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

alignmvs		2.00 94	2.00 95	2.00 100	2.00 108	2.00 108	2.00 106	2.00 111	2.00 107	2.00 106	2.00 104	2.00 106	2.00 107	2.00 105	2.00 105	2.00 105

nrg030		2.00 94	2.00 95	2.00 100	2.00 108	2.00 108	2.00 106	2.00 111	2.00 107	2.00 106	2.00 104	2.00 106	2.00 107	2.00 105	2.00 105	2.00 105

LFMVS		2.00 94	2.00 95	2.00 100	2.00 108	2.00 108	2.00 106	2.00 111	2.00 107	2.00 106	2.00 104	2.00 106	2.00 107	2.00 105	2.00 105	2.00 105

VDD-MVS		2.00 94	2.00 95	2.00 100	2.00 108	2.00 108	2.00 106	2.00 111	2.00 107	2.00 106	2.00 104	2.00 106	2.00 107	2.00 105	2.00 105	2.00 105

VDDNet		2.00 94	2.00 95	2.00 100	2.00 108	2.00 108	2.00 106	2.00 111	2.00 107	2.00 106	2.00 104	2.00 106	2.00 107	2.00 105	2.00 105	2.00 105

VPNet		2.00 94	2.00 95	2.00 100	2.00 108	2.00 108	2.00 106	2.00 111	2.00 107	2.00 106	2.00 104	2.00 106	2.00 107	2.00 105	2.00 105	2.00 105

VNet		2.00 94	2.00 95	2.00 100	2.00 108	2.00 108	2.00 106	2.00 111	2.00 107	2.00 106	2.00 104	2.00 106	2.00 107	2.00 105	2.00 105	2.00 105

VPA-MVSNet		2.00 94	2.00 95	2.00 100	2.00 108	2.00 108	2.00 106	2.00 111	2.00 107	2.00 106	2.00 104	2.00 106	2.00 107	2.00 105	2.00 105	2.00 105

cascas		2.00 94	2.00 95	2.00 100	2.00 108	2.00 108	2.00 106	2.00 111	2.00 107	2.00 106	2.00 104	2.00 106	2.00 107	2.00 105	2.00 105	2.00 105

UnsupCasMVSNet_eth		5.90 103	5.90 104	5.90 109	5.90 117	5.90 117	5.90 116	5.90 123	5.90 117	5.90 115	5.90 113	5.90 117	5.90 116	5.90 114	5.90 117	5.90 117

UnsupCasMVSNet_bld		5.90 103	5.90 104	5.90 109	5.90 117	5.90 117	5.90 116	5.90 123	5.90 117	5.90 115	5.90 113	5.90 117	5.90 116	5.90 114	5.90 117	5.90 117

WTY-MVS		5.90 103	5.90 104	5.90 109	5.90 117	5.90 117	5.90 116	5.90 123	5.90 117	5.90 115	5.90 113	5.90 117	5.90 116	5.90 114	5.90 117	5.90 117

HY-MVS	5.90 1	5.90 103	5.90 104	5.90 109	5.90 117	5.90 117	5.90 116	5.90 123	5.90 117	5.90 115	5.90 113	5.90 117	5.90 116	5.90 114	5.90 117	5.90 117

sss		5.90 103	5.90 104	5.90 109	5.90 117	5.90 117	5.90 116	5.90 123	5.90 117	5.90 115	5.90 113	5.90 117	5.90 116	5.90 114	5.90 117	5.90 117

Test_1112_low_res		5.90 103	5.90 104	5.90 109	5.90 117	5.90 117	5.90 116	5.90 123	5.90 117	5.90 115	5.90 113	5.90 117	5.90 116	5.90 114	5.90 117	5.90 117

1112_ss		5.90 103	5.90 104	5.90 109	5.90 117	5.90 117	5.90 116	5.90 123	5.90 117	5.90 115	5.90 113	5.90 117	5.90 116	5.90 114	5.90 117	5.90 117

ab-mvs-re		5.90 103	5.90 104	5.90 109	5.90 117	5.90 117	5.90 116	5.90 123	5.90 117	5.90 115	5.90 113	5.90 117	5.90 116	5.90 114	5.90 117	5.90 117

ab-mvs		5.90 103	5.90 104	5.90 109	5.90 117	5.90 117	5.90 116	5.90 123	5.90 117	5.90 115	5.90 113	5.90 117	5.90 116	5.90 114	5.90 117	5.90 117

CDPH-MVS		6.66 112	6.66 113	6.66 118	6.66 126	6.66 126	6.66 125	6.66 132	6.66 126	6.66 124	6.66 122	6.66 126	6.66 125	6.66 123	6.66 126	6.66 126

MDTV_nov1_ep13			9.99 114		9.99 127	9.99 128	9.99 126	9.99 134	9.99 127	9.99 126	9.99 123	9.99 128	9.99 127	9.99 124	9.99 128

xiu_mvs_v1_base_debu		10.28 113	10.28 115	10.28 120	10.28 128	10.28 130	10.28 128	10.28 135	10.28 129	10.28 128	10.28 124	10.28 130	10.28 128	10.28 126	10.28 129	10.28 128

xiu_mvs_v2_base		10.28 113	10.28 115	10.28 120	10.28 128	10.28 130	10.28 128	10.28 135	10.28 129	10.28 128	10.28 124	10.28 130	10.28 128	10.28 126	10.28 129	10.28 128

xiu_mvs_v1_base		10.28 113	10.28 115	10.28 120	10.28 128	10.28 130	10.28 128	10.28 135	10.28 129	10.28 128	10.28 124	10.28 130	10.28 128	10.28 126	10.28 129	10.28 128

xiu_mvs_v1_base_debi		10.28 113	10.28 115	10.28 120	10.28 128	10.28 130	10.28 128	10.28 135	10.28 129	10.28 128	10.28 124	10.28 130	10.28 128	10.28 126	10.28 129	10.28 128

cdsmvs_eth3d_5k		10.28 113	10.28 115	10.28 120	10.28 128	10.28 130	10.28 128	10.28 135	10.28 129	10.28 128	10.28 124	10.28 130	10.28 128	10.28 126	10.28 129	10.28 128

pcd_1.5k_mvsjas		10.28 113	10.28 115	10.28 120	10.28 128	10.28 130	10.28 128	10.28 135	10.28 129	10.28 128	10.28 124	10.28 130	10.28 128	10.28 126	10.28 129	10.28 128

PS-MVSNAJss		10.28 113	10.28 115	10.28 120	10.28 128	10.28 130	10.28 128	10.28 135	10.28 129	10.28 128	10.28 124	10.28 130	10.28 128	10.28 126	10.28 129	10.28 128

