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

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_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1				0.00 1	0.00 1	0.00 1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

原ACMM1				0.00 1	0.00 1	0.00 1		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

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+-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

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

SPE-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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

dp		87.20 142	113.80 146	7.42 129	10.50 148	8.88 137	298.82 163	2.70 130	510.35 181	7.79 135	172.93 156	3.37 125	9.16 136	14.00 147	3.71 125	4.23 125

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

BH-w/o		40.00 137	40.00 139	40.00 145	40.00 153	40.00 154	40.00 150	40.00 177	40.00 153	40.00 153	40.00 147	40.00 172	40.00 153	40.00 151	40.00 165	40.00 161

BH-untuned		40.00 137	40.00 139	40.00 145	40.00 153	40.00 154	40.00 150	40.00 177	40.00 153	40.00 153	40.00 147	40.00 172	40.00 153	40.00 151	40.00 165	40.00 161

BH-RMVSNet		40.00 137	40.00 139	40.00 145	40.00 153	40.00 154	40.00 150	40.00 177	40.00 153	40.00 153	40.00 147	40.00 172	40.00 153	40.00 151	40.00 165	40.00 161

TR-MVS		40.00 137	40.00 139	40.00 145	40.00 153	40.00 154	40.00 150	40.00 177	40.00 153	40.00 153	40.00 147	40.00 172	40.00 153	40.00 151	40.00 165	40.00 161

new_pmnet		88.14 143	98.62 144	56.70 149	98.14 164	56.07 159	246.79 158	15.37 160	148.06 158	50.77 157	143.13 154	23.35 156	62.65 157	93.26 156	68.71 174	51.38 171

N_pmnet		88.14 143	98.62 144	56.70 149	98.14 164	56.07 159	246.79 158	15.37 160	148.06 158	50.77 157	143.13 154	23.35 156	62.65 157	93.26 156	68.71 174	51.38 171

MTAPA		833442.10 290	1111233.77 296	67.09 151	65.59 158	64.81 161	284.50 160	10000000.00 328	219.97 163	59.62 159	229.89 167	12.72 152	103.00 172	203.67 173	27.93 152	33.46 151

MP-MVS-pluss		833433.63 289	1111219.60 295	75.70 155	74.28 159	73.29 162	284.50 160	11.35 155	238.58 164	65.86 160	255.35 172	14.55 153	115.69 174	10000000.00 322	31.94 153	38.12 159
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
ACMMP_NAP		118.81 148	133.18 150	75.70 155	74.28 159	73.29 162	284.50 160	11.35 155	238.58 164	65.86 160	255.35 172	14.55 153	115.69 174	222.18 174	31.94 153	38.12 159

CANet		110.62 145	124.04 147	70.34 152	82.03 161	74.27 164	325.54 164	25.25 163	207.16 160	69.28 162	194.38 157	27.53 158	95.79 166	147.76 160	37.43 155	40.97 165

CANet_DTU		110.62 145	124.04 147	70.34 152	82.03 161	74.27 164	325.54 164	25.25 163	207.16 160	69.28 162	194.38 157	27.53 158	95.79 166	147.76 160	37.43 155	40.97 165

UGNet		110.62 145	124.04 147	70.34 152	82.03 161	74.27 164	325.54 164	25.25 163	207.16 160	69.28 162	194.38 157	27.53 158	95.79 166	147.76 160	37.43 155	40.97 165
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022
FMVSNet5		124.76 149	140.93 151	76.26 157	107.44 167	100.17 171	329.88 167	27.12 169	259.44 169	74.30 165	204.34 160	30.74 161	92.41 159	196.98 163	38.15 158	36.19 152

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

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

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

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

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

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

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

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

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

DSMNet-mixed		131.33 156	143.00 158	96.33 167	99.00 166	81.00 167	201.00 157	45.00 182	335.00 176	99.00 175	251.00 171	38.00 171	110.00 173	120.00 159	99.00 180	98.00 176

BP-MVS1		202.65 160	232.15 162	114.16 168	183.40 178	141.78 178	655.87 182	24.69 162	372.56 177	109.76 176	356.89 174	47.15 176	139.51 176	284.15 176	54.86 172	61.20 173

