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.

fmvsm_l_conf0.5_n_a		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

fmvsm_l_conf0.5_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

fmvsm_s_conf0.1_n_a		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

fmvsm_s_conf0.1_n		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

fmvsm_s_conf0.5_n_a		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

fmvsm_s_conf0.5_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

MM		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_fmvsmconf0.1_n		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_fmvsmconf0.01_n		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_fmvsmconf_n		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_fmvsmvis_n_1920		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_fmvsm_n_1920		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_cas_vis1_n_1920		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_vis1_n_1920		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_vis1_n		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_fmvs1_n		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

mvsany_test1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

APD_test1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_vis1_rt		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_vis3_rt		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_fmvs2		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_fmvs1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_fmvs3		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

mvsany_test3		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

testf1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

APD_test2		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

test_f		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

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

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

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

MVS_0304		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

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

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

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

agg_prior					0.00 1	0.00 1		0.00 1		0.00 1			0.00 1

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

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

test_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

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

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

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

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

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

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

h-mvs33		0.30 36	0.30 37	0.30 41	0.30 48	0.30 48	0.30 48	0.30 49	0.30 48	0.30 47	0.30 45	0.30 47	0.30 48	0.30 46	0.30 46	0.30 46

hse-mvs2		0.30 36	0.30 37	0.30 41	0.30 48	0.30 48	0.30 48	0.30 49	0.30 48	0.30 47	0.30 45	0.30 47	0.30 48	0.30 46	0.30 46	0.30 46

CL-MVSNet_self_test		0.30 36	0.30 37	0.30 41	0.30 48	0.30 48	0.30 48	0.30 49	0.30 48	0.30 47	0.30 45	0.30 47	0.30 48	0.30 46	0.30 46	0.30 46

AUN-MVS		0.30 36	0.30 37	0.30 41	0.30 48	0.30 48	0.30 48	0.30 49	0.30 48	0.30 47	0.30 45	0.30 47	0.30 48	0.30 46	0.30 46	0.30 46

LCM-MVSNet		0.37 40	0.36 41	0.37 45	0.37 52	0.37 52	0.37 52	0.32 53	0.37 52	0.37 51	0.37 49	0.37 51	0.37 52	0.37 50	0.37 50	0.37 50

v144192		0.40 41	0.40 42	0.40 46	0.40 53	0.40 53	0.40 53	0.40 55	0.40 53	0.40 52	0.40 50	0.40 52	0.40 53	0.40 51	0.40 51	0.40 51

v1921920		0.40 41	0.40 42	0.40 46	0.40 53	0.40 53	0.40 53	0.40 55	0.40 53	0.40 52	0.40 50	0.40 52	0.40 53	0.40 51	0.40 51	0.40 51

v1192		0.40 41	0.40 42	0.40 46	0.40 53	0.40 53	0.40 53	0.40 55	0.40 53	0.40 52	0.40 50	0.40 52	0.40 53	0.40 51	0.40 51	0.40 51

v1144		0.40 41	0.40 42	0.40 46	0.40 53	0.40 53	0.40 53	0.40 55	0.40 53	0.40 52	0.40 50	0.40 52	0.40 53	0.40 51	0.40 51	0.40 51

v148		0.40 41	0.40 42	0.40 46	0.40 53	0.40 53	0.40 53	0.40 55	0.40 53	0.40 52	0.40 50	0.40 52	0.40 53	0.40 51	0.40 51	0.40 51

v7n		0.40 41	0.40 42	0.40 46	0.40 53	0.40 53	0.40 53	0.40 55	0.40 53	0.40 52	0.40 50	0.40 52	0.40 53	0.40 51	0.40 51	0.40 51

v1240		0.40 41	0.40 42	0.40 46	0.40 53	0.40 53	0.40 53	0.40 55	0.40 53	0.40 52	0.40 50	0.40 52	0.40 53	0.40 51	0.40 51	0.40 51

v8		0.40 41	0.40 42	0.40 46	0.40 53	0.40 53	0.40 53	0.40 55	0.40 53	0.40 52	0.40 50	0.40 52	0.40 53	0.40 51	0.40 51	0.40 51

v10		0.40 41	0.40 42	0.40 46	0.40 53	0.40 53	0.40 53	0.40 55	0.40 53	0.40 52	0.40 50	0.40 52	0.40 53	0.40 51	0.40 51	0.40 51

v2v482		0.40 41	0.40 42	0.40 46	0.40 53	0.40 53	0.40 53	0.40 55	0.40 53	0.40 52	0.40 50	0.40 52	0.40 53	0.40 51	0.40 51	0.40 51

V42		0.40 41	0.40 42	0.40 46	0.40 53	0.40 53	0.40 53	0.40 55	0.40 53	0.40 52	0.40 50	0.40 52	0.40 53	0.40 51	0.40 51	0.40 51

GA-MVS		0.40 41	0.40 42	0.40 46	0.40 53	0.40 53	0.40 53	0.40 55	0.40 53	0.40 52	0.40 50	0.40 52	0.40 53	0.40 51	0.40 51	0.40 51

Fast-Effi-MVS+		0.41 53	0.40 42	0.41 58	0.41 65	0.41 65	0.41 65	0.35 54	0.41 65	0.41 64	0.41 62	0.41 64	0.41 65	0.41 63	0.41 63	0.41 63

Fast-Effi-MVS+-dtu		0.44 54	0.44 55	0.44 59	0.44 66	0.44 66	0.44 66	0.44 67	0.44 66	0.44 65	0.44 63	0.44 65	0.44 66	0.44 64	0.44 64	0.44 64

Effi-MVS+		0.58 55	0.56 56	0.62 62	0.53 67	0.62 69	0.53 67	0.53 68	0.53 67	0.62 68	0.62 66	0.53 66	0.62 69	0.62 66	0.53 65	0.62 67

KD-MVS_self_test		0.60 57	0.60 57	0.60 61	0.60 68	0.60 68	0.60 69	0.60 69	0.60 68	0.60 67	0.60 65	0.60 67	0.60 68	0.60 65	0.60 67	0.60 66

EIA-MVS		0.62 58	0.62 59	0.62 62	0.62 69	0.62 69	0.62 70	0.62 70	0.62 69	0.62 68	0.62 66	0.62 68	0.62 69	0.62 66	0.62 68	0.62 67

ETV-MVS		0.62 58	0.62 59	0.62 62	0.62 69	0.62 69	0.62 70	0.62 70	0.62 69	0.62 68	0.62 66	0.62 68	0.62 69	0.62 66	0.62 68	0.62 67

CS-MVS		0.62 58	0.62 59	0.62 62	0.62 69	0.62 69	0.62 70	0.62 70	0.62 69	0.62 68	0.62 66	0.62 68	0.62 69	0.62 66	0.62 68	0.62 67

CS-MVS-test		0.62 58	0.62 59	0.62 62	0.62 69	0.62 69	0.62 70	0.62 70	0.62 69	0.62 68	0.62 66	0.62 68	0.62 69	0.62 66	0.62 68	0.62 67

EC-MVSNet		0.62 58	0.62 59	0.62 62	0.62 69	0.62 69	0.62 70	0.62 70	0.62 69	0.62 68	0.62 66	0.62 68	0.62 69	0.62 66	0.62 68	0.62 67

Effi-MVS+-dtu		0.59 56	0.61 58	0.53 60	0.68 74	0.53 67	0.53 67	0.68 75	0.68 74	0.53 66	0.53 64	0.68 73	0.53 67	0.68 72	0.53 65	0.53 65

CDS-MVSNet		0.88 63	0.88 64	0.88 68	0.88 75	0.88 75	0.88 75	0.88 76	0.88 75	0.88 74	0.88 72	0.88 74	0.88 75	0.88 73	0.88 73	0.88 73
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		0.88 63	0.88 64	0.88 68	0.88 75	0.88 75	0.88 75	0.88 76	0.88 75	0.88 74	0.88 72	0.88 74	0.88 75	0.88 73	0.88 73	0.88 73

LCM-MVSNet-Re		0.89 65	0.89 66	0.89 70	0.89 77	0.89 77	0.89 77	0.89 78	0.89 77	0.89 76	0.89 74	0.89 76	0.89 77	0.89 75	0.89 75	0.89 75

DeepMVS_CX				1.00 71	1.00 78	1.00 78		1.00 79	1.00 78	1.00 77	1.00 75	1.00 77	1.00 78	1.00 76	1.00 76	1.00 76

MDA-MVSNet-bldmvs		1.20 66	1.20 67	1.20 72	1.20 79	1.20 80	1.20 78	1.20 81	1.20 79	1.20 78	1.20 76	1.20 78	1.20 79	1.20 77	1.20 77	1.20 77

YYNet1		1.20 66	1.20 67	1.20 72	1.20 79	1.20 80	1.20 78	1.20 81	1.20 79	1.20 78	1.20 76	1.20 78	1.20 79	1.20 77	1.20 77	1.20 77