PS-MVSNAJ		10.28 113	10.28 115	10.28 120	10.28 128	10.28 130	10.28 128	10.28 135	10.28 129	10.28 128	10.28 124	10.28 130	10.28 128	10.28 126	10.28 129	10.28 128

jajsoiax		10.28 113	10.28 115	10.28 120	10.28 128	10.28 130	10.28 128	10.28 135	10.28 129	10.28 128	10.28 124	10.28 130	10.28 128	10.28 126	10.28 129	10.28 128

mvs_tets		10.28 113	10.28 115	10.28 120	10.28 128	10.28 130	10.28 128	10.28 135	10.28 129	10.28 128	10.28 124	10.28 130	10.28 128	10.28 126	10.28 129	10.28 128

dp		87.20 132	113.80 136	7.42 119	10.50 138	8.88 127	298.82 153	2.70 120	510.35 170	7.79 125	172.93 146	3.37 115	9.16 126	14.00 137	3.71 115	4.23 115

SR-MVS-dyc-post		11.55 123	11.55 125	11.55 132	11.55 139	11.55 141	11.55 138	11.55 147	11.55 139	11.55 139	11.55 134	11.55 141	11.55 138	11.55 136	11.55 139	11.55 138

test_method		18.29 125	20.89 127	10.50 130	15.00 140	13.00 142	55.00 145	3.00 121	34.00 142	11.50 138	32.50 136	5.00 116	13.50 139	27.00 140	5.00 116	5.00 116

XXY-MVS		15.00 124	15.00 126	15.00 133	15.00 140	15.00 143	15.00 139	15.00 149	15.00 140	15.00 141	15.00 135	15.00 145	15.00 140	15.00 138	15.00 141	15.00 140

GeoE		19.41 126	22.09 128	11.37 131	17.21 142	11.30 140	50.50 144	4.30 122	33.60 141	11.70 140	44.50 141	7.30 127	18.90 141	22.60 139	7.10 127	3.90 114

BH-w/o		40.00 127	40.00 129	40.00 135	40.00 143	40.00 144	40.00 140	40.00 166	40.00 143	40.00 143	40.00 137	40.00 162	40.00 143	40.00 141	40.00 155	40.00 151

BH-untuned		40.00 127	40.00 129	40.00 135	40.00 143	40.00 144	40.00 140	40.00 166	40.00 143	40.00 143	40.00 137	40.00 162	40.00 143	40.00 141	40.00 155	40.00 151

BH-RMVSNet		40.00 127	40.00 129	40.00 135	40.00 143	40.00 144	40.00 140	40.00 166	40.00 143	40.00 143	40.00 137	40.00 162	40.00 143	40.00 141	40.00 155	40.00 151

TR-MVS		40.00 127	40.00 129	40.00 135	40.00 143	40.00 144	40.00 140	40.00 166	40.00 143	40.00 143	40.00 137	40.00 162	40.00 143	40.00 141	40.00 155	40.00 151

GBi-Net		44.67 131	49.24 133	30.96 134	47.53 147	47.57 148	126.09 146	8.00 133	76.99 147	26.09 142	73.50 143	11.27 140	30.55 142	61.12 145	12.58 140	14.75 139

MTAPA		833442.10 273	1111233.77 279	67.09 141	65.59 148	64.81 151	284.50 150	10000000.00 311	219.97 153	59.62 149	229.89 157	12.72 142	103.00 162	203.67 163	27.93 142	33.46 141

MP-MVS-pluss		833433.63 272	1111219.60 278	75.70 145	74.28 149	73.29 152	284.50 150	11.35 145	238.58 154	65.86 150	255.35 162	14.55 143	115.69 164	10000000.00 305	31.94 143	38.12 149
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
ACMMP_NAP		118.81 138	133.18 140	75.70 145	74.28 149	73.29 152	284.50 150	11.35 145	238.58 154	65.86 150	255.35 162	14.55 143	115.69 164	222.18 164	31.94 143	38.12 149

CANet		110.62 135	124.04 137	70.34 142	82.03 151	74.27 154	325.54 154	25.25 152	207.16 150	69.28 152	194.38 147	27.53 148	95.79 156	147.76 150	37.43 145	40.97 155

CANet_DTU		110.62 135	124.04 137	70.34 142	82.03 151	74.27 154	325.54 154	25.25 152	207.16 150	69.28 152	194.38 147	27.53 148	95.79 156	147.76 150	37.43 145	40.97 155

UGNet		110.62 135	124.04 137	70.34 142	82.03 151	74.27 154	325.54 154	25.25 152	207.16 150	69.28 152	194.38 147	27.53 148	95.79 156	147.76 150	37.43 145	40.97 155
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		88.14 133	98.62 134	56.70 139	98.14 154	56.07 149	246.79 148	15.37 150	148.06 148	50.77 147	143.13 144	23.35 146	62.65 147	93.26 146	68.71 163	51.38 161

N_pmnet		88.14 133	98.62 134	56.70 139	98.14 154	56.07 149	246.79 148	15.37 150	148.06 148	50.77 147	143.13 144	23.35 146	62.65 147	93.26 146	68.71 163	51.38 161

DSMNet-mixed		131.33 146	143.00 148	96.33 157	99.00 156	81.00 157	201.00 147	45.00 171	335.00 166	99.00 165	251.00 161	38.00 161	110.00 163	120.00 149	99.00 168	98.00 165

FMVSNet5		124.76 139	140.93 141	76.26 147	107.44 157	100.17 161	329.88 157	27.12 158	259.44 159	74.30 155	204.34 150	30.74 151	92.41 149	196.98 153	38.15 148	36.19 142

test1		124.76 139	140.93 141	76.26 147	107.44 157	100.17 161	329.88 157	27.12 158	259.44 159	74.30 155	204.34 150	30.74 151	92.41 149	196.98 153	38.15 148	36.19 142

FMVSNet3		124.76 139	140.93 141	76.26 147	107.44 157	100.17 161	329.88 157	27.12 158	259.44 159	74.30 155	204.34 150	30.74 151	92.41 149	196.98 153	38.15 148	36.19 142

FMVSNet2		124.76 139	140.93 141	76.26 147	107.44 157	100.17 161	329.88 157	27.12 158	259.44 159	74.30 155	204.34 150	30.74 151	92.41 149	196.98 153	38.15 148	36.19 142

FMVSNet1		124.76 139	140.93 141	76.26 147	107.44 157	100.17 161	329.88 157	27.12 158	259.44 159	74.30 155	204.34 150	30.74 151	92.41 149	196.98 153	38.15 148	36.19 142

MIMVSNet1		124.76 139	140.93 141	76.26 147	107.44 157	100.17 161	329.88 157	27.12 158	259.44 159	74.30 155	204.34 150	30.74 151	92.41 149	196.98 153	38.15 148	36.19 142

MIMVSNet		124.76 139	140.93 141	76.26 147	107.44 157	100.17 161	329.88 157	27.12 158	259.44 159	74.30 155	204.34 150	30.74 151	92.41 149	196.98 153	38.15 148	36.19 142

PVSNet_Blended_VisFu		136.90 147	155.40 149	81.40 154	111.00 164	96.20 158	407.00 164	25.90 155	251.60 156	85.10 162	240.50 158	37.00 158	99.90 159	199.80 160	40.70 159	48.10 158

