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		833442.10 277	1111233.77 283	67.09 141	65.59 148	64.81 151	284.50 150	10000000.00 315	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		833433.63 276	1111219.60 282	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	10000000.00 309	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	99.00 169	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	171.04 161	191.70 168	183.96 170	827.10 178	78.36 180	438.24 168	176.64 169	435.12 165	65.04 169	230.52 171	334.02 167	117.96 176	98.64 166

tmp_tt		371.08 160	412.78 161	246.00 171	231.00 169	197.00 172	1293.00 203	376.00 240	756.00 190	609.00 218	71.00 142	106.00 183	195.00 167	102.00 148	171.00 190	346.00 214

FA-MVS(test-final)		261.15 151	293.29 153	164.72 159	236.23 170	199.99 173	800.05 177	42.35 170	475.87 169	155.47 167	470.67 166	58.49 167	205.24 168	319.44 166	81.03 166	88.93 164

kuosan		267.89 153	301.05 155	168.41 160	244.05 171	177.28 169	667.98 172	65.76 173	533.41 171	157.79 168	492.01 167	104.69 182	226.72 169	364.47 169	79.31 165	101.21 167

WB-MVS		316.44 154	357.41 156	193.51 163	257.06 172	213.32 175	914.45 179	49.03 172	600.77 177	186.42 171	634.00 178	75.03 172	251.35 173	411.39 170	88.55 167	115.87 169

SSC-MVS		320.23 155	364.09 157	188.66 162	260.78 173	193.84 171	975.93 185	73.11 178	596.72 176	185.29 170	589.02 173	74.47 171	246.01 172	427.42 172	94.06 168	126.12 170

EG-PatchMatch MVS		437.03 168	493.12 172	268.77 176	264.80 174	260.20 182	1491.80 206	98.00 193	723.20 187	238.80 177	722.40 182	63.10 168	382.00 188	629.00 193	207.00 197	164.10 184

testing11		348.86 157	393.09 159	216.15 164	275.24 175	239.53 176	915.55 180	72.35 175	679.89 183	215.75 174	633.79 177	118.08 186	276.62 174	509.56 183	117.61 175	132.30 171

testing91		347.05 156	389.92 158	218.43 165	275.92 176	241.43 177	923.71 181	71.70 174	667.65 182	217.04 175	629.00 176	113.33 185	281.39 175	495.50 175	115.45 172	132.47 172

RPSCF		394.81 163	445.63 165	242.35 169	276.55 177	253.63 179	1207.27 200	90.69 188	715.56 184	241.57 178	684.87 179	111.96 184	320.02 179	548.38 187	133.81 177	153.39 180

dongtai		360.45 158	401.64 160	236.89 168	303.10 178	262.16 183	963.12 182	72.78 176	622.82 180	199.37 172	708.06 181	130.96 189	310.90 178	506.46 182	108.11 170	137.60 175

Syy-MVS		370.76 159	415.60 162	236.25 167	310.54 179	210.76 174	965.13 183	98.58 194	746.06 188	266.26 181	788.85 187	91.37 176	364.76 184	357.17 168	116.42 173	133.22 173

myMVS_eth3d		390.90 162	437.44 163	251.28 173	310.54 179	255.86 180	965.13 183	98.58 194	746.06 188	266.26 181	788.85 187	154.95 196	364.76 184	490.19 174	116.42 173	133.22 173

testing99		408.82 165	462.15 167	248.86 172	322.45 181	269.42 184	1118.93 196	73.26 179	719.36 186	262.28 180	772.10 184	150.98 195	327.08 180	601.98 190	137.99 179	150.07 178

testing3		418.10 166	469.06 168	265.23 175	335.69 182	290.63 186	1240.88 201	93.72 189	717.99 185	215.31 173	811.97 193	232.41 223	358.74 183	458.67 173	114.88 171	146.32 177

DELS-MVS		514.57 176	587.73 179	295.12 180	343.03 183	328.09 191	1540.48 208	116.22 201	988.59 199	325.44 191	906.22 197	119.86 188	365.72 186	788.60 202	161.09 187	191.55 190
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		387.98 161	438.66 164	235.93 166	349.32 184	257.61 181	1081.50 193	82.45 184	637.74 181	257.12 179	738.54 183	134.25 190	308.00 176	531.93 185	135.11 178	142.17 176

DP-MVS Recon		516.25 177	581.17 178	321.48 183	361.02 185	429.00 199	1995.36 212	78.48 181	796.20 192	283.32 187	796.02 189	96.78 177	382.98 189	636.72 195	186.66 194	152.46 179

ACMH+	729.97 2	661.38 183	754.00 186	383.51 187	368.96 186	376.38 194	2483.74 225	82.42 183	1089.25 208	333.39 192	1219.68 212	66.53 170	573.60 210	957.86 208	184.14 193	200.56 191

WB-MVSnew		404.84 164	458.00 166	245.36 170	374.70 187	320.27 189	1193.74 199	72.90 177	773.77 191	238.30 176	688.22 180	90.05 175	308.59 177	532.76 186	157.54 184	107.21 168