MDA-MVSNet_test_wron		1.20 66	1.20 67	1.20 72	1.20 79	1.20 80	1.20 78	1.20 81	1.20 79	1.20 78	1.20 76	1.20 78	1.20 79	1.20 77	1.20 77	1.20 77

KD-MVS_2432*1600		1.30 69	1.30 70	1.30 75	1.30 82	1.30 83	1.30 81	1.30 84	1.30 82	1.30 81	1.30 79	1.30 81	1.30 82	1.30 80	1.30 80	1.30 80

miper_refine_blended		1.30 69	1.30 70	1.30 75	1.30 82	1.30 83	1.30 81	1.30 84	1.30 82	1.30 81	1.30 79	1.30 81	1.30 82	1.30 80	1.30 80	1.30 80

eth-test2					1.42 84

EI-MVSNet-UG-set		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

EI-MVSNet-Vis-set		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

EI-MVSNet		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

Regformer		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

CVMVSNet		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

EU-MVSNet		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

PS-CasMVS		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

UniMVSNet_NR-MVSNet		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

PEN-MVS		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

TransMVSNet (Re)		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

DTE-MVSNet		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

DU-MVS		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

UniMVSNet (Re)		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

CP-MVSNet		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

WR-MVS_H		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

WR-MVS		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

NR-MVSNet		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

Baseline_NR-MVSNet		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

TranMVSNet+NR-MVSNet		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

MVSFormer		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

jason		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82
jason: jason.
lupinMVS		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

test_djsdf		1.42 71	1.42 72	1.42 77	1.42 84	1.42 85	1.42 83	1.42 86	1.42 84	1.42 83	1.42 81	1.42 83	1.42 84	1.42 82	1.42 82	1.42 82

reproduce_monomvs		1.48 94	1.48 95	1.48 100	1.48 108	1.48 108	1.48 106	1.48 111	1.48 107	1.48 106	1.48 104	1.48 106	1.48 107	1.48 105	1.48 105	1.48 105

mmtdpeth		1.48 94	1.48 95	1.48 100	1.48 108	1.48 108	1.48 106	1.48 111	1.48 107	1.48 106	1.48 104	1.48 106	1.48 107	1.48 105	1.48 105	1.48 105

reproduce_model		1.48 94	1.48 95	1.48 100	1.48 108	1.48 108	1.48 106	1.48 111	1.48 107	1.48 106	1.48 104	1.48 106	1.48 107	1.48 105	1.48 105	1.48 105

reproduce-ours		1.48 94	1.48 95	1.48 100	1.48 108	1.48 108	1.48 106	1.48 111	1.48 107	1.48 106	1.48 104	1.48 106	1.48 107	1.48 105	1.48 105	1.48 105

our_new_method		1.48 94	1.48 95	1.48 100	1.48 108	1.48 108	1.48 106	1.48 111	1.48 107	1.48 106	1.48 104	1.48 106	1.48 107	1.48 105	1.48 105	1.48 105

mmdepth		1.48 94	1.48 95	1.48 100	1.48 108	1.48 108	1.48 106	1.48 111	1.48 107	1.48 106	1.48 104	1.48 106	1.48 107	1.48 105	1.48 105	1.48 105

monomultidepth		1.48 94	1.48 95	1.48 100	1.48 108	1.48 108	1.48 106	1.48 111	1.48 107	1.48 106	1.48 104	1.48 106	1.48 107	1.48 105	1.48 105	1.48 105

mvs5depth		1.48 94	1.48 95	1.48 100	1.48 108	1.48 108	1.48 106	1.48 111	1.48 107	1.48 106	1.48 104	1.48 106	1.48 107	1.48 105	1.48 105	1.48 105

MVStest1		1.48 94	1.48 95	1.48 100	1.48 108	1.48 108	1.48 106	1.48 111	1.48 107	1.48 106	1.48 104	1.48 106	1.48 107	1.48 105	1.48 105	1.48 105

ttmdpeth		1.48 94	1.48 95	1.48 100	1.48 108	1.48 108	1.48 106	1.48 111	1.48 107	1.48 106	1.48 104	1.48 106	1.48 107	1.48 105	1.48 105	1.48 105

alignmvs		2.00 104	2.00 105	2.00 110	2.00 118	2.00 118	2.00 116	2.00 121	2.00 117	2.00 116	2.00 114	2.00 116	2.00 117	2.00 115	2.00 115	2.00 115

nrg030		2.00 104	2.00 105	2.00 110	2.00 118	2.00 118	2.00 116	2.00 121	2.00 117	2.00 116	2.00 114	2.00 116	2.00 117	2.00 115	2.00 115	2.00 115

LFMVS		2.00 104	2.00 105	2.00 110	2.00 118	2.00 118	2.00 116	2.00 121	2.00 117	2.00 116	2.00 114	2.00 116	2.00 117	2.00 115	2.00 115	2.00 115

VDD-MVS		2.00 104	2.00 105	2.00 110	2.00 118	2.00 118	2.00 116	2.00 121	2.00 117	2.00 116	2.00 114	2.00 116	2.00 117	2.00 115	2.00 115	2.00 115

VDDNet		2.00 104	2.00 105	2.00 110	2.00 118	2.00 118	2.00 116	2.00 121	2.00 117	2.00 116	2.00 114	2.00 116	2.00 117	2.00 115	2.00 115	2.00 115

VPNet		2.00 104	2.00 105	2.00 110	2.00 118	2.00 118	2.00 116	2.00 121	2.00 117	2.00 116	2.00 114	2.00 116	2.00 117	2.00 115	2.00 115	2.00 115

VNet		2.00 104	2.00 105	2.00 110	2.00 118	2.00 118	2.00 116	2.00 121	2.00 117	2.00 116	2.00 114	2.00 116	2.00 117	2.00 115	2.00 115	2.00 115

VPA-MVSNet		2.00 104	2.00 105	2.00 110	2.00 118	2.00 118	2.00 116	2.00 121	2.00 117	2.00 116	2.00 114	2.00 116	2.00 117	2.00 115	2.00 115	2.00 115

cascas		2.00 104	2.00 105	2.00 110	2.00 118	2.00 118	2.00 116	2.00 121	2.00 117	2.00 116	2.00 114	2.00 116	2.00 117	2.00 115	2.00 115	2.00 115

UnsupCasMVSNet_eth		5.90 113	5.90 114	5.90 119	5.90 127	5.90 127	5.90 126	5.90 133	5.90 127	5.90 125	5.90 123	5.90 127	5.90 126	5.90 124	5.90 127	5.90 127

UnsupCasMVSNet_bld		5.90 113	5.90 114	5.90 119	5.90 127	5.90 127	5.90 126	5.90 133	5.90 127	5.90 125	5.90 123	5.90 127	5.90 126	5.90 124	5.90 127	5.90 127

WTY-MVS		5.90 113	5.90 114	5.90 119	5.90 127	5.90 127	5.90 126	5.90 133	5.90 127	5.90 125	5.90 123	5.90 127	5.90 126	5.90 124	5.90 127	5.90 127

HY-MVS	5.90 1	5.90 113	5.90 114	5.90 119	5.90 127	5.90 127	5.90 126	5.90 133	5.90 127	5.90 125	5.90 123	5.90 127	5.90 126	5.90 124	5.90 127	5.90 127

sss		5.90 113	5.90 114	5.90 119	5.90 127	5.90 127	5.90 126	5.90 133	5.90 127	5.90 125	5.90 123	5.90 127	5.90 126	5.90 124	5.90 127	5.90 127

Test_1112_low_res		5.90 113	5.90 114	5.90 119	5.90 127	5.90 127	5.90 126	5.90 133	5.90 127	5.90 125	5.90 123	5.90 127	5.90 126	5.90 124	5.90 127	5.90 127

1112_ss		5.90 113	5.90 114	5.90 119	5.90 127	5.90 127	5.90 126	5.90 133	5.90 127	5.90 125	5.90 123	5.90 127	5.90 126	5.90 124	5.90 127	5.90 127

ab-mvs-re		5.90 113	5.90 114	5.90 119	5.90 127	5.90 127	5.90 126	5.90 133	5.90 127	5.90 125	5.90 123	5.90 127	5.90 126	5.90 124	5.90 127	5.90 127

ab-mvs		5.90 113	5.90 114	5.90 119	5.90 127	5.90 127	5.90 126	5.90 133	5.90 127	5.90 125	5.90 123	5.90 127	5.90 126	5.90 124	5.90 127	5.90 127

CDPH-MVS		6.66 122	6.66 123	6.66 128	6.66 136	6.66 136	6.66 135	6.66 142	6.66 136	6.66 134	6.66 132	6.66 136	6.66 135	6.66 133	6.66 136	6.66 136