PVSNet_BlendedMVS		136.90 147	155.40 149	81.40 154	111.00 164	96.20 158	407.00 164	25.90 155	251.60 156	85.10 162	240.50 158	37.00 158	99.90 159	199.80 160	40.70 159	48.10 158

PVSNet_Blended		136.90 147	155.40 149	81.40 154	111.00 164	96.20 158	407.00 164	25.90 155	251.60 156	85.10 162	240.50 158	37.00 158	99.90 159	199.80 160	40.70 159	48.10 158

FE-MVS		207.10 150	234.26 152	125.61 158	180.34 167	153.23 168	635.64 171	30.05 165	378.38 167	127.68 166	377.08 164	48.95 166	154.43 166	266.67 165	63.56 162	69.18 163

DP-MVS		264.78 152	296.02 154	171.04 160	191.70 168	183.96 169	827.10 177	78.36 176	438.24 168	176.64 168	435.12 165	65.04 169	230.52 170	334.02 167	117.96 172	98.64 166

tmp_tt		371.08 156	412.78 157	246.00 167	231.00 169	197.00 171	1293.00 199	376.00 236	756.00 186	609.00 214	71.00 142	106.00 182	195.00 167	102.00 148	171.00 186	346.00 210

FA-MVS(test-final)		261.15 151	293.29 153	164.72 159	236.23 170	199.99 172	800.05 176	42.35 170	475.87 169	155.47 167	470.67 166	58.49 167	205.24 168	319.44 166	81.03 165	88.93 164

WB-MVS		316.44 153	357.41 155	193.51 162	257.06 171	213.32 174	914.45 178	49.03 172	600.77 176	186.42 170	634.00 175	75.03 172	251.35 172	411.39 169	88.55 166	115.87 168

SSC-MVS		320.23 154	364.09 156	188.66 161	260.78 172	193.84 170	975.93 181	73.11 174	596.72 175	185.29 169	589.02 172	74.47 171	246.01 171	427.42 171	94.06 167	126.12 169

EG-PatchMatch MVS		437.03 164	493.12 168	268.77 172	264.80 173	260.20 179	1491.80 202	98.00 189	723.20 183	238.80 173	722.40 178	63.10 168	382.00 184	629.00 189	207.00 193	164.10 180

RPSCF		394.81 159	445.63 161	242.35 165	276.55 174	253.63 176	1207.27 196	90.69 184	715.56 180	241.57 174	684.87 176	111.96 183	320.02 175	548.38 183	133.81 173	153.39 176

Syy-MVS		370.76 155	415.60 158	236.25 164	310.54 175	210.76 173	965.13 179	98.58 190	746.06 184	266.26 177	788.85 183	91.37 176	364.76 180	357.17 168	116.42 170	133.22 170

myMVS_eth3d		390.90 158	437.44 159	251.28 169	310.54 175	255.86 177	965.13 179	98.58 190	746.06 184	266.26 177	788.85 183	154.95 192	364.76 180	490.19 173	116.42 170	133.22 170

testing99		408.82 161	462.15 163	248.86 168	322.45 177	269.42 180	1118.93 192	73.26 175	719.36 182	262.28 176	772.10 180	150.98 191	327.08 176	601.98 186	137.99 175	150.07 174

testing3		418.10 162	469.06 164	265.23 171	335.69 178	290.63 182	1240.88 197	93.72 185	717.99 181	215.31 171	811.97 189	232.41 219	358.74 179	458.67 172	114.88 169	146.32 173

DELS-MVS		514.57 172	587.73 175	295.12 176	343.03 179	328.09 187	1540.48 204	116.22 197	988.59 195	325.44 187	906.22 193	119.86 185	365.72 182	788.60 198	161.09 183	191.55 186
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		387.98 157	438.66 160	235.93 163	349.32 180	257.61 178	1081.50 189	82.45 180	637.74 179	257.12 175	738.54 179	134.25 186	308.00 173	531.93 181	135.11 174	142.17 172

DP-MVS Recon		516.25 173	581.17 174	321.48 179	361.02 181	429.00 195	1995.36 208	78.48 177	796.20 188	283.32 183	796.02 185	96.78 177	382.98 185	636.72 191	186.66 190	152.46 175

ACMH+	729.97 2	661.38 179	754.00 182	383.51 183	368.96 182	376.38 190	2483.74 221	82.42 179	1089.25 204	333.39 188	1219.68 208	66.53 170	573.60 206	957.86 204	184.14 189	200.56 187

WB-MVSnew		404.84 160	458.00 162	245.36 166	374.70 183	320.27 185	1193.74 195	72.90 173	773.77 187	238.30 172	688.22 177	90.05 175	308.59 174	532.76 182	157.54 180	107.21 167

MVP-Stereo		473.58 168	533.67 170	293.33 174	376.00 184	318.00 183	1461.00 200	96.00 186	835.00 189	290.00 184	804.00 186	97.00 178	383.00 186	688.00 196	156.00 178	179.00 182
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MS-PatchMatch		473.58 168	533.67 170	293.33 174	376.00 184	318.00 183	1461.00 200	96.00 186	835.00 189	290.00 184	804.00 186	97.00 178	383.00 186	688.00 196	156.00 178	179.00 182

ETVMVS		443.50 167	498.07 169	279.78 173	378.05 186	321.57 186	1163.68 194	87.12 181	897.50 194	269.81 179	822.83 190	141.20 190	334.53 178	568.21 185	154.21 177	183.26 184

testing222		430.52 163	487.50 167	259.56 170	379.87 187	282.69 181	1138.34 193	81.30 178	880.86 191	281.58 180	834.27 191	135.83 188	333.22 177	514.90 180	140.56 176	162.76 177

tpmvs		501.65 171	567.42 173	304.33 177	395.39 188	356.32 188	1512.04 203	216.53 223	994.15 196	350.16 189	804.16 188	119.38 184	380.98 183	555.14 184	159.87 182	175.69 181

PatchmatchNet		492.52 170	551.22 172	316.40 178	400.20 189	357.90 189	1277.10 198	115.80 196	1034.60 203	315.90 186	874.00 192	155.10 193	402.20 188	629.50 190	158.80 181	189.10 185
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PMVS	863.65 3	957.08 198	1054.11 207	666.00 212	401.00 190	495.00 198	3790.00 229	279.00 225	1607.00 224	521.00 206	1745.00 224	90.00 173	1105.00 235	639.00 192	415.00 220	398.00 217
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
CSCG		826.03 193	963.29 198	414.24 185	421.52 191	426.11 194	2230.35 209	179.52 219	1827.44 226	733.43 225	933.12 195	281.25 221	545.23 197	1800.35 233	262.64 207	271.38 198

IB-MVS	872.44 4	616.41 178	700.96 181	362.78 182	426.10 192	409.25 193	1822.69 205	124.42 206	1186.23 206	366.85 191	1079.42 205	190.60 207	451.78 191	930.72 203	181.59 188	227.30 189
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		443.33 165	482.84 165	324.79 180	434.94 193	387.73 191	1110.57 190	87.69 182	887.02 192	282.92 181	779.29 181	98.57 180	422.76 189	502.40 174	162.19 184	163.87 178