MVP-Stereo		473.58 172	533.67 174	293.33 178	376.00 188	318.00 187	1461.00 204	96.00 190	835.00 193	290.00 188	804.00 190	97.00 178	383.00 190	688.00 200	156.00 182	179.00 186
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MS-PatchMatch		473.58 172	533.67 174	293.33 178	376.00 188	318.00 187	1461.00 204	96.00 190	835.00 193	290.00 188	804.00 190	97.00 178	383.00 190	688.00 200	156.00 182	179.00 186

ETVMVS		443.50 171	498.07 173	279.78 177	378.05 190	321.57 190	1163.68 198	87.12 185	897.50 198	269.81 183	822.83 194	141.20 194	334.53 182	568.21 189	154.21 181	183.26 188

testing222		430.52 167	487.50 171	259.56 174	379.87 191	282.69 185	1138.34 197	81.30 182	880.86 195	281.58 184	834.27 195	135.83 192	333.22 181	514.90 184	140.56 180	162.76 181

tpmvs		501.65 175	567.42 177	304.33 181	395.39 192	356.32 192	1512.04 207	216.53 227	994.15 200	350.16 193	804.16 192	119.38 187	380.98 187	555.14 188	159.87 186	175.69 185

PatchmatchNet		492.52 174	551.22 176	316.40 182	400.20 193	357.90 193	1277.10 202	115.80 200	1034.60 207	315.90 190	874.00 196	155.10 197	402.20 192	629.50 194	158.80 185	189.10 189
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PMVS	863.65 3	957.08 202	1054.11 211	666.00 216	401.00 194	495.00 202	3790.00 233	279.00 229	1607.00 228	521.00 210	1745.00 228	90.00 173	1105.00 239	639.00 196	415.00 224	398.00 221
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
CSCG		826.03 197	963.29 202	414.24 189	421.52 195	426.11 198	2230.35 213	179.52 223	1827.44 230	733.43 229	933.12 199	281.25 225	545.23 201	1800.35 237	262.64 211	271.38 202

IB-MVS	872.44 4	616.41 182	700.96 185	362.78 186	426.10 196	409.25 197	1822.69 209	124.42 210	1186.23 210	366.85 195	1079.42 209	190.60 211	451.78 195	930.72 207	181.59 192	227.30 193
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		443.33 169	482.84 169	324.79 184	434.94 197	387.73 195	1110.57 194	87.69 186	887.02 196	282.92 185	779.29 185	98.57 180	422.76 193	502.40 176	162.19 188	163.87 182

ADS-MVSNet		443.33 169	482.84 169	324.79 184	434.94 197	387.73 195	1110.57 194	87.69 186	887.02 196	282.92 185	779.29 185	98.57 180	422.76 193	502.40 176	162.19 188	163.87 182

ACMH	993.80 5	967.92 203	1106.11 213	553.33 204	494.00 199	534.00 204	3581.00 231	136.00 212	1585.00 227	478.00 207	1871.00 230	90.00 173	839.00 222	1460.00 231	260.00 210	287.00 205
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
IterMVS		615.05 181	691.66 184	385.23 188	516.40 200	454.80 200	1863.80 210	102.10 197	1142.20 209	364.10 194	1093.20 211	135.00 191	480.40 196	826.90 203	181.20 191	220.50 192
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
ACMM	1311.08 8	1165.06 215	1332.72 218	662.07 215	584.90 201	715.99 227	4373.59 238	153.99 220	1880.27 232	709.02 226	2316.97 234	188.63 210	939.89 227	1484.30 232	302.78 218	330.34 211
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
new-patchmatchnet		766.12 186	859.03 191	487.38 201	595.68 202	536.14 205	2346.27 215	142.51 215	1488.08 217	422.43 196	1361.32 216	163.65 200	628.60 215	1003.74 217	207.61 198	297.41 207

ACMP	1246.57 7	1086.24 211	1235.17 215	639.45 211	596.53 203	639.91 222	3904.24 234	152.04 218	1851.54 231	566.58 216	1997.95 232	138.50 193	938.30 226	1605.46 233	303.70 219	340.14 212
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
SixPastTwentyTwo		773.62 187	869.37 193	486.35 200	603.45 204	547.15 214	2532.14 226	106.92 199	1434.95 216	428.08 197	1360.56 215	165.15 201	628.96 216	984.09 209	209.01 199	282.94 204

IterMVS-LS		758.94 185	856.56 190	466.10 198	606.60 205	546.80 213	2309.90 214	122.20 209	1402.80 215	463.50 199	1348.20 214	192.60 212	574.60 211	1028.60 218	234.60 209	276.90 203
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MG-MVS		1256.50 217	1432.00 220	730.00 220	610.00 206	760.00 229	4720.00 239	169.00 221	1920.00 233	723.00 228	2510.00 240	201.00 215	1050.00 237	1645.00 235	390.00 223	380.00 218

RE-MVS-def			610.10 181		610.10 207	610.10 220	610.10 169	610.10 272	610.10 178	610.10 219	610.10 174	610.10 255		610.10 191	610.10 228	610.10 226

SR-MVS		610.10 179	610.10 181	610.10 210	610.10 207	610.10 220	610.10 169	610.10 272	610.10 178	610.10 219	610.10 174	610.10 255	610.10 213	610.10 191	610.10 228	610.10 226

GG-mvs-BLEND				596.01 208	611.29 209	600.33 217	790.30 174	513.12 263		552.71 212	567.40 168	662.54 267	531.67 197	503.93 178	779.80 245	656.02 229

gm-plane-assit					611.29 209	600.33 217			579.21 172		567.40 168		531.67 197	503.93 178