MDTV_nov1_ep13			9.99 124		9.99 137	9.99 138	9.99 136	9.99 144	9.99 137	9.99 136	9.99 133	9.99 138	9.99 137	9.99 134	9.99 138

xiu_mvs_v1_base_debu		10.28 123	10.28 125	10.28 130	10.28 138	10.28 140	10.28 138	10.28 145	10.28 139	10.28 138	10.28 134	10.28 140	10.28 138	10.28 136	10.28 139	10.28 138

xiu_mvs_v2_base		10.28 123	10.28 125	10.28 130	10.28 138	10.28 140	10.28 138	10.28 145	10.28 139	10.28 138	10.28 134	10.28 140	10.28 138	10.28 136	10.28 139	10.28 138

xiu_mvs_v1_base		10.28 123	10.28 125	10.28 130	10.28 138	10.28 140	10.28 138	10.28 145	10.28 139	10.28 138	10.28 134	10.28 140	10.28 138	10.28 136	10.28 139	10.28 138

xiu_mvs_v1_base_debi		10.28 123	10.28 125	10.28 130	10.28 138	10.28 140	10.28 138	10.28 145	10.28 139	10.28 138	10.28 134	10.28 140	10.28 138	10.28 136	10.28 139	10.28 138

cdsmvs_eth3d_5k		10.28 123	10.28 125	10.28 130	10.28 138	10.28 140	10.28 138	10.28 145	10.28 139	10.28 138	10.28 134	10.28 140	10.28 138	10.28 136	10.28 139	10.28 138

pcd_1.5k_mvsjas		10.28 123	10.28 125	10.28 130	10.28 138	10.28 140	10.28 138	10.28 145	10.28 139	10.28 138	10.28 134	10.28 140	10.28 138	10.28 136	10.28 139	10.28 138

PS-MVSNAJss		10.28 123	10.28 125	10.28 130	10.28 138	10.28 140	10.28 138	10.28 145	10.28 139	10.28 138	10.28 134	10.28 140	10.28 138	10.28 136	10.28 139	10.28 138

PS-MVSNAJ		10.28 123	10.28 125	10.28 130	10.28 138	10.28 140	10.28 138	10.28 145	10.28 139	10.28 138	10.28 134	10.28 140	10.28 138	10.28 136	10.28 139	10.28 138

jajsoiax		10.28 123	10.28 125	10.28 130	10.28 138	10.28 140	10.28 138	10.28 145	10.28 139	10.28 138	10.28 134	10.28 140	10.28 138	10.28 136	10.28 139	10.28 138

mvs_tets		10.28 123	10.28 125	10.28 130	10.28 138	10.28 140	10.28 138	10.28 145	10.28 139	10.28 138	10.28 134	10.28 140	10.28 138	10.28 136	10.28 139	10.28 138

dp		87.20 142	113.80 146	7.42 129	10.50 148	8.88 137	298.82 163	2.70 130	510.35 180	7.79 135	172.93 156	3.37 125	9.16 136	14.00 147	3.71 125	4.23 125

SR-MVS-dyc-post		11.55 133	11.55 135	11.55 142	11.55 149	11.55 151	11.55 148	11.55 157	11.55 149	11.55 149	11.55 144	11.55 151	11.55 148	11.55 146	11.55 149	11.55 148

test_method		18.29 135	20.89 137	10.50 140	15.00 150	13.00 152	55.00 155	3.00 131	34.00 152	11.50 148	32.50 146	5.00 126	13.50 149	27.00 150	5.00 126	5.00 126

XXY-MVS		15.00 134	15.00 136	15.00 143	15.00 150	15.00 153	15.00 149	15.00 159	15.00 150	15.00 151	15.00 145	15.00 155	15.00 150	15.00 148	15.00 151	15.00 150

GeoE		19.41 136	22.09 138	11.37 141	17.21 152	11.30 150	50.50 154	4.30 132	33.60 151	11.70 150	44.50 151	7.30 137	18.90 151	22.60 149	7.10 137	3.90 124

BH-w/o		40.00 137	40.00 139	40.00 145	40.00 153	40.00 154	40.00 150	40.00 176	40.00 153	40.00 153	40.00 147	40.00 172	40.00 153	40.00 151	40.00 165	40.00 161

BH-untuned		40.00 137	40.00 139	40.00 145	40.00 153	40.00 154	40.00 150	40.00 176	40.00 153	40.00 153	40.00 147	40.00 172	40.00 153	40.00 151	40.00 165	40.00 161

BH-RMVSNet		40.00 137	40.00 139	40.00 145	40.00 153	40.00 154	40.00 150	40.00 176	40.00 153	40.00 153	40.00 147	40.00 172	40.00 153	40.00 151	40.00 165	40.00 161

TR-MVS		40.00 137	40.00 139	40.00 145	40.00 153	40.00 154	40.00 150	40.00 176	40.00 153	40.00 153	40.00 147	40.00 172	40.00 153	40.00 151	40.00 165	40.00 161

GBi-Net		44.67 141	49.24 143	30.96 144	47.53 157	47.57 158	126.09 156	8.00 143	76.99 157	26.09 152	73.50 153	11.27 150	30.55 152	61.12 155	12.58 150	14.75 149

MTAPA		833442.10 289	1111233.77 295	67.09 151	65.59 158	64.81 161	284.50 160	10000000.00 327	219.97 163	59.62 159	229.89 167	12.72 152	103.00 172	203.67 173	27.93 152	33.46 151

MP-MVS-pluss		833433.63 288	1111219.60 294	75.70 155	74.28 159	73.29 162	284.50 160	11.35 155	238.58 164	65.86 160	255.35 172	14.55 153	115.69 174	10000000.00 321	31.94 153	38.12 159
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
ACMMP_NAP		118.81 148	133.18 150	75.70 155	74.28 159	73.29 162	284.50 160	11.35 155	238.58 164	65.86 160	255.35 172	14.55 153	115.69 174	222.18 174	31.94 153	38.12 159

CANet		110.62 145	124.04 147	70.34 152	82.03 161	74.27 164	325.54 164	25.25 162	207.16 160	69.28 162	194.38 157	27.53 158	95.79 166	147.76 160	37.43 155	40.97 165

CANet_DTU		110.62 145	124.04 147	70.34 152	82.03 161	74.27 164	325.54 164	25.25 162	207.16 160	69.28 162	194.38 157	27.53 158	95.79 166	147.76 160	37.43 155	40.97 165

UGNet		110.62 145	124.04 147	70.34 152	82.03 161	74.27 164	325.54 164	25.25 162	207.16 160	69.28 162	194.38 157	27.53 158	95.79 166	147.76 160	37.43 155	40.97 165
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
new_pmnet		88.14 143	98.62 144	56.70 149	98.14 164	56.07 159	246.79 158	15.37 160	148.06 158	50.77 157	143.13 154	23.35 156	62.65 157	93.26 156	68.71 173	51.38 171

N_pmnet		88.14 143	98.62 144	56.70 149	98.14 164	56.07 159	246.79 158	15.37 160	148.06 158	50.77 157	143.13 154	23.35 156	62.65 157	93.26 156	68.71 173	51.38 171

DSMNet-mixed		131.33 156	143.00 158	96.33 167	99.00 166	81.00 167	201.00 157	45.00 181	335.00 176	99.00 175	251.00 171	38.00 171	110.00 173	120.00 159	99.00 179	98.00 175

FMVSNet5		124.76 149	140.93 151	76.26 157	107.44 167	100.17 171	329.88 167	27.12 168	259.44 169	74.30 165	204.34 160	30.74 161	92.41 159	196.98 163	38.15 158	36.19 152

test1		124.76 149	140.93 151	76.26 157	107.44 167	100.17 171	329.88 167	27.12 168	259.44 169	74.30 165	204.34 160	30.74 161	92.41 159	196.98 163	38.15 158	36.19 152

FMVSNet3		124.76 149	140.93 151	76.26 157	107.44 167	100.17 171	329.88 167	27.12 168	259.44 169	74.30 165	204.34 160	30.74 161	92.41 159	196.98 163	38.15 158	36.19 152

FMVSNet2		124.76 149	140.93 151	76.26 157	107.44 167	100.17 171	329.88 167	27.12 168	259.44 169	74.30 165	204.34 160	30.74 161	92.41 159	196.98 163	38.15 158	36.19 152

FMVSNet1		124.76 149	140.93 151	76.26 157	107.44 167	100.17 171	329.88 167	27.12 168	259.44 169	74.30 165	204.34 160	30.74 161	92.41 159	196.98 163	38.15 158	36.19 152

MIMVSNet1		124.76 149	140.93 151	76.26 157	107.44 167	100.17 171	329.88 167	27.12 168	259.44 169	74.30 165	204.34 160	30.74 161	92.41 159	196.98 163	38.15 158	36.19 152

MIMVSNet		124.76 149	140.93 151	76.26 157	107.44 167	100.17 171	329.88 167	27.12 168	259.44 169	74.30 165	204.34 160	30.74 161	92.41 159	196.98 163	38.15 158	36.19 152