ADS-MVSNet		443.33 165	482.84 165	324.79 180	434.94 193	387.73 191	1110.57 190	87.69 182	887.02 192	282.92 181	779.29 181	98.57 180	422.76 189	502.40 174	162.19 184	163.87 178

ACMH	993.80 5	967.92 199	1106.11 209	553.33 200	494.00 195	534.00 200	3581.00 227	136.00 208	1585.00 223	478.00 203	1871.00 226	90.00 173	839.00 218	1460.00 227	260.00 206	287.00 201
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
IterMVS		615.05 177	691.66 180	385.23 184	516.40 196	454.80 196	1863.80 206	102.10 193	1142.20 205	364.10 190	1093.20 207	135.00 187	480.40 192	826.90 199	181.20 187	220.50 188
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
ACMM	1311.08 8	1165.06 211	1332.72 214	662.07 211	584.90 197	715.99 223	4373.59 234	153.99 216	1880.27 228	709.02 222	2316.97 230	188.63 206	939.89 223	1484.30 228	302.78 214	330.34 207
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
new-patchmatchnet		766.12 182	859.03 187	487.38 197	595.68 198	536.14 201	2346.27 211	142.51 211	1488.08 213	422.43 192	1361.32 212	163.65 196	628.60 211	1003.74 213	207.61 194	297.41 203

ACMP	1246.57 7	1086.24 207	1235.17 211	639.45 207	596.53 199	639.91 218	3904.24 230	152.04 214	1851.54 227	566.58 212	1997.95 228	138.50 189	938.30 222	1605.46 229	303.70 215	340.14 208
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
SixPastTwentyTwo		773.62 183	869.37 189	486.35 196	603.45 200	547.15 210	2532.14 222	106.92 195	1434.95 212	428.08 193	1360.56 211	165.15 197	628.96 212	984.09 205	209.01 195	282.94 200

IterMVS-LS		758.94 181	856.56 186	466.10 194	606.60 201	546.80 209	2309.90 210	122.20 205	1402.80 211	463.50 195	1348.20 210	192.60 208	574.60 207	1028.60 214	234.60 205	276.90 199
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MG-MVS		1256.50 213	1432.00 216	730.00 216	610.00 202	760.00 225	4720.00 235	169.00 217	1920.00 229	723.00 224	2510.00 236	201.00 211	1050.00 233	1645.00 231	390.00 219	380.00 214

RE-MVS-def			610.10 177		610.10 203	610.10 216	610.10 169	610.10 268	610.10 177	610.10 215	610.10 173	610.10 251		610.10 187	610.10 224	610.10 222

SR-MVS		610.10 175	610.10 177	610.10 206	610.10 203	610.10 216	610.10 169	610.10 268	610.10 177	610.10 215	610.10 173	610.10 251	610.10 209	610.10 187	610.10 224	610.10 222

GG-mvs-BLEND				596.01 204	611.29 205	600.33 213	790.30 173	513.12 259		552.71 208	567.40 167	662.54 263	531.67 193	503.93 176	779.80 241	656.02 225

gm-plane-assit					611.29 205	600.33 213			579.21 171		567.40 167		531.67 193	503.93 176

CR-MVSNet		612.36 176	617.81 179	596.01 204	611.29 205	600.33 213	790.30 173	513.12 259	579.21 171	552.71 208	567.40 167	662.54 263	531.67 193	503.93 176	779.80 241	656.02 225

Gipuma		689.75 180	767.00 183	458.00 193	613.00 208	549.00 211	1943.00 207	187.00 220	1230.00 207	518.00 205	1092.00 206	203.00 213	564.00 198	892.00 202	225.00 203	261.00 197
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
gg-mvs-nofinetune		594.69 174	605.37 176	562.67 201	617.29 209	500.33 199	772.30 172	413.12 244	579.21 171	552.71 208	567.40 167	662.54 263	531.67 193	503.93 176	779.80 241	656.02 225

mvs_anonymous		774.90 184	882.28 190	452.77 186	636.50 210	537.20 202	2348.80 212	120.30 198	1504.30 214	474.40 196	1371.10 213	186.90 199	564.70 199	1078.90 216	219.30 196	256.40 190

casdiffmvs		774.90 184	882.28 190	452.77 186	636.50 210	537.20 202	2348.80 212	120.30 198	1504.30 214	474.40 196	1371.10 213	186.90 199	564.70 199	1078.90 216	219.30 196	256.40 190
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		774.90 184	882.28 190	452.77 186	636.50 210	537.20 202	2348.80 212	120.30 198	1504.30 214	474.40 196	1371.10 213	186.90 199	564.70 199	1078.90 216	219.30 196	256.40 190
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		774.90 184	882.28 190	452.77 186	636.50 210	537.20 202	2348.80 212	120.30 198	1504.30 214	474.40 196	1371.10 213	186.90 199	564.70 199	1078.90 216	219.30 196	256.40 190

baseline1		774.90 184	882.28 190	452.77 186	636.50 210	537.20 202	2348.80 212	120.30 198	1504.30 214	474.40 196	1371.10 213	186.90 199	564.70 199	1078.90 216	219.30 196	256.40 190

casdiffmvs_mvg		774.90 184	882.28 190	452.77 186	636.50 210	537.20 202	2348.80 212	120.30 198	1504.30 214	474.40 196	1371.10 213	186.90 199	564.70 199	1078.90 216	219.30 196	256.40 190
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		774.90 184	882.28 190	452.77 186	636.50 210	537.20 202	2348.80 212	120.30 198	1504.30 214	474.40 196	1371.10 213	186.90 199	564.70 199	1078.90 216	219.30 196	256.40 190

PVSNet	1207.94 6	829.56 194	937.18 197	506.69 198	645.55 217	585.72 212	2477.98 220	130.52 207	1578.29 222	509.50 204	1460.01 220	194.90 209	637.19 213	1170.78 224	267.07 209	297.17 202

FPMVS		1407.00 216	1495.59 218	1141.23 229	648.01 218	893.85 232	4124.00 231	503.81 258	3219.04 239	742.72 226	2498.84 235	157.98 194	1727.83 242	832.93 200	732.98 240	802.00 234

lessismore_v0				569.20 202	667.25 219	644.68 219		96.45 188		428.86 194	1514.17 221	204.21 214	756.58 215	1061.60 215	197.79 192	306.34 204

PVSNet_0	1661.03 9	968.54 200	1066.82 208	673.70 213	706.94 220	695.69 221	2669.02 225	153.52 215	2108.17 231	605.54 213	1679.14 223	213.26 217	886.75 221	1236.76 226	229.01 204	438.67 218

MSLP-MVS++		1242.93 212	1411.08 215	738.48 217	712.71 221	712.68 222	4168.17 232	136.50 209	2276.40 233	613.28 217	2368.60 233	161.61 195	1130.38 236	1964.54 236	297.88 212	372.39 213