FE-MVS		207.10 161	234.26 163	125.61 169	180.34 177	153.23 179	635.64 181	30.05 176	378.38 178	127.68 177	377.08 175	48.95 177	154.43 177	266.67 175	63.56 173	69.18 174

FA-MVS(test-final)		261.15 162	293.29 164	164.72 170	236.23 181	199.99 184	800.05 188	42.35 181	475.87 180	155.47 178	470.67 177	58.49 178	205.24 179	319.44 177	81.03 177	88.93 175

kuosan		267.89 164	301.05 166	168.41 171	244.05 182	177.28 180	667.98 183	65.76 184	533.41 182	157.79 179	492.01 178	104.69 193	226.72 180	364.47 180	79.31 176	101.21 178

DP-MVS		264.78 163	296.02 165	171.04 172	191.70 179	183.96 181	827.10 189	78.36 191	438.24 179	176.64 180	435.12 176	65.04 180	230.52 182	334.02 178	117.96 187	98.64 177

SSC-MVS		320.23 166	364.09 168	188.66 173	260.78 184	193.84 182	975.93 196	73.11 189	596.72 187	185.29 181	589.02 184	74.47 182	246.01 183	427.42 183	94.06 179	126.12 181

WB-MVS		316.44 165	357.41 167	193.51 174	257.06 183	213.32 186	914.45 190	49.03 183	600.77 188	186.42 182	634.00 189	75.03 183	251.35 184	411.39 181	88.55 178	115.87 180

dongtai		360.45 169	401.64 171	236.89 179	303.10 189	262.16 194	963.12 193	72.78 187	622.82 191	199.37 183	708.06 192	130.96 200	310.90 189	506.46 193	108.11 181	137.60 186

testing3		418.10 177	469.06 179	265.23 186	335.69 193	290.63 197	1240.88 212	93.72 200	717.99 196	215.31 184	811.97 204	232.41 236	358.74 194	458.67 184	114.88 182	146.32 188

testing11		348.86 168	393.09 170	216.15 175	275.24 186	239.53 187	915.55 191	72.35 186	679.89 194	215.75 185	633.79 188	118.08 197	276.62 185	509.56 194	117.61 186	132.30 182

testing91		347.05 167	389.92 169	218.43 176	275.92 187	241.43 188	923.71 192	71.70 185	667.65 193	217.04 186	629.00 187	113.33 196	281.39 186	495.50 186	115.45 183	132.47 183

WB-MVSnew		404.84 175	458.00 177	245.36 181	374.70 198	320.27 200	1193.74 210	72.90 188	773.77 202	238.30 187	688.22 191	90.05 186	308.59 188	532.76 197	157.54 196	107.21 179

EG-PatchMatch MVS		437.03 179	493.12 183	268.77 187	264.80 185	260.20 193	1491.80 217	98.00 204	723.20 198	238.80 188	722.40 193	63.10 179	382.00 199	629.00 205	207.00 210	164.10 195

RPSCF		394.81 174	445.63 176	242.35 180	276.55 188	253.63 190	1207.27 211	90.69 199	715.56 195	241.57 189	684.87 190	111.96 195	320.02 190	548.38 198	133.81 188	153.39 191

UWE-MVS		387.98 172	438.66 175	235.93 177	349.32 195	257.61 192	1081.50 204	82.45 195	637.74 192	257.12 190	738.54 194	134.25 201	308.00 187	531.93 196	135.11 189	142.17 187

testing99		408.82 176	462.15 178	248.86 183	322.45 192	269.42 195	1118.93 207	73.26 190	719.36 197	262.28 191	772.10 195	150.98 206	327.08 191	601.98 201	137.99 190	150.07 189

Syy-MVS		370.76 170	415.60 173	236.25 178	310.54 190	210.76 185	965.13 194	98.58 205	746.06 199	266.26 192	788.85 198	91.37 187	364.76 195	357.17 179	116.42 184	133.22 184

myMVS_eth3d		390.90 173	437.44 174	251.28 184	310.54 190	255.86 191	965.13 194	98.58 205	746.06 199	266.26 192	788.85 198	154.95 207	364.76 195	490.19 185	116.42 184	133.22 184