PVSNet_Blended_VisFu		136.90 157	155.40 159	81.40 164	111.00 174	96.20 168	407.00 174	25.90 165	251.60 166	85.10 172	240.50 168	37.00 168	99.90 169	199.80 170	40.70 169	48.10 168

PVSNet_BlendedMVS		136.90 157	155.40 159	81.40 164	111.00 174	96.20 168	407.00 174	25.90 165	251.60 166	85.10 172	240.50 168	37.00 168	99.90 169	199.80 170	40.70 169	48.10 168

PVSNet_Blended		136.90 157	155.40 159	81.40 164	111.00 174	96.20 168	407.00 174	25.90 165	251.60 166	85.10 172	240.50 168	37.00 168	99.90 169	199.80 170	40.70 169	48.10 168

FE-MVS		207.10 160	234.26 162	125.61 168	180.34 177	153.23 178	635.64 181	30.05 175	378.38 177	127.68 176	377.08 174	48.95 176	154.43 176	266.67 175	63.56 172	69.18 173

DP-MVS		264.78 162	296.02 164	171.04 171	191.70 178	183.96 180	827.10 188	78.36 190	438.24 178	176.64 179	435.12 175	65.04 179	230.52 181	334.02 177	117.96 186	98.64 176

tmp_tt		371.08 170	412.78 171	246.00 181	231.00 179	197.00 182	1293.00 213	376.00 252	756.00 200	609.00 230	71.00 152	106.00 193	195.00 177	102.00 158	171.00 201	346.00 226

FA-MVS(test-final)		261.15 161	293.29 163	164.72 169	236.23 180	199.99 183	800.05 187	42.35 180	475.87 179	155.47 177	470.67 176	58.49 177	205.24 178	319.44 176	81.03 176	88.93 174

kuosan		267.89 163	301.05 165	168.41 170	244.05 181	177.28 179	667.98 182	65.76 183	533.41 181	157.79 178	492.01 177	104.69 192	226.72 179	364.47 179	79.31 175	101.21 177

WB-MVS		316.44 164	357.41 166	193.51 173	257.06 182	213.32 185	914.45 189	49.03 182	600.77 187	186.42 181	634.00 188	75.03 182	251.35 183	411.39 180	88.55 177	115.87 179

SSC-MVS		320.23 165	364.09 167	188.66 172	260.78 183	193.84 181	975.93 195	73.11 188	596.72 186	185.29 180	589.02 183	74.47 181	246.01 182	427.42 182	94.06 178	126.12 180

EG-PatchMatch MVS		437.03 178	493.12 182	268.77 186	264.80 184	260.20 192	1491.80 216	98.00 203	723.20 197	238.80 187	722.40 192	63.10 178	382.00 198	629.00 204	207.00 209	164.10 194

testing11		348.86 167	393.09 169	216.15 174	275.24 185	239.53 186	915.55 190	72.35 185	679.89 193	215.75 184	633.79 187	118.08 196	276.62 184	509.56 193	117.61 185	132.30 181

testing91		347.05 166	389.92 168	218.43 175	275.92 186	241.43 187	923.71 191	71.70 184	667.65 192	217.04 185	629.00 186	113.33 195	281.39 185	495.50 185	115.45 182	132.47 182

RPSCF		394.81 173	445.63 175	242.35 179	276.55 187	253.63 189	1207.27 210	90.69 198	715.56 194	241.57 188	684.87 189	111.96 194	320.02 189	548.38 197	133.81 187	153.39 190

dongtai		360.45 168	401.64 170	236.89 178	303.10 188	262.16 193	963.12 192	72.78 186	622.82 190	199.37 182	708.06 191	130.96 199	310.90 188	506.46 192	108.11 180	137.60 185

Syy-MVS		370.76 169	415.60 172	236.25 177	310.54 189	210.76 184	965.13 193	98.58 204	746.06 198	266.26 191	788.85 197	91.37 186	364.76 194	357.17 178	116.42 183	133.22 183

myMVS_eth3d		390.90 172	437.44 173	251.28 183	310.54 189	255.86 190	965.13 193	98.58 204	746.06 198	266.26 191	788.85 197	154.95 206	364.76 194	490.19 184	116.42 183	133.22 183

testing99		408.82 175	462.15 177	248.86 182	322.45 191	269.42 194	1118.93 206	73.26 189	719.36 196	262.28 190	772.10 194	150.98 205	327.08 190	601.98 200	137.99 189	150.07 188

testing3		418.10 176	469.06 178	265.23 185	335.69 192	290.63 196	1240.88 211	93.72 199	717.99 195	215.31 183	811.97 203	232.41 235	358.74 193	458.67 183	114.88 181	146.32 187

DELS-MVS		514.57 186	587.73 189	295.12 190	343.03 193	328.09 202	1540.48 218	116.22 212	988.59 209	325.44 203	906.22 207	119.86 198	365.72 196	788.60 214	161.09 198	191.55 201
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
UWE-MVS		387.98 171	438.66 174	235.93 176	349.32 194	257.61 191	1081.50 203	82.45 194	637.74 191	257.12 189	738.54 193	134.25 200	308.00 186	531.93 195	135.11 188	142.17 186

DP-MVS Recon		516.25 187	581.17 188	321.48 195	361.02 195	429.00 211	1995.36 223	78.48 191	796.20 202	283.32 197	796.02 199	96.78 187	382.98 199	636.72 206	186.66 206	152.46 189

ACMH+	729.97 2	661.38 194	754.00 196	383.51 199	368.96 196	376.38 206	2483.74 237	82.42 193	1089.25 218	333.39 204	1219.68 223	66.53 180	573.60 222	957.86 220	184.14 205	200.56 203

WB-MVSnew		404.84 174	458.00 176	245.36 180	374.70 197	320.27 199	1193.74 209	72.90 187	773.77 201	238.30 186	688.22 190	90.05 185	308.59 187	532.76 196	157.54 195	107.21 178

MVP-Stereo		473.58 182	533.67 184	293.33 188	376.00 198	318.00 197	1461.00 214	96.00 200	835.00 203	290.00 198	804.00 200	97.00 188	383.00 200	688.00 211	156.00 192	179.00 196
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MS-PatchMatch		473.58 182	533.67 184	293.33 188	376.00 198	318.00 197	1461.00 214	96.00 200	835.00 203	290.00 198	804.00 200	97.00 188	383.00 200	688.00 211	156.00 192	179.00 196

ETVMVS		443.50 181	498.07 183	279.78 187	378.05 200	321.57 200	1163.68 208	87.12 195	897.50 208	269.81 193	822.83 204	141.20 204	334.53 192	568.21 199	154.21 191	183.26 198

testing222		430.52 177	487.50 181	259.56 184	379.87 201	282.69 195	1138.34 207	81.30 192	880.86 205	281.58 194	834.27 205	135.83 202	333.22 191	514.90 194	140.56 190	162.76 191

UBG		667.82 195	787.71 199	308.16 192	385.94 202	327.65 201	1718.51 219	117.00 213	1942.46 245	317.12 202	1488.73 236	183.89 213	404.82 204	763.70 213	172.02 202	192.01 202

WBMVS		655.88 193	770.84 198	310.98 193	391.79 203	353.00 203	2280.68 225	99.17 207	1776.79 240	301.20 200	1123.23 222	187.34 221	390.28 202	620.39 203	156.98 194	189.66 200

tpmvs		501.65 185	567.42 187	304.33 191	395.39 204	356.32 204	1512.04 217	216.53 239	994.15 210	350.16 205	804.16 202	119.38 197	380.98 197	555.14 198	159.87 197	175.69 195

PatchmatchNet		492.52 184	551.22 186	316.40 194	400.20 205	357.90 205	1277.10 212	115.80 211	1034.60 217	315.90 201	874.00 206	155.10 207	402.20 203	629.50 205	158.80 196	189.10 199
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PMVS	863.65 3	957.08 214	1054.11 223	666.00 228	401.00 206	495.00 214	3790.00 245	279.00 241	1607.00 238	521.00 222	1745.00 240	90.00 183	1105.00 251	639.00 207	415.00 236	398.00 233
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
CSCG		826.03 209	963.29 214	414.24 201	421.52 207	426.11 210	2230.35 224	179.52 235	1827.44 241	733.43 241	933.12 209	281.25 237	545.23 213	1800.35 249	262.64 223	271.38 214

IB-MVS	872.44 4	616.41 192	700.96 195	362.78 198	426.10 208	409.25 209	1822.69 220	124.42 222	1186.23 220	366.85 207	1079.42 219	190.60 223	451.78 207	930.72 219	181.59 204	227.30 205
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
ADS-MVSNet2		443.33 179	482.84 179	324.79 196	434.94 209	387.73 207	1110.57 204	87.69 196	887.02 206	282.92 195	779.29 195	98.57 190	422.76 205	502.40 186	162.19 199	163.87 192