CR-MVSNet		612.36 180	617.81 183	596.01 208	611.29 209	600.33 217	790.30 174	513.12 263	579.21 172	552.71 212	567.40 168	662.54 267	531.67 197	503.93 178	779.80 245	656.02 229

Gipuma		689.75 184	767.00 187	458.00 197	613.00 212	549.00 215	1943.00 211	187.00 224	1230.00 211	518.00 209	1092.00 210	203.00 217	564.00 202	892.00 206	225.00 207	261.00 201
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
gg-mvs-nofinetune		594.69 178	605.37 180	562.67 205	617.29 213	500.33 203	772.30 173	413.12 248	579.21 172	552.71 212	567.40 168	662.54 267	531.67 197	503.93 178	779.80 245	656.02 229

mvs_anonymous		774.90 188	882.28 194	452.77 190	636.50 214	537.20 206	2348.80 216	120.30 202	1504.30 218	474.40 200	1371.10 217	186.90 203	564.70 203	1078.90 220	219.30 200	256.40 194

casdiffmvs		774.90 188	882.28 194	452.77 190	636.50 214	537.20 206	2348.80 216	120.30 202	1504.30 218	474.40 200	1371.10 217	186.90 203	564.70 203	1078.90 220	219.30 200	256.40 194
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		774.90 188	882.28 194	452.77 190	636.50 214	537.20 206	2348.80 216	120.30 202	1504.30 218	474.40 200	1371.10 217	186.90 203	564.70 203	1078.90 220	219.30 200	256.40 194
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		774.90 188	882.28 194	452.77 190	636.50 214	537.20 206	2348.80 216	120.30 202	1504.30 218	474.40 200	1371.10 217	186.90 203	564.70 203	1078.90 220	219.30 200	256.40 194

baseline1		774.90 188	882.28 194	452.77 190	636.50 214	537.20 206	2348.80 216	120.30 202	1504.30 218	474.40 200	1371.10 217	186.90 203	564.70 203	1078.90 220	219.30 200	256.40 194

casdiffmvs_mvg		774.90 188	882.28 194	452.77 190	636.50 214	537.20 206	2348.80 216	120.30 202	1504.30 218	474.40 200	1371.10 217	186.90 203	564.70 203	1078.90 220	219.30 200	256.40 194
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		774.90 188	882.28 194	452.77 190	636.50 214	537.20 206	2348.80 216	120.30 202	1504.30 218	474.40 200	1371.10 217	186.90 203	564.70 203	1078.90 220	219.30 200	256.40 194

PVSNet	1207.94 6	829.56 198	937.18 201	506.69 202	645.55 221	585.72 216	2477.98 224	130.52 211	1578.29 226	509.50 208	1460.01 224	194.90 213	637.19 217	1170.78 228	267.07 213	297.17 206

FPMVS		1407.00 220	1495.59 222	1141.23 233	648.01 222	893.85 236	4124.00 235	503.81 262	3219.04 243	742.72 230	2498.84 239	157.98 198	1727.83 246	832.93 204	732.98 244	802.00 238

lessismore_v0				569.20 206	667.25 223	644.68 223		96.45 192		428.86 198	1514.17 225	204.21 218	756.58 219	1061.60 219	197.79 196	306.34 208

PVSNet_0	1661.03 9	968.54 204	1066.82 212	673.70 217	706.94 224	695.69 225	2669.02 229	153.52 219	2108.17 235	605.54 217	1679.14 227	213.26 221	886.75 225	1236.76 230	229.01 208	438.67 222

MSLP-MVS++		1242.93 216	1411.08 219	738.48 221	712.71 225	712.68 226	4168.17 236	136.50 213	2276.40 237	613.28 221	2368.60 237	161.61 199	1130.38 240	1964.54 240	297.88 216	372.39 217

MVSTER		890.06 201	1005.91 210	542.52 203	736.13 226	653.90 224	2616.56 228	145.22 217	1692.10 229	555.69 215	1554.72 226	266.25 224	660.02 218	1219.66 229	266.84 212	313.64 210

MVS_111021_LR		1136.45 214	1298.72 217	649.64 212	756.17 227	726.26 228	3785.94 232	138.15 214	2190.64 236	629.63 222	2064.39 233	165.45 202	874.83 224	1678.43 236	279.70 214	347.82 215

DeepC-MVS_fast	2190.19 12	1535.59 221	1886.82 225	481.89 199	847.73 228	830.16 233	7943.84 258	189.23 225	2398.83 238	691.73 225	2341.13 235	209.16 219	230.25 170	1999.25 241	360.46 221	385.25 219
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
JIA-IIPM		804.30 196	835.64 189	710.26 219	885.90 229	895.90 237	455.98 167	668.73 277	1297.17 212	1002.26 241	1001.67 207	655.98 265	756.98 220	667.90 197	885.21 257	477.90 223

RPMNet		787.26 195	829.13 188	661.63 214	885.90 229	895.90 237	455.98 167	610.10 272	1297.17 212	1002.26 241	1001.67 207	655.98 265	611.10 214	667.90 197	885.21 257	477.90 223