ETVMVS		443.50 182	498.07 184	279.78 188	378.05 201	321.57 201	1163.68 209	87.12 196	897.50 209	269.81 194	822.83 205	141.20 205	334.53 193	568.21 200	154.21 192	183.26 199

testing222		430.52 178	487.50 182	259.56 185	379.87 202	282.69 196	1138.34 208	81.30 193	880.86 206	281.58 195	834.27 206	135.83 203	333.22 192	514.90 195	140.56 191	162.76 192

ADS-MVSNet2		443.33 180	482.84 180	324.79 197	434.94 210	387.73 208	1110.57 205	87.69 197	887.02 207	282.92 196	779.29 196	98.57 191	422.76 206	502.40 187	162.19 200	163.87 193

ADS-MVSNet		443.33 180	482.84 180	324.79 197	434.94 210	387.73 208	1110.57 205	87.69 197	887.02 207	282.92 196	779.29 196	98.57 191	422.76 206	502.40 187	162.19 200	163.87 193

DP-MVS Recon		516.25 188	581.17 189	321.48 196	361.02 196	429.00 212	1995.36 224	78.48 192	796.20 203	283.32 198	796.02 200	96.78 188	382.98 200	636.72 207	186.66 207	152.46 190

MVP-Stereo		473.58 183	533.67 185	293.33 189	376.00 199	318.00 198	1461.00 215	96.00 201	835.00 204	290.00 199	804.00 201	97.00 189	383.00 201	688.00 212	156.00 193	179.00 197
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MS-PatchMatch		473.58 183	533.67 185	293.33 189	376.00 199	318.00 198	1461.00 215	96.00 201	835.00 204	290.00 199	804.00 201	97.00 189	383.00 201	688.00 212	156.00 193	179.00 197

WBMVS		655.88 194	770.84 199	310.98 194	391.79 204	353.00 204	2280.68 226	99.17 208	1776.79 241	301.20 201	1123.23 223	187.34 222	390.28 203	620.39 204	156.98 195	189.66 201

PatchmatchNet		492.52 185	551.22 187	316.40 195	400.20 206	357.90 206	1277.10 213	115.80 212	1034.60 218	315.90 202	874.00 207	155.10 208	402.20 204	629.50 206	158.80 197	189.10 200
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
UBG		667.82 196	787.71 200	308.16 193	385.94 203	327.65 202	1718.51 220	117.00 214	1942.46 246	317.12 203	1488.73 237	183.89 214	404.82 205	763.70 214	172.02 203	192.01 203

DELS-MVS		514.57 187	587.73 190	295.12 191	343.03 194	328.09 203	1540.48 219	116.22 213	988.59 210	325.44 204	906.22 208	119.86 199	365.72 197	788.60 215	161.09 199	191.55 202
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
ACMH+	729.97 2	661.38 195	754.00 197	383.51 200	368.96 197	376.38 207	2483.74 238	82.42 194	1089.25 219	333.39 205	1219.68 224	66.53 181	573.60 223	957.86 221	184.14 206	200.56 204

tpmvs		501.65 186	567.42 188	304.33 192	395.39 205	356.32 205	1512.04 218	216.53 240	994.15 211	350.16 206	804.16 203	119.38 198	380.98 198	555.14 199	159.87 198	175.69 196

IterMVS		615.05 192	691.66 195	385.23 201	516.40 213	454.80 213	1863.80 222	102.10 209	1142.20 220	364.10 207	1093.20 222	135.00 202	480.40 209	826.90 216	181.20 204	220.50 205
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
IB-MVS	872.44 4	616.41 193	700.96 196	362.78 199	426.10 209	409.25 210	1822.69 221	124.42 223	1186.23 221	366.85 208	1079.42 220	190.60 224	451.78 208	930.72 220	181.59 205	227.30 206
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
new-patchmatchnet		766.12 199	859.03 204	487.38 214	595.68 215	536.14 218	2346.27 228	142.51 228	1488.08 228	422.43 209	1361.32 228	163.65 211	628.60 228	1003.74 230	207.61 211	297.41 220

