1												10000000.00 259				10000000.00 257

sam_mvs												10000000.00 259

semantic-postprocess				10000000.00 251	10000000.00 258	10000000.00 261		10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

MTGPA								10000000.00 261

test_post											10000000.00 256	10000000.00 259	10000000.00 259

patchmatchnet-post											10000000.00 256	10000000.00 259	10000000.00 259

gm-plane-assit					611.29 178	600.33 186			579.21 156		567.40 153		531.67 170	503.93 156

test9_res														0.00 1	0.00 1	0.00 1

agg_prior2														0.00 1	0.00 1	0.00 1

agg_prior					0.00 1	0.00 1		0.00 1		0.00 1			0.00 1

TestCases				10000000.00 251	10000000.00 258	10000000.00 261		10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

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

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

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

testdata2													0.00 1	0.00 1

segment_acmp												0.00 1

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

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

plane_prior7					10000000.00 258	10000000.00 261

plane_prior6					10000000.00 258	10000000.00 261						10000000.00 259

plane_prior5								10000000.00 261					10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

plane_prior4											10000000.00 256

plane_prior3						10000000.00 261			10000000.00 257	10000000.00 258

plane_prior1					10000000.00 258

n2								14.20 133

nn								1.42 69

door-mid								1.42 69

lessismore_v0				569.20 177	667.25 189	644.68 190		96.45 165		428.86 171	1514.17 192	204.21 189	756.58 187	1061.60 188	197.79 169	306.34 179

LGP-MVS_train				10000000.00 251	10000000.00 258	10000000.00 261		10000000.00 261	10000000.00 257	10000000.00 258	10000000.00 256	10000000.00 259	10000000.00 259	10000000.00 257	10000000.00 257	10000000.00 257

test11								1.00 64

door								99.00 167

HQP5-MVS						10000000.00 261

BP-MVS														10000000.00 257

HQP4-MVS										10000000.00 258			10000000.00 259			10000000.00 257

HQP3-MVS								10000000.00 261							10000000.00 257

HQP2-MVS												10000000.00 259

NP-MVS					10000000.00 258	10000000.00 261					10000000.00 256

ACMMP++_ref															10000000.00 257

ACMMP++															10000000.00 257

Test By Simon												990.00 234

ITE_SJBPF				2014.00 226	1998.00 224	1992.00 237		701.00 229	5989.00 228	1812.00 238	3612.00 213	650.00 219	2852.00 234	4601.00 230	1195.00 233	1198.00 232

DeepMVS_CX				1.00 58	1.00 63	1.00 64		1.00 64	1.00 63	1.00 63	1.00 61	1.00 63	1.00 64	1.00 62	1.00 62	1.00 63

High-resolution multi-view benchmark