MVSTER		890.06 197	1005.91 206	542.52 199	736.13 222	653.90 220	2616.56 224	145.22 213	1692.10 225	555.69 211	1554.72 222	266.25 220	660.02 214	1219.66 225	266.84 208	313.64 206

MVS_111021_LR		1136.45 210	1298.72 213	649.64 208	756.17 223	726.26 224	3785.94 228	138.15 210	2190.64 232	629.63 218	2064.39 229	165.45 198	874.83 220	1678.43 232	279.70 210	347.82 211

DeepC-MVS_fast	2190.19 12	1535.59 217	1886.82 221	481.89 195	847.73 224	830.16 229	7943.84 254	189.23 221	2398.83 234	691.73 221	2341.13 231	209.16 215	230.25 169	1999.25 237	360.46 217	385.25 215
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
JIA-IIPM		804.30 192	835.64 185	710.26 215	885.90 225	895.90 233	455.98 167	668.73 273	1297.17 208	1002.26 237	1001.67 203	655.98 261	756.98 216	667.90 193	885.21 253	477.90 219

RPMNet		787.26 191	829.13 184	661.63 210	885.90 225	895.90 233	455.98 167	610.10 268	1297.17 208	1002.26 237	1001.67 203	655.98 261	611.10 210	667.90 193	885.21 253	477.90 219

ACMMPR		1296.60 214	1480.82 217	743.96 218	899.25 227	763.47 226	4305.47 233	143.90 212	2530.94 236	683.99 219	2346.34 232	201.65 212	1098.25 234	1920.59 235	295.21 211	370.16 212

test_0402		1110.00 209	1260.00 212	660.00 209	900.00 228	780.00 227	3300.00 226	210.00 222	2040.00 230	690.00 220	1950.00 227	300.00 224	810.00 217	1620.00 230	330.00 216	390.00 216

TSAR-MVS + GP.		1386.84 215	1622.84 219	678.81 214	952.13 229	840.17 230	5358.21 238	170.75 218	2650.47 237	713.54 223	2394.28 234	209.42 216	855.56 219	1854.36 234	302.42 213	340.71 209

ambc				999.00 221	999.00 230	999.00 235	999.00 182	999.00 284		999.00 230	999.00 196	999.00 276	999.00 226	999.00 206	999.00 260	999.00 257

OurMVSNet-221017-0		999.00 201	999.00 200	999.00 221	999.00 230	999.00 235	999.00 182	999.00 284	999.00 197	999.00 230	999.00 196	999.00 276	999.00 226	999.00 206	999.00 260	999.00 257

EPMVS		999.00 201	999.00 200	999.00 221	999.00 230	999.00 235	999.00 182	999.00 284	999.00 197	999.00 230	999.00 196	999.00 276	999.00 226	999.00 206	999.00 260	999.00 257

uanet_test		1000.00 203	1000.00 202	1000.00 224	1000.00 233	1000.00 238	1000.00 185	1000.00 287	1000.00 199	1000.00 233	1000.00 199	1000.00 279	1000.00 229	1000.00 209	1000.00 263	1000.00 260

sosnet		1000.00 203	1000.00 202	1000.00 224	1000.00 233	1000.00 238	1000.00 185	1000.00 287	1000.00 199	1000.00 233	1000.00 199	1000.00 279	1000.00 229	1000.00 209	1000.00 263	1000.00 260

USDC		1000.00 203	1000.00 202	1000.00 224	1000.00 233	1000.00 238	1000.00 185	1000.00 287	1000.00 199	1000.00 233	1000.00 199	1000.00 279	1000.00 229	1000.00 209	1000.00 263	1000.00 260

TinyColmap		1000.00 203	1000.00 202	1000.00 224	1000.00 233	1000.00 238	1000.00 185	1000.00 287	1000.00 199	1000.00 233	1000.00 199	1000.00 279	1000.00 229	1000.00 209	1000.00 263	1000.00 260

COLMAP_ROB	2144.59 11	1658.33 218	1869.33 220	1025.33 228	1030.00 237	1023.00 242	5311.00 237	359.00 234	3044.00 238	937.00 229	2892.00 237	332.00 228	1440.00 239	2312.00 239	607.00 223	613.00 224
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
F-COLMAP		1878.17 219	2113.11 222	1173.33 232	1231.00 238	1174.00 243	6297.00 240	392.00 239	3356.00 241	1087.00 239	3082.00 238	361.00 232	1670.00 241	2523.00 241	689.00 230	676.00 229

OpenMVS_ROB	1936.51 10	1959.51 220	2224.88 224	1163.39 231	1253.91 239	1434.22 246	7065.71 244	272.76 224	2472.29 235	1647.54 269	3538.72 241	200.37 210	1496.48 240	2575.17 242	997.45 259	559.48 221

Patchmtry		1090.75 208	1198.88 210	766.38 219	1290.90 240	485.90 197	2423.98 219	1267.30 291	1297.17 208	923.90 227	923.40 194	1215.54 284	990.23 224	667.90 193	779.80 241	823.02 239

PatchT		856.34 195	860.99 188	842.38 220	1290.90 240	880.90 231	790.30 173	1267.30 291	579.21 171	923.90 227	567.40 167	662.54 263	990.23 224	887.56 201	779.80 241	656.02 225

K. test v3		877.74 196	980.16 199	570.46 203	1316.85 242	813.15 228	2565.52 223	103.78 194	1509.49 221	548.33 207	1258.90 209	219.93 218	587.82 208	1102.37 223	196.30 191	310.42 205

PLC	2858.82 16	2192.92 223	2474.00 226	1349.67 234	1407.00 243	1356.00 245	7164.00 245	475.00 251	3970.00 245	1237.00 246	3765.00 244	451.00 239	1891.00 247	3006.00 245	791.00 246	802.00 234
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
CMPMVS	2623.62 15	1983.08 221	2156.14 223	1463.89 242	1414.80 244	1517.00 248	5239.20 236	867.40 278	3310.30 240	1128.70 241	3489.90 240	366.75 233	2030.20 253	2427.60 240	1160.60 272	844.46 242
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
ZD-MVS					1584.00 245	1821.00 268		378.00 237	3721.00 243	1231.00 244	1833.00 225	321.00 227	1224.00 237	2103.00 238	692.00 234

Vis-MVSNet		2877.42 236	3170.00 239	1999.67 257	1673.00 246	2042.00 274	8593.00 258	474.00 250	6452.00 270	1268.00 247	5125.00 258	339.00 229	3004.00 271	4222.00 261	384.00 218	953.00 253
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
PCF-MVS	4335.85 20	2272.23 225	2597.03 228	1297.84 233	1701.20 247	1332.37 244	8105.11 255	451.45 247	4031.84 246	1099.10 240	3966.50 245	467.45 240	1734.05 243	2701.68 244	848.94 250	827.11 240
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
test_0728_SECOND				1451.45 239	1725.60 248	1598.35 252	9203.30 261	315.86 228					2023.43 250	3973.88 255	620.04 226	732.56 231

test0726					1725.60 248	1598.35 252	9203.30 261	315.86 228	5016.02 257	1363.85 249	4894.28 255	387.23 234