ACMMPR		1296.60 218	1480.82 221	743.96 222	899.25 231	763.47 230	4305.47 237	143.90 216	2530.94 240	683.99 223	2346.34 236	201.65 216	1098.25 238	1920.59 239	295.21 215	370.16 216

test_0402		1110.00 213	1260.00 216	660.00 213	900.00 232	780.00 231	3300.00 230	210.00 226	2040.00 234	690.00 224	1950.00 231	300.00 228	810.00 221	1620.00 234	330.00 220	390.00 220

TSAR-MVS + GP.		1386.84 219	1622.84 223	678.81 218	952.13 233	840.17 234	5358.21 242	170.75 222	2650.47 241	713.54 227	2394.28 238	209.42 220	855.56 223	1854.36 238	302.42 217	340.71 213

ambc				999.00 225	999.00 234	999.00 239	999.00 186	999.00 288		999.00 234	999.00 200	999.00 280	999.00 230	999.00 210	999.00 264	999.00 261

OurMVSNet-221017-0		999.00 205	999.00 204	999.00 225	999.00 234	999.00 239	999.00 186	999.00 288	999.00 201	999.00 234	999.00 200	999.00 280	999.00 230	999.00 210	999.00 264	999.00 261

EPMVS		999.00 205	999.00 204	999.00 225	999.00 234	999.00 239	999.00 186	999.00 288	999.00 201	999.00 234	999.00 200	999.00 280	999.00 230	999.00 210	999.00 264	999.00 261

uanet_test		1000.00 207	1000.00 206	1000.00 228	1000.00 237	1000.00 242	1000.00 189	1000.00 291	1000.00 203	1000.00 237	1000.00 203	1000.00 283	1000.00 233	1000.00 213	1000.00 267	1000.00 264

sosnet		1000.00 207	1000.00 206	1000.00 228	1000.00 237	1000.00 242	1000.00 189	1000.00 291	1000.00 203	1000.00 237	1000.00 203	1000.00 283	1000.00 233	1000.00 213	1000.00 267	1000.00 264

USDC		1000.00 207	1000.00 206	1000.00 228	1000.00 237	1000.00 242	1000.00 189	1000.00 291	1000.00 203	1000.00 237	1000.00 203	1000.00 283	1000.00 233	1000.00 213	1000.00 267	1000.00 264

TinyColmap		1000.00 207	1000.00 206	1000.00 228	1000.00 237	1000.00 242	1000.00 189	1000.00 291	1000.00 203	1000.00 237	1000.00 203	1000.00 283	1000.00 233	1000.00 213	1000.00 267	1000.00 264

COLMAP_ROB	2144.59 11	1658.33 222	1869.33 224	1025.33 232	1030.00 241	1023.00 246	5311.00 241	359.00 238	3044.00 242	937.00 233	2892.00 241	332.00 232	1440.00 243	2312.00 243	607.00 227	613.00 228
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
F-COLMAP		1878.17 223	2113.11 226	1173.33 236	1231.00 242	1174.00 247	6297.00 244	392.00 243	3356.00 245	1087.00 243	3082.00 242	361.00 236	1670.00 245	2523.00 245	689.00 234	676.00 233

OpenMVS_ROB	1936.51 10	1959.51 224	2224.88 228	1163.39 235	1253.91 243	1434.22 250	7065.71 248	272.76 228	2472.29 239	1647.54 273	3538.72 245	200.37 214	1496.48 244	2575.17 246	997.45 263	559.48 225

Patchmtry		1090.75 212	1198.88 214	766.38 223	1290.90 244	485.90 201	2423.98 223	1267.30 295	1297.17 212	923.90 231	923.40 198	1215.54 288	990.23 228	667.90 197	779.80 245	823.02 243

PatchT		856.34 199	860.99 192	842.38 224	1290.90 244	880.90 235	790.30 174	1267.30 295	579.21 172	923.90 231	567.40 168	662.54 267	990.23 228	887.56 205	779.80 245	656.02 229

K. test v3		877.74 200	980.16 203	570.46 207	1316.85 246	813.15 232	2565.52 227	103.78 198	1509.49 225	548.33 211	1258.90 213	219.93 222	587.82 212	1102.37 227	196.30 195	310.42 209

PLC	2858.82 16	2192.92 227	2474.00 230	1349.67 238	1407.00 247	1356.00 249	7164.00 249	475.00 255	3970.00 249	1237.00 250	3765.00 248	451.00 243	1891.00 251	3006.00 249	791.00 250	802.00 238
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
CMPMVS	2623.62 15	1983.08 225	2156.14 227	1463.89 246	1414.80 248	1517.00 252	5239.20 240	867.40 282	3310.30 244	1128.70 245	3489.90 244	366.75 237	2030.20 257	2427.60 244	1160.60 276	844.46 246
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
ZD-MVS					1584.00 249	1821.00 272		378.00 241	3721.00 247	1231.00 248	1833.00 229	321.00 231	1224.00 241	2103.00 242	692.00 238

Vis-MVSNet		2877.42 240	3170.00 243	1999.67 261	1673.00 250	2042.00 278	8593.00 262	474.00 254	6452.00 274	1268.00 251	5125.00 262	339.00 233	3004.00 275	4222.00 265	384.00 222	953.00 257
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
PCF-MVS	4335.85 20	2272.23 229	2597.03 232	1297.84 237	1701.20 251	1332.37 248	8105.11 259	451.45 251	4031.84 250	1099.10 244	3966.50 249	467.45 244	1734.05 247	2701.68 248	848.94 254	827.11 244
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
test_0728_SECOND				1451.45 243	1725.60 252	1598.35 256	9203.30 265	315.86 232					2023.43 254	3973.88 259	620.04 230	732.56 235

test0726					1725.60 252	1598.35 256	9203.30 265	315.86 232	5016.02 261	1363.85 253	4894.28 259	387.23 238