SixPastTwentyTwo		773.62 200	869.37 206	486.35 213	603.45 217	547.15 227	2532.14 239	106.92 211	1434.95 227	428.08 210	1360.56 227	165.15 212	628.96 229	984.09 222	209.01 212	282.94 217

lessismore_v0				569.20 219	667.25 236	644.68 236		96.45 203		428.86 211	1514.17 238	204.21 231	756.58 232	1061.60 232	197.79 209	306.34 221

IterMVS-LS		758.94 198	856.56 203	466.10 211	606.60 218	546.80 226	2309.90 227	122.20 222	1402.80 226	463.50 212	1348.20 226	192.60 225	574.60 224	1028.60 231	234.60 222	276.90 216
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
mvs_anonymous		774.90 201	882.28 207	452.77 203	636.50 227	537.20 219	2348.80 229	120.30 215	1504.30 229	474.40 213	1371.10 229	186.90 215	564.70 216	1078.90 233	219.30 213	256.40 207

casdiffmvs		774.90 201	882.28 207	452.77 203	636.50 227	537.20 219	2348.80 229	120.30 215	1504.30 229	474.40 213	1371.10 229	186.90 215	564.70 216	1078.90 233	219.30 213	256.40 207
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		774.90 201	882.28 207	452.77 203	636.50 227	537.20 219	2348.80 229	120.30 215	1504.30 229	474.40 213	1371.10 229	186.90 215	564.70 216	1078.90 233	219.30 213	256.40 207
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		774.90 201	882.28 207	452.77 203	636.50 227	537.20 219	2348.80 229	120.30 215	1504.30 229	474.40 213	1371.10 229	186.90 215	564.70 216	1078.90 233	219.30 213	256.40 207

baseline1		774.90 201	882.28 207	452.77 203	636.50 227	537.20 219	2348.80 229	120.30 215	1504.30 229	474.40 213	1371.10 229	186.90 215	564.70 216	1078.90 233	219.30 213	256.40 207

casdiffmvs_mvg		774.90 201	882.28 207	452.77 203	636.50 227	537.20 219	2348.80 229	120.30 215	1504.30 229	474.40 213	1371.10 229	186.90 215	564.70 216	1078.90 233	219.30 213	256.40 207
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		774.90 201	882.28 207	452.77 203	636.50 227	537.20 219	2348.80 229	120.30 215	1504.30 229	474.40 213	1371.10 229	186.90 215	564.70 216	1078.90 233	219.30 213	256.40 207

ACMH	993.80 5	967.92 216	1106.11 226	553.33 217	494.00 212	534.00 217	3581.00 244	136.00 225	1585.00 238	478.00 220	1871.00 243	90.00 184	839.00 235	1460.00 244	260.00 223	287.00 218
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PVSNet	1207.94 6	829.56 211	937.18 214	506.69 215	645.55 234	585.72 229	2477.98 237	130.52 224	1578.29 237	509.50 221	1460.01 236	194.90 226	637.19 230	1170.78 241	267.07 226	297.17 219

Gipuma		689.75 197	767.00 198	458.00 210	613.00 225	549.00 228	1943.00 223	187.00 237	1230.00 222	518.00 222	1092.00 221	203.00 230	564.00 215	892.00 219	225.00 220	261.00 214
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMVS	863.65 3	957.08 215	1054.11 224	666.00 229	401.00 207	495.00 215	3790.00 246	279.00 242	1607.00 239	521.00 223	1745.00 241	90.00 184	1105.00 252	639.00 208	415.00 237	398.00 234
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
K. test v3		877.74 213	980.16 216	570.46 220	1316.85 259	813.15 245	2565.52 240	103.78 210	1509.49 236	548.33 224	1258.90 225	219.93 235	587.82 225	1102.37 240	196.30 208	310.42 222

GG-mvs-BLEND				596.01 221	611.29 222	600.33 230	790.30 185	513.12 276		552.71 225	567.40 179	662.54 280	531.67 210	503.93 189	779.80 258	656.02 242

gg-mvs-nofinetune		594.69 189	605.37 191	562.67 218	617.29 226	500.33 216	772.30 184	413.12 261	579.21 183	552.71 225	567.40 179	662.54 280	531.67 210	503.93 189	779.80 258	656.02 242