SD-MVS		2654.53 232	3055.56 237	1451.45 239	1725.60 248	1598.35 252	9203.30 261	315.86 228	5016.02 257	1363.85 249	4894.28 255	387.23 234	2023.43 250	3973.88 255	620.04 226	732.56 231
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	2531.17 229	2839.56 232	1606.00 243	1732.00 251	1557.00 250	8375.00 257	483.00 252	4370.00 251	1371.00 252	4200.00 246	350.00 230	2207.00 254	3877.00 254	798.00 247	1054.00 264

LF4IMVS		2699.50 234	3049.67 236	1649.00 245	1755.00 252	1689.00 259	8330.00 256	464.00 249	4997.00 256	1528.00 255	4763.00 254	568.00 249	2296.00 256	4215.00 260	827.00 249	962.00 254

DPM-MVS		3268.00 240	3762.89 243	1783.33 250	1756.00 253	1806.00 266	12319.00 277	307.00 226	6319.00 268	1557.00 260	5763.00 261	302.00 225	2609.00 263	5061.00 266	482.00 221	935.00 251

OPM-MVS		3268.00 240	3762.89 243	1783.33 250	1756.00 253	1806.00 266	12319.00 277	307.00 226	6319.00 268	1557.00 260	5763.00 261	302.00 225	2609.00 263	5061.00 266	482.00 221	935.00 251
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
OpenMVS	2352.88 13	2263.08 224	2530.89 227	1459.67 241	1767.00 255	1591.00 251	7932.00 253	399.00 240	3643.00 242	1176.00 242	3569.00 242	297.00 223	1927.00 249	3302.00 247	693.00 235	861.00 243

tpmrst		2557.50 230	2847.12 233	1688.66 246	1784.08 256	1778.25 265	7445.50 251	342.14 231	4471.54 252	1534.55 256	4382.10 250	530.10 246	2361.21 257	4142.81 258	991.22 258	926.51 249

AdaColmap		2570.77 231	2948.61 234	1437.24 238	1873.64 257	1526.60 249	7819.77 252	373.97 235	4970.45 255	1479.29 254	4648.46 252	525.80 245	1904.97 248	4150.42 259	695.69 236	880.14 247

SteuartSystems-ACMMP		2891.50 237	3284.78 240	1711.67 247	1954.00 258	1655.00 258	10117.00 274	445.00 246	5102.00 260	1375.00 253	5126.00 259	351.00 231	2638.00 267	4402.00 262	691.00 233	842.00 241
Skip Steuart: Steuart Systems R&D Blog.
ITE_SJBPF				2014.00 258	1998.00 259	1992.00 272		701.00 274	5989.00 262	1812.00 273	3612.00 243	650.00 257	2852.00 270	4601.00 264	1195.00 273	1198.00 270

tpm2		3617.85 244	4007.23 246	2449.73 264	2012.71 260	1698.05 260	7351.19 247	869.29 279	6132.06 263	1588.28 263	8007.42 279	1281.09 285	3888.11 283	7472.04 284	1351.00 274	1763.02 280

tpm cat1		3617.85 244	4007.23 246	2449.73 264	2012.71 260	1698.05 260	7351.19 247	869.29 279	6132.06 263	1588.28 263	8007.42 279	1281.09 285	3888.11 283	7472.04 284	1351.00 274	1763.02 280

CostFormer		3617.85 244	4007.23 246	2449.73 264	2012.71 260	1698.05 260	7351.19 247	869.29 279	6132.06 263	1588.28 263	8007.42 279	1281.09 285	3888.11 283	7472.04 284	1351.00 274	1763.02 280

tpm		3617.85 244	4007.23 246	2449.73 264	2012.71 260	1698.05 260	7351.19 247	869.29 279	6132.06 263	1588.28 263	8007.42 279	1281.09 285	3888.11 283	7472.04 284	1351.00 274	1763.02 280

CHOSEN 280x420		2340.81 226	2643.03 229	1434.14 235	2025.55 264	1629.36 255	6542.40 241	412.49 241	4219.70 248	1547.02 257	4328.52 247	650.74 258	1798.26 244	3333.17 248	727.72 237	874.79 244

CHOSEN 1792x2688		2340.81 226	2643.03 229	1434.14 235	2025.55 264	1629.36 255	6542.40 241	412.49 241	4219.70 248	1547.02 257	4328.52 247	650.74 258	1798.26 244	3333.17 248	727.72 237	874.79 244

HyFIR lowres test		2340.81 226	2643.03 229	1434.14 235	2025.55 264	1629.36 255	6542.40 241	412.49 241	4219.70 248	1547.02 257	4328.52 247	650.74 258	1798.26 244	3333.17 248	727.72 237	874.79 244

DVP-MVS++		3981.10 250	4731.32 255	1730.42 248	2191.51 267	1949.98 270	16473.90 286	355.33 232	7172.90 279	1622.98 267	7879.79 277	434.33 237	2428.11 259	5762.12 269	689.04 231	813.18 237

DVP-MVS		3981.10 250	4731.32 255	1730.42 248	2191.51 267	1949.98 270	16473.90 286	355.33 232	7172.90 279	1622.98 267	7879.79 277	434.33 237	2428.11 259	5762.12 269	689.04 231	813.18 237
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	3146.67 238	3537.00 241	1975.67 254	2310.00 269	2005.00 273	10100.00 273	626.00 271	5753.00 261	1803.00 272	5179.00 260	487.00 241	2622.00 265	4550.00 263	1025.00 267	1300.00 271

TSAR-MVS + MP.		3528.01 243	4065.89 250	1914.35 253	2349.10 270	2141.30 275	12362.70 279	417.60 245	6717.80 274	1759.40 271	6497.50 264	518.18 244	2629.38 266	5164.32 268	806.40 248	972.38 256
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	2670.71 233	3021.57 235	1618.12 244	2377.67 271	1751.39 264	8915.70 260	567.44 266	4569.74 253	1236.84 245	4615.63 251	513.23 243	2291.32 255	3515.48 251	882.39 252	811.66 236

GST-MVS		4000.00 252	4533.33 253	2400.00 263	2400.00 272	2400.00 278	7200.00 246	2400.00 295	7200.00 281	2400.00 283	7200.00 271	2400.00 289	2400.00 258	7200.00 282	2400.00 286	2400.00 285

MVS_111021_HR		3742.80 248	4330.34 251	1980.20 255	2484.31 273	2259.52 277	14973.80 284	515.90 265	6500.13 271	1949.21 274	6146.89 263	535.66 247	2593.66 262	4880.76 265	986.37 257	1087.43 265