SD-MVS		2654.53 236	3055.56 241	1451.45 243	1725.60 252	1598.35 256	9203.30 265	315.86 232	5016.02 261	1363.85 253	4894.28 259	387.23 238	2023.43 254	3973.88 259	620.04 230	732.56 235
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	2531.17 233	2839.56 236	1606.00 247	1732.00 255	1557.00 254	8375.00 261	483.00 256	4370.00 255	1371.00 256	4200.00 250	350.00 234	2207.00 258	3877.00 258	798.00 251	1054.00 268

LF4IMVS		2699.50 238	3049.67 240	1649.00 249	1755.00 256	1689.00 263	8330.00 260	464.00 253	4997.00 260	1528.00 259	4763.00 258	568.00 253	2296.00 260	4215.00 264	827.00 253	962.00 258

DPM-MVS		3268.00 244	3762.89 247	1783.33 254	1756.00 257	1806.00 270	12319.00 281	307.00 230	6319.00 272	1557.00 264	5763.00 265	302.00 229	2609.00 267	5061.00 270	482.00 225	935.00 255

OPM-MVS		3268.00 244	3762.89 247	1783.33 254	1756.00 257	1806.00 270	12319.00 281	307.00 230	6319.00 272	1557.00 264	5763.00 265	302.00 229	2609.00 267	5061.00 270	482.00 225	935.00 255
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
OpenMVS	2352.88 13	2263.08 228	2530.89 231	1459.67 245	1767.00 259	1591.00 255	7932.00 257	399.00 244	3643.00 246	1176.00 246	3569.00 246	297.00 227	1927.00 253	3302.00 251	693.00 239	861.00 247

tpmrst		2557.50 234	2847.12 237	1688.66 250	1784.08 260	1778.25 269	7445.50 255	342.14 235	4471.54 256	1534.55 260	4382.10 254	530.10 250	2361.21 261	4142.81 262	991.22 262	926.51 253

AdaColmap		2570.77 235	2948.61 238	1437.24 242	1873.64 261	1526.60 253	7819.77 256	373.97 239	4970.45 259	1479.29 258	4648.46 256	525.80 249	1904.97 252	4150.42 263	695.69 240	880.14 251

SteuartSystems-ACMMP		2891.50 241	3284.78 244	1711.67 251	1954.00 262	1655.00 262	10117.00 278	445.00 250	5102.00 264	1375.00 257	5126.00 263	351.00 235	2638.00 271	4402.00 266	691.00 237	842.00 245
Skip Steuart: Steuart Systems R&D Blog.
ITE_SJBPF				2014.00 262	1998.00 263	1992.00 276		701.00 278	5989.00 266	1812.00 277	3612.00 247	650.00 261	2852.00 274	4601.00 268	1195.00 277	1198.00 274

tpm2		3617.85 248	4007.23 250	2449.73 268	2012.71 264	1698.05 264	7351.19 251	869.29 283	6132.06 267	1588.28 267	8007.42 283	1281.09 289	3888.11 287	7472.04 288	1351.00 278	1763.02 284

tpm cat1		3617.85 248	4007.23 250	2449.73 268	2012.71 264	1698.05 264	7351.19 251	869.29 283	6132.06 267	1588.28 267	8007.42 283	1281.09 289	3888.11 287	7472.04 288	1351.00 278	1763.02 284

CostFormer		3617.85 248	4007.23 250	2449.73 268	2012.71 264	1698.05 264	7351.19 251	869.29 283	6132.06 267	1588.28 267	8007.42 283	1281.09 289	3888.11 287	7472.04 288	1351.00 278	1763.02 284

tpm		3617.85 248	4007.23 250	2449.73 268	2012.71 264	1698.05 264	7351.19 251	869.29 283	6132.06 267	1588.28 267	8007.42 283	1281.09 289	3888.11 287	7472.04 288	1351.00 278	1763.02 284

CHOSEN 280x420		2340.81 230	2643.03 233	1434.14 239	2025.55 268	1629.36 259	6542.40 245	412.49 245	4219.70 252	1547.02 261	4328.52 251	650.74 262	1798.26 248	3333.17 252	727.72 241	874.79 248

CHOSEN 1792x2688		2340.81 230	2643.03 233	1434.14 239	2025.55 268	1629.36 259	6542.40 245	412.49 245	4219.70 252	1547.02 261	4328.52 251	650.74 262	1798.26 248	3333.17 252	727.72 241	874.79 248

HyFIR lowres test		2340.81 230	2643.03 233	1434.14 239	2025.55 268	1629.36 259	6542.40 245	412.49 245	4219.70 252	1547.02 261	4328.52 251	650.74 262	1798.26 248	3333.17 252	727.72 241	874.79 248

DVP-MVS++		3981.10 254	4731.32 259	1730.42 252	2191.51 271	1949.98 274	16473.90 290	355.33 236	7172.90 283	1622.98 271	7879.79 281	434.33 241	2428.11 263	5762.12 273	689.04 235	813.18 241