CR-MVSNet		612.36 191	617.81 194	596.01 221	611.29 222	600.33 230	790.30 185	513.12 276	579.21 183	552.71 225	567.40 179	662.54 280	531.67 210	503.93 189	779.80 258	656.02 242

MVSTER		890.06 214	1005.91 223	542.52 216	736.13 239	653.90 237	2616.56 241	145.22 230	1692.10 240	555.69 228	1554.72 239	266.25 237	660.02 231	1219.66 242	266.84 225	313.64 223

ACMP	1246.57 7	1086.24 224	1235.17 228	639.45 224	596.53 216	639.91 235	3904.24 247	152.04 231	1851.54 243	566.58 229	1997.95 245	138.50 204	938.30 239	1605.46 246	303.70 232	340.14 225
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PVSNet_0	1661.03 9	968.54 217	1066.82 225	673.70 230	706.94 237	695.69 238	2669.02 242	153.52 232	2108.17 248	605.54 230	1679.14 240	213.26 234	886.75 238	1236.76 243	229.01 221	438.67 235

tmp_tt		371.08 171	412.78 172	246.00 182	231.00 180	197.00 183	1293.00 214	376.00 253	756.00 201	609.00 231	71.00 152	106.00 194	195.00 178	102.00 158	171.00 202	346.00 227

RE-MVS-def			610.10 192		610.10 220	610.10 233	610.10 179	610.10 285	610.10 189	610.10 232	610.10 185	610.10 268		610.10 202	610.10 241	610.10 239

SR-MVS		610.10 190	610.10 192	610.10 223	610.10 220	610.10 233	610.10 179	610.10 285	610.10 189	610.10 232	610.10 185	610.10 268	610.10 226	610.10 202	610.10 241	610.10 239

MSLP-MVS++		1242.93 229	1411.08 232	738.48 234	712.71 238	712.68 239	4168.17 249	136.50 226	2276.40 250	613.28 234	2368.60 250	161.61 210	1130.38 253	1964.54 253	297.88 229	372.39 230

MVS_111021_LR		1136.45 227	1298.72 230	649.64 225	756.17 240	726.26 241	3785.94 245	138.15 227	2190.64 249	629.63 235	2064.39 246	165.45 213	874.83 237	1678.43 249	279.70 227	347.82 228

ACMMPR		1296.60 231	1480.82 234	743.96 235	899.25 244	763.47 243	4305.47 250	143.90 229	2530.94 253	683.99 236	2346.34 249	201.65 229	1098.25 251	1920.59 252	295.21 228	370.16 229

test_0402		1110.00 226	1260.00 229	660.00 226	900.00 245	780.00 244	3300.00 243	210.00 239	2040.00 247	690.00 237	1950.00 244	300.00 241	810.00 234	1620.00 247	330.00 233	390.00 233

DeepC-MVS_fast	2190.19 12	1535.59 234	1886.82 238	481.89 212	847.73 241	830.16 246	7943.84 271	189.23 238	2398.83 251	691.73 238	2341.13 248	209.16 232	230.25 181	1999.25 254	360.46 234	385.25 232
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ACMM	1311.08 8	1165.06 228	1332.72 231	662.07 228	584.90 214	715.99 240	4373.59 251	153.99 233	1880.27 244	709.02 239	2316.97 247	188.63 223	939.89 240	1484.30 245	302.78 231	330.34 224
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
TSAR-MVS + GP.		1386.84 232	1622.84 236	678.81 231	952.13 246	840.17 247	5358.21 255	170.75 235	2650.47 254	713.54 240	2394.28 251	209.42 233	855.56 236	1854.36 251	302.42 230	340.71 226

MG-MVS		1256.50 230	1432.00 233	730.00 233	610.00 219	760.00 242	4720.00 252	169.00 234	1920.00 245	723.00 241	2510.00 253	201.00 228	1050.00 250	1645.00 248	390.00 236	380.00 231