ADS-MVSNet		443.33 179	482.84 179	324.79 196	434.94 209	387.73 207	1110.57 204	87.69 196	887.02 206	282.92 195	779.29 195	98.57 190	422.76 205	502.40 186	162.19 199	163.87 192

ACMH	993.80 5	967.92 215	1106.11 225	553.33 216	494.00 211	534.00 216	3581.00 243	136.00 224	1585.00 237	478.00 219	1871.00 242	90.00 183	839.00 234	1460.00 243	260.00 222	287.00 217
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
IterMVS		615.05 191	691.66 194	385.23 200	516.40 212	454.80 212	1863.80 221	102.10 208	1142.20 219	364.10 206	1093.20 221	135.00 201	480.40 208	826.90 215	181.20 203	220.50 204
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
ACMM	1311.08 8	1165.06 227	1332.72 230	662.07 227	584.90 213	715.99 239	4373.59 250	153.99 232	1880.27 243	709.02 238	2316.97 246	188.63 222	939.89 239	1484.30 244	302.78 230	330.34 223
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
new-patchmatchnet		766.12 198	859.03 203	487.38 213	595.68 214	536.14 217	2346.27 227	142.51 227	1488.08 227	422.43 208	1361.32 227	163.65 210	628.60 227	1003.74 229	207.61 210	297.41 219

ACMP	1246.57 7	1086.24 223	1235.17 227	639.45 223	596.53 215	639.91 234	3904.24 246	152.04 230	1851.54 242	566.58 228	1997.95 244	138.50 203	938.30 238	1605.46 245	303.70 231	340.14 224
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
SixPastTwentyTwo		773.62 199	869.37 205	486.35 212	603.45 216	547.15 226	2532.14 238	106.92 210	1434.95 226	428.08 209	1360.56 226	165.15 211	628.96 228	984.09 221	209.01 211	282.94 216

IterMVS-LS		758.94 197	856.56 202	466.10 210	606.60 217	546.80 225	2309.90 226	122.20 221	1402.80 225	463.50 211	1348.20 225	192.60 224	574.60 223	1028.60 230	234.60 221	276.90 215
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MG-MVS		1256.50 229	1432.00 232	730.00 232	610.00 218	760.00 241	4720.00 251	169.00 233	1920.00 244	723.00 240	2510.00 252	201.00 227	1050.00 249	1645.00 247	390.00 235	380.00 230

RE-MVS-def			610.10 191		610.10 219	610.10 232	610.10 179	610.10 284	610.10 188	610.10 231	610.10 184	610.10 267		610.10 201	610.10 240	610.10 238

SR-MVS		610.10 189	610.10 191	610.10 222	610.10 219	610.10 232	610.10 179	610.10 284	610.10 188	610.10 231	610.10 184	610.10 267	610.10 225	610.10 201	610.10 240	610.10 238

GG-mvs-BLEND				596.01 220	611.29 221	600.33 229	790.30 184	513.12 275		552.71 224	567.40 178	662.54 279	531.67 209	503.93 188	779.80 257	656.02 241

gm-plane-assit					611.29 221	600.33 229			579.21 182		567.40 178		531.67 209	503.93 188

CR-MVSNet		612.36 190	617.81 193	596.01 220	611.29 221	600.33 229	790.30 184	513.12 275	579.21 182	552.71 224	567.40 178	662.54 279	531.67 209	503.93 188	779.80 257	656.02 241

Gipuma		689.75 196	767.00 197	458.00 209	613.00 224	549.00 227	1943.00 222	187.00 236	1230.00 221	518.00 221	1092.00 220	203.00 229	564.00 214	892.00 218	225.00 219	261.00 213
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
gg-mvs-nofinetune		594.69 188	605.37 190	562.67 217	617.29 225	500.33 215	772.30 183	413.12 260	579.21 182	552.71 224	567.40 178	662.54 279	531.67 209	503.93 188	779.80 257	656.02 241

mvs_anonymous		774.90 200	882.28 206	452.77 202	636.50 226	537.20 218	2348.80 228	120.30 214	1504.30 228	474.40 212	1371.10 228	186.90 214	564.70 215	1078.90 232	219.30 212	256.40 206

casdiffmvs		774.90 200	882.28 206	452.77 202	636.50 226	537.20 218	2348.80 228	120.30 214	1504.30 228	474.40 212	1371.10 228	186.90 214	564.70 215	1078.90 232	219.30 212	256.40 206
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		774.90 200	882.28 206	452.77 202	636.50 226	537.20 218	2348.80 228	120.30 214	1504.30 228	474.40 212	1371.10 228	186.90 214	564.70 215	1078.90 232	219.30 212	256.40 206
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		774.90 200	882.28 206	452.77 202	636.50 226	537.20 218	2348.80 228	120.30 214	1504.30 228	474.40 212	1371.10 228	186.90 214	564.70 215	1078.90 232	219.30 212	256.40 206

baseline1		774.90 200	882.28 206	452.77 202	636.50 226	537.20 218	2348.80 228	120.30 214	1504.30 228	474.40 212	1371.10 228	186.90 214	564.70 215	1078.90 232	219.30 212	256.40 206

casdiffmvs_mvg		774.90 200	882.28 206	452.77 202	636.50 226	537.20 218	2348.80 228	120.30 214	1504.30 228	474.40 212	1371.10 228	186.90 214	564.70 215	1078.90 232	219.30 212	256.40 206
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		774.90 200	882.28 206	452.77 202	636.50 226	537.20 218	2348.80 228	120.30 214	1504.30 228	474.40 212	1371.10 228	186.90 214	564.70 215	1078.90 232	219.30 212	256.40 206

PVSNet	1207.94 6	829.56 210	937.18 213	506.69 214	645.55 233	585.72 228	2477.98 236	130.52 223	1578.29 236	509.50 220	1460.01 235	194.90 225	637.19 229	1170.78 240	267.07 225	297.17 218

FPMVS		1407.00 232	1495.59 234	1141.23 245	648.01 234	893.85 248	4124.00 247	503.81 274	3219.04 255	742.72 242	2498.84 251	157.98 208	1727.83 258	832.93 216	732.98 256	802.00 250

lessismore_v0				569.20 218	667.25 235	644.68 235		96.45 202		428.86 210	1514.17 237	204.21 230	756.58 231	1061.60 231	197.79 208	306.34 220

PVSNet_0	1661.03 9	968.54 216	1066.82 224	673.70 229	706.94 236	695.69 237	2669.02 241	153.52 231	2108.17 247	605.54 229	1679.14 239	213.26 233	886.75 237	1236.76 242	229.01 220	438.67 234

MSLP-MVS++		1242.93 228	1411.08 231	738.48 233	712.71 237	712.68 238	4168.17 248	136.50 225	2276.40 249	613.28 233	2368.60 249	161.61 209	1130.38 252	1964.54 252	297.88 228	372.39 229

MVSTER		890.06 213	1005.91 222	542.52 215	736.13 238	653.90 236	2616.56 240	145.22 229	1692.10 239	555.69 227	1554.72 238	266.25 236	660.02 230	1219.66 241	266.84 224	313.64 222

MVS_111021_LR		1136.45 226	1298.72 229	649.64 224	756.17 239	726.26 240	3785.94 244	138.15 226	2190.64 248	629.63 234	2064.39 245	165.45 212	874.83 236	1678.43 248	279.70 226	347.82 227

DeepC-MVS_fast	2190.19 12	1535.59 233	1886.82 237	481.89 211	847.73 240	830.16 245	7943.84 270	189.23 237	2398.83 250	691.73 237	2341.13 247	209.16 231	230.25 180	1999.25 253	360.46 233	385.25 231
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
JIA-IIPM		804.30 208	835.64 201	710.26 231	885.90 241	895.90 249	455.98 177	668.73 289	1297.17 222	1002.26 253	1001.67 217	655.98 277	756.98 232	667.90 208	885.21 269	477.90 235

RPMNet		787.26 207	829.13 200	661.63 226	885.90 241	895.90 249	455.98 177	610.10 284	1297.17 222	1002.26 253	1001.67 217	655.98 277	611.10 226	667.90 208	885.21 269	477.90 235

ACMMPR		1296.60 230	1480.82 233	743.96 234	899.25 243	763.47 242	4305.47 249	143.90 228	2530.94 252	683.99 235	2346.34 248	201.65 228	1098.25 250	1920.59 251	295.21 227	370.16 228

test_0402		1110.00 225	1260.00 228	660.00 225	900.00 244	780.00 243	3300.00 242	210.00 238	2040.00 246	690.00 236	1950.00 243	300.00 240	810.00 233	1620.00 246	330.00 232	390.00 232