DVP-MVS		3981.10 254	4731.32 259	1730.42 252	2191.51 271	1949.98 274	16473.90 290	355.33 236	7172.90 283	1622.98 271	7879.79 281	434.33 241	2428.11 263	5762.12 273	689.04 235	813.18 241
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	3146.67 242	3537.00 245	1975.67 258	2310.00 273	2005.00 277	10100.00 277	626.00 275	5753.00 265	1803.00 276	5179.00 264	487.00 245	2622.00 269	4550.00 267	1025.00 271	1300.00 275

TSAR-MVS + MP.		3528.01 247	4065.89 254	1914.35 257	2349.10 274	2141.30 279	12362.70 283	417.60 249	6717.80 278	1759.40 275	6497.50 268	518.18 248	2629.38 270	5164.32 272	806.40 252	972.38 260
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	2670.71 237	3021.57 239	1618.12 248	2377.67 275	1751.39 268	8915.70 264	567.44 270	4569.74 257	1236.84 249	4615.63 255	513.23 247	2291.32 259	3515.48 255	882.39 256	811.66 240

GST-MVS		4000.00 256	4533.33 257	2400.00 267	2400.00 276	2400.00 282	7200.00 250	2400.00 299	7200.00 285	2400.00 287	7200.00 275	2400.00 293	2400.00 262	7200.00 286	2400.00 290	2400.00 289

MVS_111021_HR		3742.80 252	4330.34 255	1980.20 259	2484.31 277	2259.52 281	14973.80 288	515.90 269	6500.13 275	1949.21 278	6146.89 267	535.66 251	2593.66 266	4880.76 269	986.37 261	1087.43 269

DeepC-MVS	3917.13 19	3155.06 243	3601.83 246	1814.72 256	2515.52 278	1941.53 273	10432.50 279	589.42 271	4789.45 258	1298.65 252	7677.31 280	578.35 254	2589.53 265	3611.78 257	923.52 259	913.10 252
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	3374.90 246	3806.99 249	2078.63 263	2535.47 279	2499.25 288	8816.16 263	456.05 252	6255.60 271	1664.52 274	6704.88 270	629.95 260	2768.38 272	6343.93 284	856.35 255	968.25 259
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
FOURS1					2643.17 280	2465.14 283	13996.40 285	493.26 257	7619.38 286	2107.24 279

MSC_two_6792asdad				2237.56 264	2643.17 280	2465.14 283		493.26 257					3088.29 280	6075.14 280	1078.39 272	1159.26 270

No_MVS				2237.56 264	2643.17 280	2465.14 283		493.26 257					3088.29 280	6075.14 280	1078.39 272	1159.26 270

test_one_0601					2643.17 280	2465.14 283		493.26 257	7619.38 286	2107.24 279	7416.93 277	610.24 257

SED-MVS		4062.74 257	4671.13 258	2237.56 264	2643.17 280	2465.14 283	13996.40 285	493.26 257	7619.38 286	2107.24 279	7416.93 277	610.24 257	3088.29 280	6075.14 280	1078.39 272	1159.26 270

IU-MVS					2725.60 285	2598.35 289		515.86 265	7016.02 279	2363.85 283				5973.88 276	1620.04 284	1732.56 280

OPU-MVS				2451.45 272	2725.60 285	2598.35 289	9203.30 265				6894.28 271	887.23 275	3023.43 276	5973.88 276	1620.04 284	1732.56 280

test_241102_ONE					2725.60 285	2598.35 289		515.86 265	7016.02 279	2363.85 283	6894.28 271	887.23 275	3023.43 276

MSP-MVS		4296.20 258	4911.12 262	2451.45 272	2725.60 285	2598.35 289	16203.30 289	515.86 265	7016.02 279	2363.85 283	6894.28 271	887.23 275	3023.43 276	5973.88 276	1620.04 284	1732.56 280
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		2125.39 226	2452.68 229	1143.53 234	2938.33 289	1446.92 251	6083.19 243	391.74 242	3801.71 248	1202.10 247	3439.72 243	492.73 246	1304.35 242	3048.25 250	676.32 233	679.32 234

EGC-MVSNET		2819.75 239	3096.89 242	1988.33 260	3105.00 290	2241.00 280	9480.00 269	640.00 276	4209.00 251	1583.00 266	4740.00 257	547.00 252	2797.00 273	2644.00 247	924.00 260	927.00 254

MAR-MVS		3973.16 253	4387.92 256	2728.86 274	3345.27 291	3341.39 295	11403.90 280	798.76 280	6555.62 277	2569.29 288	6514.86 269	834.97 274	3237.43 284	5891.08 275	1577.54 283	1607.76 276
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		4380.83 259	4906.56 261	2803.67 275	3844.00 292	3116.00 294	13454.00 284	901.00 287	6511.00 276	2794.00 289	7365.00 276	754.00 271	3634.00 285	6622.00 285	1914.00 289	1661.00 279

CLD-MVS		7338.25 261	8341.00 264	4330.00 277	4902.00 293	4991.00 296	23318.00 293	728.00 279	14437.00 300	4378.00 292	13379.00 295	824.00 273	5708.00 291	11429.00 301	1674.00 288	2291.00 288
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
OMC-MVS		5022.26 260	5748.82 263	2842.58 276	4905.27 294	3101.27 293	14933.60 287	812.24 281	9278.40 290	2959.29 290	8800.17 287	1092.24 287	3806.30 286	7568.54 292	1389.60 282	1620.18 278