DeepC-MVS	3917.13 19	3155.06 239	3601.83 242	1814.72 252	2515.52 274	1941.53 269	10432.50 275	589.42 267	4789.45 254	1298.65 248	7677.31 276	578.35 250	2589.53 261	3611.78 253	923.52 255	913.10 248
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	3374.90 242	3806.99 245	2078.63 259	2535.47 275	2499.25 284	8816.16 259	456.05 248	6255.60 267	1664.52 270	6704.88 266	629.95 256	2768.38 268	6343.93 280	856.35 251	968.25 255
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
FOURS1					2643.17 276	2465.14 279	13996.40 281	493.26 253	7619.38 282	2107.24 275

MSC_two_6792asdad				2237.56 260	2643.17 276	2465.14 279		493.26 253					3088.29 276	6075.14 276	1078.39 268	1159.26 266

No_MVS				2237.56 260	2643.17 276	2465.14 279		493.26 253					3088.29 276	6075.14 276	1078.39 268	1159.26 266

test_one_0601					2643.17 276	2465.14 279		493.26 253	7619.38 282	2107.24 275	7416.93 273	610.24 253

SED-MVS		4062.74 253	4671.13 254	2237.56 260	2643.17 276	2465.14 279	13996.40 281	493.26 253	7619.38 282	2107.24 275	7416.93 273	610.24 253	3088.29 276	6075.14 276	1078.39 268	1159.26 266

IU-MVS					2725.60 281	2598.35 285		515.86 261	7016.02 275	2363.85 279				5973.88 272	1620.04 280	1732.56 276

OPU-MVS				2451.45 268	2725.60 281	2598.35 285	9203.30 261				6894.28 267	887.23 271	3023.43 272	5973.88 272	1620.04 280	1732.56 276

test_241102_ONE					2725.60 281	2598.35 285		515.86 261	7016.02 275	2363.85 279	6894.28 267	887.23 271	3023.43 272

MSP-MVS		4296.20 254	4911.12 258	2451.45 268	2725.60 281	2598.35 285	16203.30 285	515.86 261	7016.02 275	2363.85 279	6894.28 267	887.23 271	3023.43 272	5973.88 272	1620.04 280	1732.56 276
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		2125.39 222	2452.68 225	1143.53 230	2938.33 285	1446.92 247	6083.19 239	391.74 238	3801.71 244	1202.10 243	3439.72 239	492.73 242	1304.35 238	3048.25 246	676.32 229	679.32 230

EGC-MVSNET		2819.75 235	3096.89 238	1988.33 256	3105.00 286	2241.00 276	9480.00 265	640.00 272	4209.00 247	1583.00 262	4740.00 253	547.00 248	2797.00 269	2644.00 243	924.00 256	927.00 250

MAR-MVS		3973.16 249	4387.92 252	2728.86 270	3345.27 287	3341.39 291	11403.90 276	798.76 276	6555.62 273	2569.29 284	6514.86 265	834.97 270	3237.43 280	5891.08 271	1577.54 279	1607.76 272
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		4380.83 255	4906.56 257	2803.67 271	3844.00 288	3116.00 290	13454.00 280	901.00 283	6511.00 272	2794.00 285	7365.00 272	754.00 267	3634.00 281	6622.00 281	1914.00 285	1661.00 275

CLD-MVS		7338.25 257	8341.00 260	4330.00 273	4902.00 289	4991.00 292	23318.00 289	728.00 275	14437.00 296	4378.00 288	13379.00 291	824.00 269	5708.00 287	11429.00 297	1674.00 284	2291.00 284
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
OMC-MVS		5022.26 256	5748.82 259	2842.58 272	4905.27 290	3101.27 289	14933.60 283	812.24 277	9278.40 286	2959.29 286	8800.17 283	1092.24 283	3806.30 282	7568.54 288	1389.60 278	1620.18 274

LS3D		7684.71 258	8776.23 261	4410.16 274	5298.55 291	5631.53 293	34329.90 291	1504.57 293	11554.00 295	3896.41 287	15111.00 292	812.19 268	5985.63 288	3516.20 252	2963.23 287	1613.31 273

MVE	10021.00 22	10550.67 266	10002.44 269	12195.33 283	6242.00 292	8768.00 295	30896.00 290	4451.00 296	10331.00 294	6247.00 289	18296.00 293	283.00 222	21484.00 297	7364.00 283	5912.00 289	6334.00 287
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CNLPA		10738.67 267	11772.44 270	7637.33 275	9120.00 293	8206.00 294	22252.00 288	2010.00 294	24984.00 297	7458.00 290	22596.00 294	2940.00 290	10260.00 296	11100.00 296	3492.00 288	4446.00 286

ZNCC-MVS		9999.00 259	9999.00 262	9999.00 276	9999.00 294	9999.00 296	9999.00 266	9999.00 299	9999.00 287	9999.00 291	9999.00 284	9999.00 292	9999.00 289	9999.00 289	9999.00 290	9999.00 288

patch_mono-2		10000.00 260	10000.00 263	10000.00 277	10000.00 295	10000.00 297	10000.00 267	10000.00 300	10000.00 288	10000.00 292	10000.00 285	10000.00 293	10000.00 290	10000.00 290	10000.00 291	10000.00 289

dcpmvs_2		10000.00 260	10000.00 263	10000.00 277	10000.00 295	10000.00 297	10000.00 267	10000.00 300	10000.00 288	10000.00 292	10000.00 285	10000.00 293	10000.00 290	10000.00 290	10000.00 291	10000.00 289

DCPMVS		10000.00 260	10000.00 263	10000.00 277	10000.00 295	10000.00 297	10000.00 267	10000.00 300	10000.00 288	10000.00 292	10000.00 285	10000.00 293	10000.00 290	10000.00 290	10000.00 291	10000.00 289

UA-Net		10000.00 260	10000.00 263	10000.00 277	10000.00 295	10000.00 297	10000.00 267	10000.00 300	10000.00 288	10000.00 292	10000.00 285	10000.00 293	10000.00 290	10000.00 290	10000.00 291	10000.00 289

uncertanet		10000.00 260	10000.00 263	10000.00 277	10000.00 295	10000.00 297	10000.00 267	10000.00 300	10000.00 288	10000.00 292	10000.00 285	10000.00 293	10000.00 290	10000.00 290	10000.00 291	10000.00 289

uanet		10000.00 260	10000.00 263	10000.00 277	10000.00 295	10000.00 297	10000.00 267	10000.00 300	10000.00 288	10000.00 292	10000.00 285	10000.00 293	10000.00 290	10000.00 290	10000.00 291	10000.00 289

LTVRE_ROB	20565.47 23	23378.08 268	22805.00 271	25097.33 284	15500.00 301	19201.00 303	42712.00 292	6055.00 297	38388.00 298	16926.00 298	38534.00 295	7071.00 291	35653.00 298	29475.00 298	10584.00 297	20438.00 296
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		32606.17 269	34443.44 272	27094.33 285	29249.00 302	25246.00 304	51144.00 293	6705.00 298	42886.00 299	22888.00 299	48534.00 296	13263.00 299	37507.00 299	79298.00 299	16024.00 298	18530.00 295

114514_t		99999.00 270	99999.00 273	99999.00 286	99999.00 303	99999.00 305	99999.00 294	99999.00 306	99999.00 300	99999.00 300	99999.00 297	99999.00 300	99999.00 300	99999.00 300	99999.00 299	99999.00 297