TSAR-MVS + GP.		1386.84 231	1622.84 235	678.81 230	952.13 245	840.17 246	5358.21 254	170.75 234	2650.47 253	713.54 239	2394.28 250	209.42 232	855.56 235	1854.36 250	302.42 229	340.71 225

ambc				999.00 237	999.00 246	999.00 251	999.00 196	999.00 300		999.00 246	999.00 210	999.00 292	999.00 242	999.00 222	999.00 276	999.00 273

OurMVSNet-221017-0		999.00 217	999.00 216	999.00 237	999.00 246	999.00 251	999.00 196	999.00 300	999.00 211	999.00 246	999.00 210	999.00 292	999.00 242	999.00 222	999.00 276	999.00 273

EPMVS		999.00 217	999.00 216	999.00 237	999.00 246	999.00 251	999.00 196	999.00 300	999.00 211	999.00 246	999.00 210	999.00 292	999.00 242	999.00 222	999.00 276	999.00 273

uanet_test		1000.00 219	1000.00 218	1000.00 240	1000.00 249	1000.00 254	1000.00 199	1000.00 303	1000.00 213	1000.00 249	1000.00 213	1000.00 295	1000.00 245	1000.00 225	1000.00 279	1000.00 276

sosnet		1000.00 219	1000.00 218	1000.00 240	1000.00 249	1000.00 254	1000.00 199	1000.00 303	1000.00 213	1000.00 249	1000.00 213	1000.00 295	1000.00 245	1000.00 225	1000.00 279	1000.00 276

USDC		1000.00 219	1000.00 218	1000.00 240	1000.00 249	1000.00 254	1000.00 199	1000.00 303	1000.00 213	1000.00 249	1000.00 213	1000.00 295	1000.00 245	1000.00 225	1000.00 279	1000.00 276

TinyColmap		1000.00 219	1000.00 218	1000.00 240	1000.00 249	1000.00 254	1000.00 199	1000.00 303	1000.00 213	1000.00 249	1000.00 213	1000.00 295	1000.00 245	1000.00 225	1000.00 279	1000.00 276

COLMAP_ROB	2144.59 11	1658.33 234	1869.33 236	1025.33 244	1030.00 253	1023.00 258	5311.00 253	359.00 250	3044.00 254	937.00 245	2892.00 253	332.00 244	1440.00 255	2312.00 255	607.00 239	613.00 240
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
F-COLMAP		1878.17 235	2113.11 238	1173.33 248	1231.00 254	1174.00 259	6297.00 256	392.00 255	3356.00 257	1087.00 255	3082.00 254	361.00 248	1670.00 257	2523.00 257	689.00 246	676.00 245

OpenMVS_ROB	1936.51 10	1959.51 236	2224.88 240	1163.39 247	1253.91 255	1434.22 262	7065.71 260	272.76 240	2472.29 251	1647.54 285	3538.72 257	200.37 226	1496.48 256	2575.17 258	997.45 275	559.48 237

Patchmtry		1090.75 224	1198.88 226	766.38 235	1290.90 256	485.90 213	2423.98 235	1267.30 307	1297.17 222	923.90 243	923.40 208	1215.54 300	990.23 240	667.90 208	779.80 257	823.02 255

PatchT		856.34 211	860.99 204	842.38 236	1290.90 256	880.90 247	790.30 184	1267.30 307	579.21 182	923.90 243	567.40 178	662.54 279	990.23 240	887.56 217	779.80 257	656.02 241

K. test v3		877.74 212	980.16 215	570.46 219	1316.85 258	813.15 244	2565.52 239	103.78 209	1509.49 235	548.33 223	1258.90 224	219.93 234	587.82 224	1102.37 239	196.30 207	310.42 221

PLC	2858.82 16	2192.92 239	2474.00 242	1349.67 250	1407.00 259	1356.00 261	7164.00 261	475.00 267	3970.00 261	1237.00 262	3765.00 260	451.00 255	1891.00 263	3006.00 261	791.00 262	802.00 250
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
CMPMVS	2623.62 15	1983.08 237	2156.14 239	1463.89 258	1414.80 260	1517.00 264	5239.20 252	867.40 294	3310.30 256	1128.70 257	3489.90 256	366.75 249	2030.20 269	2427.60 256	1160.60 288	844.46 258
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
ZD-MVS					1584.00 261	1821.00 284		378.00 253	3721.00 259	1231.00 260	1833.00 241	321.00 243	1224.00 253	2103.00 254	692.00 250

Vis-MVSNet		2877.42 252	3170.00 255	1999.67 273	1673.00 262	2042.00 290	8593.00 274	474.00 266	6452.00 286	1268.00 263	5125.00 274	339.00 245	3004.00 287	4222.00 277	384.00 234	953.00 269
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
PCF-MVS	4335.85 20	2272.23 241	2597.03 244	1297.84 249	1701.20 263	1332.37 260	8105.11 271	451.45 263	4031.84 262	1099.10 256	3966.50 261	467.45 256	1734.05 259	2701.68 260	848.94 266	827.11 256
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
test_0728_SECOND				1451.45 255	1725.60 264	1598.35 268	9203.30 277	315.86 244					2023.43 266	3973.88 271	620.04 242	732.56 247

test0726					1725.60 264	1598.35 268	9203.30 277	315.86 244	5016.02 273	1363.85 265	4894.28 271	387.23 250

SD-MVS		2654.53 248	3055.56 253	1451.45 255	1725.60 264	1598.35 268	9203.30 277	315.86 244	5016.02 273	1363.85 265	4894.28 271	387.23 250	2023.43 266	3973.88 271	620.04 242	732.56 247
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
3Dnovator	2482.06 14	2531.17 245	2839.56 248	1606.00 259	1732.00 267	1557.00 266	8375.00 273	483.00 268	4370.00 267	1371.00 268	4200.00 262	350.00 246	2207.00 270	3877.00 270	798.00 263	1054.00 280

LF4IMVS		2699.50 250	3049.67 252	1649.00 261	1755.00 268	1689.00 275	8330.00 272	464.00 265	4997.00 272	1528.00 271	4763.00 270	568.00 265	2296.00 272	4215.00 276	827.00 265	962.00 270

DPM-MVS		3268.00 256	3762.89 259	1783.33 266	1756.00 269	1806.00 282	12319.00 293	307.00 242	6319.00 284	1557.00 276	5763.00 277	302.00 241	2609.00 279	5061.00 282	482.00 237	935.00 267

OPM-MVS		3268.00 256	3762.89 259	1783.33 266	1756.00 269	1806.00 282	12319.00 293	307.00 242	6319.00 284	1557.00 276	5763.00 277	302.00 241	2609.00 279	5061.00 282	482.00 237	935.00 267
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
OpenMVS	2352.88 13	2263.08 240	2530.89 243	1459.67 257	1767.00 271	1591.00 267	7932.00 269	399.00 256	3643.00 258	1176.00 258	3569.00 258	297.00 239	1927.00 265	3302.00 263	693.00 251	861.00 259

tpmrst		2557.50 246	2847.12 249	1688.66 262	1784.08 272	1778.25 281	7445.50 267	342.14 247	4471.54 268	1534.55 272	4382.10 266	530.10 262	2361.21 273	4142.81 274	991.22 274	926.51 265

AdaColmap		2570.77 247	2948.61 250	1437.24 254	1873.64 273	1526.60 265	7819.77 268	373.97 251	4970.45 271	1479.29 270	4648.46 268	525.80 261	1904.97 264	4150.42 275	695.69 252	880.14 263

SteuartSystems-ACMMP		2891.50 253	3284.78 256	1711.67 263	1954.00 274	1655.00 274	10117.00 290	445.00 262	5102.00 276	1375.00 269	5126.00 275	351.00 247	2638.00 283	4402.00 278	691.00 249	842.00 257
Skip Steuart: Steuart Systems R&D Blog.
ITE_SJBPF				2014.00 274	1998.00 275	1992.00 288		701.00 290	5989.00 278	1812.00 289	3612.00 259	650.00 273	2852.00 286	4601.00 280	1195.00 289	1198.00 286

tpm2		3617.85 260	4007.23 262	2449.73 280	2012.71 276	1698.05 276	7351.19 263	869.29 295	6132.06 279	1588.28 279	8007.42 295	1281.09 301	3888.11 299	7472.04 300	1351.00 290	1763.02 296

tpm cat1		3617.85 260	4007.23 262	2449.73 280	2012.71 276	1698.05 276	7351.19 263	869.29 295	6132.06 279	1588.28 279	8007.42 295	1281.09 301	3888.11 299	7472.04 300	1351.00 290	1763.02 296

CostFormer		3617.85 260	4007.23 262	2449.73 280	2012.71 276	1698.05 276	7351.19 263	869.29 295	6132.06 279	1588.28 279	8007.42 295	1281.09 301	3888.11 299	7472.04 300	1351.00 290	1763.02 296

tpm		3617.85 260	4007.23 262	2449.73 280	2012.71 276	1698.05 276	7351.19 263	869.29 295	6132.06 279	1588.28 279	8007.42 295	1281.09 301	3888.11 299	7472.04 300	1351.00 290	1763.02 296