LS3D		7684.71 262	8776.23 265	4410.16 278	5298.55 295	5631.53 297	34329.90 295	1504.57 297	11554.00 299	3896.41 291	15111.00 296	812.19 272	5985.63 292	3516.20 256	2963.23 291	1613.31 277

MVE	10021.00 22	10550.67 270	10002.44 273	12195.33 287	6242.00 296	8768.00 299	30896.00 294	4451.00 300	10331.00 298	6247.00 293	18296.00 297	283.00 226	21484.00 301	7364.00 287	5912.00 293	6334.00 291
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CNLPA		10738.67 271	11772.44 274	7637.33 279	9120.00 297	8206.00 298	22252.00 292	2010.00 298	24984.00 301	7458.00 294	22596.00 298	2940.00 294	10260.00 300	11100.00 300	3492.00 292	4446.00 290

ZNCC-MVS		9999.00 263	9999.00 266	9999.00 280	9999.00 298	9999.00 300	9999.00 270	9999.00 303	9999.00 291	9999.00 295	9999.00 288	9999.00 296	9999.00 293	9999.00 293	9999.00 294	9999.00 292

patch_mono-2		10000.00 264	10000.00 267	10000.00 281	10000.00 299	10000.00 301	10000.00 271	10000.00 304	10000.00 292	10000.00 296	10000.00 289	10000.00 297	10000.00 294	10000.00 294	10000.00 295	10000.00 293

dcpmvs_2		10000.00 264	10000.00 267	10000.00 281	10000.00 299	10000.00 301	10000.00 271	10000.00 304	10000.00 292	10000.00 296	10000.00 289	10000.00 297	10000.00 294	10000.00 294	10000.00 295	10000.00 293

DCPMVS		10000.00 264	10000.00 267	10000.00 281	10000.00 299	10000.00 301	10000.00 271	10000.00 304	10000.00 292	10000.00 296	10000.00 289	10000.00 297	10000.00 294	10000.00 294	10000.00 295	10000.00 293

UA-Net		10000.00 264	10000.00 267	10000.00 281	10000.00 299	10000.00 301	10000.00 271	10000.00 304	10000.00 292	10000.00 296	10000.00 289	10000.00 297	10000.00 294	10000.00 294	10000.00 295	10000.00 293

uncertanet		10000.00 264	10000.00 267	10000.00 281	10000.00 299	10000.00 301	10000.00 271	10000.00 304	10000.00 292	10000.00 296	10000.00 289	10000.00 297	10000.00 294	10000.00 294	10000.00 295	10000.00 293

uanet		10000.00 264	10000.00 267	10000.00 281	10000.00 299	10000.00 301	10000.00 271	10000.00 304	10000.00 292	10000.00 296	10000.00 289	10000.00 297	10000.00 294	10000.00 294	10000.00 295	10000.00 293

LTVRE_ROB	20565.47 23	23378.08 272	22805.00 275	25097.33 288	15500.00 305	19201.00 307	42712.00 296	6055.00 301	38388.00 302	16926.00 302	38534.00 299	7071.00 295	35653.00 302	29475.00 302	10584.00 301	20438.00 300
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		32606.17 273	34443.44 276	27094.33 289	29249.00 306	25246.00 308	51144.00 297	6705.00 302	42886.00 303	22888.00 303	48534.00 300	13263.00 303	37507.00 303	79298.00 303	16024.00 302	18530.00 299

114514_t		99999.00 274	99999.00 277	99999.00 290	99999.00 307	99999.00 309	99999.00 298	99999.00 310	99999.00 304	99999.00 304	99999.00 301	99999.00 304	99999.00 304	99999.00 304	99999.00 303	99999.00 301

PHI-MVS		99999.00 274	99999.00 277	99999.00 290	99999.00 307	99999.00 309	99999.00 298	99999.00 310	99999.00 304	99999.00 304	99999.00 301	99999.00 304	99999.00 304	99999.00 304	99999.00 303	99999.00 301

XVG-OURS-SEG-HR		999999.00 278	999999.00 279	999999.00 292	999999.00 309	999999.00 311	999999.00 300	999999.00 312	999999.00 306	999999.00 306	999999.00 303	999999.00 306	999999.00 306	999999.00 306	999999.00 305	999999.00 303

XVG-OURS		999999.00 278	999999.00 279	999999.00 292	999999.00 309	999999.00 311	999999.00 300	999999.00 312	999999.00 306	999999.00 306	999999.00 303	999999.00 306	999999.00 306	999999.00 306	999999.00 305	999999.00 303

XVG-ACMP-BASELINE		999999.00 278	999999.00 279	999999.00 292	999999.00 309	999999.00 311	999999.00 300	999999.00 312	999999.00 306	999999.00 306	999999.00 303	999999.00 306	999999.00 306	999999.00 306	999999.00 305	999999.00 303