PHI-MVS		99999.00 270	99999.00 273	99999.00 286	99999.00 303	99999.00 305	99999.00 294	99999.00 306	99999.00 300	99999.00 300	99999.00 297	99999.00 300	99999.00 300	99999.00 300	99999.00 299	99999.00 297

XVG-OURS-SEG-HR		999999.00 274	999999.00 275	999999.00 288	999999.00 305	999999.00 307	999999.00 296	999999.00 308	999999.00 302	999999.00 302	999999.00 299	999999.00 302	999999.00 302	999999.00 302	999999.00 301	999999.00 299

XVG-OURS		999999.00 274	999999.00 275	999999.00 288	999999.00 305	999999.00 307	999999.00 296	999999.00 308	999999.00 302	999999.00 302	999999.00 299	999999.00 302	999999.00 302	999999.00 302	999999.00 301	999999.00 299

XVG-ACMP-BASELINE		999999.00 274	999999.00 275	999999.00 288	999999.00 305	999999.00 307	999999.00 296	999999.00 308	999999.00 302	999999.00 302	999999.00 299	999999.00 302	999999.00 302	999999.00 302	999999.00 301	999999.00 299

dmvs_re		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

SDMVSNet		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

dmvs_testset		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

sd_testset		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

iter_conf_final		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

bld_raw_dy_0_64		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

test2506		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

test1111		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

ECVR-MVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

test_blank		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

tt0805		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

eth-test					10000000.00 308

Anonymous20240521		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

cl22		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

miper_ehance_all_eth		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

miper_enhance_ethall		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

cl____		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

DIV-MVS_self_test		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

eth_miper_zixun_eth		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

ET-MVSNet_ETH3D		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

UniMVSNet_ETH3D		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

miper_lstm_enhance		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

D2MVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

test_yl		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

thisisatest0530		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

Anonymous20240529		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

Anonymous202405211		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

DCV-MVSNet		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

tttt0517		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

our_test_3		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

thisisatest0515		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

ppachtmachnet_test		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

SMA-MVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302
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		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part2					10000000.00 308	10000000.00 310				10000000.00 305

thres100view900		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

tfpnnormal		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

tfpn200view9		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

c3_l		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

IterMVS-SCA-FT		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

pmmvs6		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

pmmvs5		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

Anonymous20231211		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

pmmvs-eth3d		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

Anonymous20231206		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

SCA		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

Patchmatch-test		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

Patchmatch-RL test		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

canonicalmvs		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

anonymousdsp		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

FIs		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

FC-MVSNet-test		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

sosnet-low-res		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

AllTest		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

TestCases				10000000.00 291	10000000.00 308	10000000.00 310		10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

iter_conf05		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

RRT_MVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

HPM-MVS++		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

XVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

pm-mvs1		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

X-MVStestdata		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

APDe-MVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
APD-MVS_3200maxsize		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

pmmvs4		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

test-LLR		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

TESTMET0.1,1		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

test-mter		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

testgi		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

test20.03		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

thres600view7		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

MP-MVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

thres400		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

test123		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

thres200		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

test0.0.03 1		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

pmmvs3		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

EMVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

E-PMN		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

PGM-MVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

MCST-MVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

MVS_Test		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

PMMVS2		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

PM-MVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

HQP_MVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

plane_prior7					10000000.00 308	10000000.00 310

plane_prior6					10000000.00 308	10000000.00 310						10000000.00 305

plane_prior1					10000000.00 308

mPP-MVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

mvsmamba		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

HPM-MVS_fast		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

HPM-MVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
LPG-MVS_test		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

LGP-MVS_train				10000000.00 291	10000000.00 308	10000000.00 310		10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

EPNet_dtu		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP-NCC					10000000.00 308		10000000.00 299		10000000.00 305	10000000.00 305

ACMP_Plane					10000000.00 308		10000000.00 299		10000000.00 305	10000000.00 305

CNVR-MVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

NCCC		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

CP-MVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

NP-MVS					10000000.00 308	10000000.00 310					10000000.00 302

CPTT-MVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

HQP-MVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

IS-MVSNet		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

PAPM_NR		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

PAPR		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

Vis-MVSNet (Re-imp)		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

PatchMatch-RL		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

TDRefinement		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

EPP-MVSNet		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

PMMVS		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

PAPM		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

ACMMP		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302
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		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

wuyk23d		10000000.00 277	10000000.00 280	10000000.00 291	10000000.00 308	10000000.00 310	10000000.00 299	10000000.00 311	10000000.00 305	10000000.00 305	10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

APD-MVS		1000000000.00 383	1000000000.00 386	1000000000.00 399	1000000000.00 424	1000000000.00 424	1000000000.00 410	1000000000.00 424	1000000000.00 417	1000000000.00 418	1000000000.00 415	1000000000.00 420	1000000000.00 418	1000000000.00 417	1000000000.00 416	1000000000.00 414
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
WAC-MVS						248.46 175								422.23 170

PC_three_1452									7619.38 282	2107.24 275	7416.93 273	610.24 253	3088.29 276	6075.14 276	1078.39 268	1159.26 266

test_241102_TWO								515.86 261	7016.02 275	2363.85 279	6894.28 267	887.23 271	3023.43 272	5973.88 272	1620.04 280	1732.56 276

test_0728_THIRD									5016.02 257	1363.85 249	4894.28 255	387.23 234	2023.43 250	3973.88 255	620.04 226	732.56 231

GSMVS																10000000.00 302

sam_mvs1												10000000.00 305				10000000.00 302

sam_mvs												10000000.00 305

MTGPA								10000000.00 311

test_post1							10000000.00 299				10000000.00 302	10000000.00 305	10000000.00 305	10000000.00 305

test_post											10000000.00 302	10000000.00 305	10000000.00 305

patchmatchnet-post											10000000.00 302	10000000.00 305	10000000.00 305

MTMP							10000000.00 299	10000000.00 311

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								10000000.00 311					10000000.00 305	10000000.00 305	10000000.00 304	10000000.00 302

plane_prior4											10000000.00 302

plane_prior3						10000000.00 310			10000000.00 305	10000000.00 305

plane_prior2							10000000.00 299		10000000.00 305

plane_prior						1.00 78	2.00 106		2.00 107						2.00 105

n2								14.20 148

nn								1.42 86

door-mid								1.42 86

test11								1.00 79

door								99.00 192

HQP5-MVS						10000000.00 310

BP-MVS														10000000.00 305

HQP4-MVS										10000000.00 305			10000000.00 305			10000000.00 302

HQP3-MVS								10000000.00 311							10000000.00 304

HQP2-MVS												10000000.00 305

MDTV_nov1_ep13_2view						9.99 128	9.99 126		9.99 127	9.99 126		9.99 128		9.99 124		9.99 127

ACMMP++_ref															10000000.00 304

ACMMP++															10000000.00 304

Test By Simon												990.00 275

High-resolution multi-view benchmark