CHOSEN 280x420		2340.81 242	2643.03 245	1434.14 251	2025.55 280	1629.36 271	6542.40 257	412.49 257	4219.70 264	1547.02 273	4328.52 263	650.74 274	1798.26 260	3333.17 264	727.72 253	874.79 260

CHOSEN 1792x2688		2340.81 242	2643.03 245	1434.14 251	2025.55 280	1629.36 271	6542.40 257	412.49 257	4219.70 264	1547.02 273	4328.52 263	650.74 274	1798.26 260	3333.17 264	727.72 253	874.79 260

HyFIR lowres test		2340.81 242	2643.03 245	1434.14 251	2025.55 280	1629.36 271	6542.40 257	412.49 257	4219.70 264	1547.02 273	4328.52 263	650.74 274	1798.26 260	3333.17 264	727.72 253	874.79 260

DVP-MVS++		3981.10 266	4731.32 271	1730.42 264	2191.51 283	1949.98 286	16473.90 302	355.33 248	7172.90 295	1622.98 283	7879.79 293	434.33 253	2428.11 275	5762.12 285	689.04 247	813.18 253

DVP-MVS		3981.10 266	4731.32 271	1730.42 264	2191.51 283	1949.98 286	16473.90 302	355.33 248	7172.90 295	1622.98 283	7879.79 293	434.33 253	2428.11 275	5762.12 285	689.04 247	813.18 253
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
3Dnovator+	3414.41 17	3146.67 254	3537.00 257	1975.67 270	2310.00 285	2005.00 289	10100.00 289	626.00 287	5753.00 277	1803.00 288	5179.00 276	487.00 257	2622.00 281	4550.00 279	1025.00 283	1300.00 287

TSAR-MVS + MP.		3528.01 259	4065.89 266	1914.35 269	2349.10 286	2141.30 291	12362.70 295	417.60 261	6717.80 290	1759.40 287	6497.50 280	518.18 260	2629.38 282	5164.32 284	806.40 264	972.38 272
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
DeepPCF-MVS	3452.42 18	2670.71 249	3021.57 251	1618.12 260	2377.67 287	1751.39 280	8915.70 276	567.44 282	4569.74 269	1236.84 261	4615.63 267	513.23 259	2291.32 271	3515.48 267	882.39 268	811.66 252

GST-MVS		4000.00 268	4533.33 269	2400.00 279	2400.00 288	2400.00 294	7200.00 262	2400.00 311	7200.00 297	2400.00 299	7200.00 287	2400.00 305	2400.00 274	7200.00 298	2400.00 302	2400.00 301

MVS_111021_HR		3742.80 264	4330.34 267	1980.20 271	2484.31 289	2259.52 293	14973.80 300	515.90 281	6500.13 287	1949.21 290	6146.89 279	535.66 263	2593.66 278	4880.76 281	986.37 273	1087.43 281

DeepC-MVS	3917.13 19	3155.06 255	3601.83 258	1814.72 268	2515.52 290	1941.53 285	10432.50 291	589.42 283	4789.45 270	1298.65 264	7677.31 292	578.35 266	2589.53 277	3611.78 269	923.52 271	913.10 264
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
TAPA-MVS	6309.84 21	3374.90 258	3806.99 261	2078.63 275	2535.47 291	2499.25 300	8816.16 275	456.05 264	6255.60 283	1664.52 286	6704.88 282	629.95 272	2768.38 284	6343.93 296	856.35 267	968.25 271
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
FOURS1					2643.17 292	2465.14 295	13996.40 297	493.26 269	7619.38 298	2107.24 291

MSC_two_6792asdad				2237.56 276	2643.17 292	2465.14 295		493.26 269					3088.29 292	6075.14 292	1078.39 284	1159.26 282

No_MVS				2237.56 276	2643.17 292	2465.14 295		493.26 269					3088.29 292	6075.14 292	1078.39 284	1159.26 282

test_one_0601					2643.17 292	2465.14 295		493.26 269	7619.38 298	2107.24 291	7416.93 289	610.24 269

SED-MVS		4062.74 269	4671.13 270	2237.56 276	2643.17 292	2465.14 295	13996.40 297	493.26 269	7619.38 298	2107.24 291	7416.93 289	610.24 269	3088.29 292	6075.14 292	1078.39 284	1159.26 282

IU-MVS					2725.60 297	2598.35 301		515.86 277	7016.02 291	2363.85 295				5973.88 288	1620.04 296	1732.56 292

OPU-MVS				2451.45 284	2725.60 297	2598.35 301	9203.30 277				6894.28 283	887.23 287	3023.43 288	5973.88 288	1620.04 296	1732.56 292

test_241102_ONE					2725.60 297	2598.35 301		515.86 277	7016.02 291	2363.85 295	6894.28 283	887.23 287	3023.43 288

MSP-MVS		4296.20 270	4911.12 274	2451.45 284	2725.60 297	2598.35 301	16203.30 301	515.86 277	7016.02 291	2363.85 295	6894.28 283	887.23 287	3023.43 288	5973.88 288	1620.04 296	1732.56 292
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
MVS-HIRNet		2125.39 238	2452.68 241	1143.53 246	2938.33 301	1446.92 263	6083.19 255	391.74 254	3801.71 260	1202.10 259	3439.72 255	492.73 258	1304.35 254	3048.25 262	676.32 245	679.32 246

EGC-MVSNET		2819.75 251	3096.89 254	1988.33 272	3105.00 302	2241.00 292	9480.00 281	640.00 288	4209.00 263	1583.00 278	4740.00 269	547.00 264	2797.00 285	2644.00 259	924.00 272	927.00 266

MAR-MVS		3973.16 265	4387.92 268	2728.86 286	3345.27 303	3341.39 307	11403.90 292	798.76 292	6555.62 289	2569.29 300	6514.86 281	834.97 286	3237.43 296	5891.08 287	1577.54 295	1607.76 288
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		4380.83 271	4906.56 273	2803.67 287	3844.00 304	3116.00 306	13454.00 296	901.00 299	6511.00 288	2794.00 301	7365.00 288	754.00 283	3634.00 297	6622.00 297	1914.00 301	1661.00 291

CLD-MVS		7338.25 273	8341.00 276	4330.00 289	4902.00 305	4991.00 308	23318.00 305	728.00 291	14437.00 312	4378.00 304	13379.00 307	824.00 285	5708.00 303	11429.00 313	1674.00 300	2291.00 300
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
OMC-MVS		5022.26 272	5748.82 275	2842.58 288	4905.27 306	3101.27 305	14933.60 299	812.24 293	9278.40 302	2959.29 302	8800.17 299	1092.24 299	3806.30 298	7568.54 304	1389.60 294	1620.18 290

LS3D		7684.71 274	8776.23 277	4410.16 290	5298.55 307	5631.53 309	34329.90 307	1504.57 309	11554.00 311	3896.41 303	15111.00 308	812.19 284	5985.63 304	3516.20 268	2963.23 303	1613.31 289

MVE	10021.00 22	10550.67 282	10002.44 285	12195.33 299	6242.00 308	8768.00 311	30896.00 306	4451.00 312	10331.00 310	6247.00 305	18296.00 309	283.00 238	21484.00 313	7364.00 299	5912.00 305	6334.00 303
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CNLPA		10738.67 283	11772.44 286	7637.33 291	9120.00 309	8206.00 310	22252.00 304	2010.00 310	24984.00 313	7458.00 306	22596.00 310	2940.00 306	10260.00 312	11100.00 312	3492.00 304	4446.00 302

ZNCC-MVS		9999.00 275	9999.00 278	9999.00 292	9999.00 310	9999.00 312	9999.00 282	9999.00 315	9999.00 303	9999.00 307	9999.00 300	9999.00 308	9999.00 305	9999.00 305	9999.00 306	9999.00 304

patch_mono-2		10000.00 276	10000.00 279	10000.00 293	10000.00 311	10000.00 313	10000.00 283	10000.00 316	10000.00 304	10000.00 308	10000.00 301	10000.00 309	10000.00 306	10000.00 306	10000.00 307	10000.00 305

dcpmvs_2		10000.00 276	10000.00 279	10000.00 293	10000.00 311	10000.00 313	10000.00 283	10000.00 316	10000.00 304	10000.00 308	10000.00 301	10000.00 309	10000.00 306	10000.00 306	10000.00 307	10000.00 305

DCPMVS		10000.00 276	10000.00 279	10000.00 293	10000.00 311	10000.00 313	10000.00 283	10000.00 316	10000.00 304	10000.00 308	10000.00 301	10000.00 309	10000.00 306	10000.00 306	10000.00 307	10000.00 305