MVSMamba_pp		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

MGCFI-Net		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

sasdasda		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

dmvs_re		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

SDMVSNet		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

dmvs_testset		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

sd_testset		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

iter_conf05_11		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

bld_raw_dy_0_64		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

test2506		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

test1111		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

ECVR-MVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

test_blank		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

tt0805		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

eth-test					10000000.00 312

Anonymous20240521		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

cl22		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

miper_ehance_all_eth		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

miper_enhance_ethall		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

cl____		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

DIV-MVS_self_test		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

eth_miper_zixun_eth		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

ET-MVSNet_ETH3D		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

UniMVSNet_ETH3D		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

miper_lstm_enhance		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

D2MVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

test_yl		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

thisisatest0530		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

Anonymous20240529		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

Anonymous202405211		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

DCV-MVSNet		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

tttt0517		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

our_test_3		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

thisisatest0515		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

ppachtmachnet_test		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

SMA-MVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306
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		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part2					10000000.00 312	10000000.00 314				10000000.00 309

thres100view900		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

tfpnnormal		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

tfpn200view9		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

c3_l		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

IterMVS-SCA-FT		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

pmmvs6		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

pmmvs5		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

Anonymous20231211		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

pmmvs-eth3d		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

Anonymous20231206		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

SCA		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

Patchmatch-test		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

Patchmatch-RL test		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

canonicalmvs		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

anonymousdsp		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

FIs		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

FC-MVSNet-test		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

sosnet-low-res		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

AllTest		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

TestCases				10000000.00 295	10000000.00 312	10000000.00 314		10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

iter_conf05		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

mamv4		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

HPM-MVS++		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

XVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

pm-mvs1		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

X-MVStestdata		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

APDe-MVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
APD-MVS_3200maxsize		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

pmmvs4		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

test-LLR		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

TESTMET0.1,1		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

test-mter		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

testgi		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

test20.03		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

thres600view7		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

MP-MVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

thres400		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

test123		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

thres200		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

test0.0.03 1		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

pmmvs3		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

EMVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

E-PMN		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

PGM-MVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

MCST-MVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

MVS_Test		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

PMMVS2		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

PM-MVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

HQP_MVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

plane_prior7					10000000.00 312	10000000.00 314

plane_prior6					10000000.00 312	10000000.00 314						10000000.00 309

plane_prior1					10000000.00 312

mPP-MVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

mvsmamba		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

HPM-MVS_fast		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

HPM-MVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
LPG-MVS_test		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

LGP-MVS_train				10000000.00 295	10000000.00 312	10000000.00 314		10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

EPNet_dtu		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP-NCC					10000000.00 312		10000000.00 303		10000000.00 309	10000000.00 309

ACMP_Plane					10000000.00 312		10000000.00 303		10000000.00 309	10000000.00 309

CNVR-MVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

NCCC		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

CP-MVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

NP-MVS					10000000.00 312	10000000.00 314					10000000.00 306

CPTT-MVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

HQP-MVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

IS-MVSNet		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

PAPM_NR		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

PAPR		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

Vis-MVSNet (Re-imp)		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

PatchMatch-RL		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

TDRefinement		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

EPP-MVSNet		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

PMMVS		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

PAPM		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

ACMMP		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306
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		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

wuyk23d		10000000.00 281	10000000.00 284	10000000.00 295	10000000.00 312	10000000.00 314	10000000.00 303	10000000.00 315	10000000.00 309	10000000.00 309	10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

APD-MVS		1000000000.00 390	1000000000.00 393	1000000000.00 406	1000000000.00 431	1000000000.00 431	1000000000.00 417	1000000000.00 431	1000000000.00 424	1000000000.00 425	1000000000.00 422	1000000000.00 427	1000000000.00 425	1000000000.00 424	1000000000.00 423	1000000000.00 421
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
WAC-MVS						248.46 178								422.23 171

PC_three_1452									7619.38 286	2107.24 279	7416.93 277	610.24 257	3088.29 280	6075.14 280	1078.39 272	1159.26 270

test_241102_TWO								515.86 265	7016.02 279	2363.85 283	6894.28 271	887.23 275	3023.43 276	5973.88 276	1620.04 284	1732.56 280

test_0728_THIRD									5016.02 261	1363.85 253	4894.28 259	387.23 238	2023.43 254	3973.88 259	620.04 230	732.56 235

GSMVS																10000000.00 306

sam_mvs1												10000000.00 309				10000000.00 306

sam_mvs												10000000.00 309

MTGPA								10000000.00 315

test_post1							10000000.00 303				10000000.00 306	10000000.00 309	10000000.00 309	10000000.00 309

test_post											10000000.00 306	10000000.00 309	10000000.00 309

patchmatchnet-post											10000000.00 306	10000000.00 309	10000000.00 309

MTMP							10000000.00 303	10000000.00 315

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								10000000.00 315					10000000.00 309	10000000.00 309	10000000.00 308	10000000.00 306

plane_prior4											10000000.00 306

plane_prior3						10000000.00 314			10000000.00 309	10000000.00 309

plane_prior2							10000000.00 303		10000000.00 309

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								99.00 196

HQP5-MVS						10000000.00 314

BP-MVS														10000000.00 309

HQP4-MVS										10000000.00 309			10000000.00 309			10000000.00 306

HQP3-MVS								10000000.00 315							10000000.00 308

HQP2-MVS												10000000.00 309

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															10000000.00 308

ACMMP++															10000000.00 308

Test By Simon												990.00 279

High-resolution multi-view benchmark