UA-Net		10000.00 276	10000.00 279	10000.00 293	10000.00 311	10000.00 313	10000.00 283	10000.00 316	10000.00 304	10000.00 308	10000.00 301	10000.00 309	10000.00 306	10000.00 306	10000.00 307	10000.00 305

uncertanet		10000.00 276	10000.00 279	10000.00 293	10000.00 311	10000.00 313	10000.00 283	10000.00 316	10000.00 304	10000.00 308	10000.00 301	10000.00 309	10000.00 306	10000.00 306	10000.00 307	10000.00 305

uanet		10000.00 276	10000.00 279	10000.00 293	10000.00 311	10000.00 313	10000.00 283	10000.00 316	10000.00 304	10000.00 308	10000.00 301	10000.00 309	10000.00 306	10000.00 306	10000.00 307	10000.00 305

LTVRE_ROB	20565.47 23	23378.08 284	22805.00 287	25097.33 300	15500.00 317	19201.00 319	42712.00 308	6055.00 313	38388.00 314	16926.00 314	38534.00 311	7071.00 307	35653.00 314	29475.00 314	10584.00 313	20438.00 312
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		32606.17 285	34443.44 288	27094.33 301	29249.00 318	25246.00 320	51144.00 309	6705.00 314	42886.00 315	22888.00 315	48534.00 312	13263.00 315	37507.00 315	79298.00 315	16024.00 314	18530.00 311

114514_t		99999.00 286	99999.00 289	99999.00 302	99999.00 319	99999.00 321	99999.00 310	99999.00 322	99999.00 316	99999.00 316	99999.00 313	99999.00 316	99999.00 316	99999.00 316	99999.00 315	99999.00 313

PHI-MVS		99999.00 286	99999.00 289	99999.00 302	99999.00 319	99999.00 321	99999.00 310	99999.00 322	99999.00 316	99999.00 316	99999.00 313	99999.00 316	99999.00 316	99999.00 316	99999.00 315	99999.00 313

XVG-OURS-SEG-HR		999999.00 290	999999.00 291	999999.00 304	999999.00 321	999999.00 323	999999.00 312	999999.00 324	999999.00 318	999999.00 318	999999.00 315	999999.00 318	999999.00 318	999999.00 318	999999.00 317	999999.00 315

XVG-OURS		999999.00 290	999999.00 291	999999.00 304	999999.00 321	999999.00 323	999999.00 312	999999.00 324	999999.00 318	999999.00 318	999999.00 315	999999.00 318	999999.00 318	999999.00 318	999999.00 317	999999.00 315

XVG-ACMP-BASELINE		999999.00 290	999999.00 291	999999.00 304	999999.00 321	999999.00 323	999999.00 312	999999.00 324	999999.00 318	999999.00 318	999999.00 315	999999.00 318	999999.00 318	999999.00 318	999999.00 317	999999.00 315

MVSMamba_PlusPlus		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

MGCFI-Net		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

sasdasda		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

dmvs_re		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

SDMVSNet		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

dmvs_testset		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

sd_testset		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

balanced_conf03		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

MonoMVSNet		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

test2506		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

test1111		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

ECVR-MVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

test_blank		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

tt0805		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

eth-test					10000000.00 324

Anonymous20240521		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

cl22		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

miper_ehance_all_eth		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

miper_enhance_ethall		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

cl____		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

DIV-MVS_self_test		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

eth_miper_zixun_eth		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

ET-MVSNet_ETH3D		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

UniMVSNet_ETH3D		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

miper_lstm_enhance		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

D2MVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

test_yl		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

thisisatest0530		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

Anonymous20240529		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

Anonymous202405211		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

DCV-MVSNet		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

tttt0517		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

our_test_3		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

thisisatest0515		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

ppachtmachnet_test		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

SMA-MVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318
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		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part2					10000000.00 324	10000000.00 326				10000000.00 321

thres100view900		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

tfpnnormal		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

tfpn200view9		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

c3_l		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

IterMVS-SCA-FT		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

pmmvs6		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

pmmvs5		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

Anonymous20231211		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

pmmvs-eth3d		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

Anonymous20231206		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

SCA		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

Patchmatch-test		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

Patchmatch-RL test		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

canonicalmvs		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

anonymousdsp		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

FIs		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

FC-MVSNet-test		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

sosnet-low-res		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

AllTest		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

TestCases				10000000.00 307	10000000.00 324	10000000.00 326		10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

RRT-MVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

mamv4		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

HPM-MVS++		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

XVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

pm-mvs1		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

X-MVStestdata		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

APDe-MVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
APD-MVS_3200maxsize		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

pmmvs4		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

test-LLR		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

TESTMET0.1,1		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

test-mter		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

testgi		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

test20.03		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

thres600view7		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

MP-MVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

thres400		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

test123		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

thres200		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

test0.0.03 1		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

pmmvs3		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

EMVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

E-PMN		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

PGM-MVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

MCST-MVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

MVS_Test		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

PMMVS2		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

PM-MVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

HQP_MVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

plane_prior7					10000000.00 324	10000000.00 326

plane_prior6					10000000.00 324	10000000.00 326						10000000.00 321

plane_prior1					10000000.00 324

mPP-MVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

mvsmamba		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

HPM-MVS_fast		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

HPM-MVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
LPG-MVS_test		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

LGP-MVS_train				10000000.00 307	10000000.00 324	10000000.00 326		10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

EPNet_dtu		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP-NCC					10000000.00 324		10000000.00 315		10000000.00 321	10000000.00 321

ACMP_Plane					10000000.00 324		10000000.00 315		10000000.00 321	10000000.00 321

CNVR-MVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

NCCC		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

CP-MVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

NP-MVS					10000000.00 324	10000000.00 326					10000000.00 318

CPTT-MVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

HQP-MVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

IS-MVSNet		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

PAPM_NR		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

PAPR		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

Vis-MVSNet (Re-imp)		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

PatchMatch-RL		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

TDRefinement		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

EPP-MVSNet		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

PMMVS		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

PAPM		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

ACMMP		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318
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		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

wuyk23d		10000000.00 293	10000000.00 296	10000000.00 307	10000000.00 324	10000000.00 326	10000000.00 315	10000000.00 327	10000000.00 321	10000000.00 321	10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

APD-MVS		1000000000.00 402	1000000000.00 405	1000000000.00 418	1000000000.00 443	1000000000.00 443	1000000000.00 429	1000000000.00 443	1000000000.00 436	1000000000.00 437	1000000000.00 434	1000000000.00 439	1000000000.00 437	1000000000.00 436	1000000000.00 435	1000000000.00 433
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
WAC-MVS						248.46 188								422.23 181

PC_three_1452									7619.38 298	2107.24 291	7416.93 289	610.24 269	3088.29 292	6075.14 292	1078.39 284	1159.26 282

test_241102_TWO								515.86 277	7016.02 291	2363.85 295	6894.28 283	887.23 287	3023.43 288	5973.88 288	1620.04 296	1732.56 292

test_0728_THIRD									5016.02 273	1363.85 265	4894.28 271	387.23 250	2023.43 266	3973.88 271	620.04 242	732.56 247

GSMVS																10000000.00 318

sam_mvs1												10000000.00 321				10000000.00 318

sam_mvs												10000000.00 321

MTGPA								10000000.00 327

test_post1							10000000.00 315				10000000.00 318	10000000.00 321	10000000.00 321	10000000.00 321

test_post											10000000.00 318	10000000.00 321	10000000.00 321

patchmatchnet-post											10000000.00 318	10000000.00 321	10000000.00 321

MTMP							10000000.00 315	10000000.00 327

test9_res														0.00 1	0.00 1	0.00 1

agg_prior2														0.00 1	0.00 1	0.00 1

test_prior4						0.00 1	0.00 1

test_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

testdata2													0.00 1	0.00 1

segment_acmp												0.00 1

testdata1							0.00 1		0.00 1

plane_prior5								10000000.00 327					10000000.00 321	10000000.00 321	10000000.00 320	10000000.00 318

plane_prior4											10000000.00 318

plane_prior3						10000000.00 326			10000000.00 321	10000000.00 321

plane_prior2							10000000.00 315		10000000.00 321

plane_prior						1.00 78	2.00 116		2.00 117						2.00 115

n2								14.20 158

nn								1.42 86

door-mid								1.42 86

test11								1.00 79

door								99.00 206

HQP5-MVS						10000000.00 326

BP-MVS														10000000.00 321

HQP4-MVS										10000000.00 321			10000000.00 321			10000000.00 318

HQP3-MVS								10000000.00 327							10000000.00 320

HQP2-MVS												10000000.00 321

MDTV_nov1_ep13_2view						9.99 138	9.99 136		9.99 137	9.99 136		9.99 138		9.99 134		9.99 137

ACMMP++_ref															10000000.00 320

ACMMP++															10000000.00 320

Test By Simon												990.00 291

High-resolution multi-view benchmark