CSCG		826.03 210	963.29 215	414.24 202	421.52 208	426.11 211	2230.35 225	179.52 236	1827.44 242	733.43 242	933.12 210	281.25 238	545.23 214	1800.35 250	262.64 224	271.38 215

FPMVS		1407.00 233	1495.59 235	1141.23 246	648.01 235	893.85 249	4124.00 248	503.81 275	3219.04 256	742.72 243	2498.84 252	157.98 209	1727.83 259	832.93 217	732.98 257	802.00 251

Patchmtry		1090.75 225	1198.88 227	766.38 236	1290.90 257	485.90 214	2423.98 236	1267.30 308	1297.17 223	923.90 244	923.40 209	1215.54 301	990.23 241	667.90 209	779.80 258	823.02 256

PatchT		856.34 212	860.99 205	842.38 237	1290.90 257	880.90 248	790.30 185	1267.30 308	579.21 183	923.90 244	567.40 179	662.54 280	990.23 241	887.56 218	779.80 258	656.02 242

COLMAP_ROB	2144.59 11	1658.33 235	1869.33 237	1025.33 245	1030.00 254	1023.00 259	5311.00 254	359.00 251	3044.00 255	937.00 246	2892.00 254	332.00 245	1440.00 256	2312.00 256	607.00 240	613.00 241
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ambc				999.00 238	999.00 247	999.00 252	999.00 197	999.00 301		999.00 247	999.00 211	999.00 293	999.00 243	999.00 223	999.00 277	999.00 274

OurMVSNet-221017-0		999.00 218	999.00 217	999.00 238	999.00 247	999.00 252	999.00 197	999.00 301	999.00 212	999.00 247	999.00 211	999.00 293	999.00 243	999.00 223	999.00 277	999.00 274

EPMVS		999.00 218	999.00 217	999.00 238	999.00 247	999.00 252	999.00 197	999.00 301	999.00 212	999.00 247	999.00 211	999.00 293	999.00 243	999.00 223	999.00 277	999.00 274

uanet_test		1000.00 220	1000.00 219	1000.00 241	1000.00 250	1000.00 255	1000.00 200	1000.00 304	1000.00 214	1000.00 250	1000.00 214	1000.00 296	1000.00 246	1000.00 226	1000.00 280	1000.00 277

sosnet		1000.00 220	1000.00 219	1000.00 241	1000.00 250	1000.00 255	1000.00 200	1000.00 304	1000.00 214	1000.00 250	1000.00 214	1000.00 296	1000.00 246	1000.00 226	1000.00 280	1000.00 277

USDC		1000.00 220	1000.00 219	1000.00 241	1000.00 250	1000.00 255	1000.00 200	1000.00 304	1000.00 214	1000.00 250	1000.00 214	1000.00 296	1000.00 246	1000.00 226	1000.00 280	1000.00 277

TinyColmap		1000.00 220	1000.00 219	1000.00 241	1000.00 250	1000.00 255	1000.00 200	1000.00 304	1000.00 214	1000.00 250	1000.00 214	1000.00 296	1000.00 246	1000.00 226	1000.00 280	1000.00 277

JIA-IIPM		804.30 209	835.64 202	710.26 232	885.90 242	895.90 250	455.98 177	668.73 290	1297.17 223	1002.26 254	1001.67 218	655.98 278	756.98 233	667.90 209	885.21 270	477.90 236

RPMNet		787.26 208	829.13 201	661.63 227	885.90 242	895.90 250	455.98 177	610.10 285	1297.17 223	1002.26 254	1001.67 218	655.98 278	611.10 227	667.90 209	885.21 270	477.90 236

F-COLMAP		1878.17 236	2113.11 239	1173.33 249	1231.00 255	1174.00 260	6297.00 257	392.00 256	3356.00 258	1087.00 256	3082.00 255	361.00 249	1670.00 258	2523.00 258	689.00 247	676.00 246

PCF-MVS	4335.85 20	2272.23 242	2597.03 245	1297.84 250	1701.20 264	1332.37 261	8105.11 272	451.45 264	4031.84 263	1099.10 257	3966.50 262	467.45 257	1734.05 260	2701.68 261	848.94 267	827.11 257
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
CMPMVS	2623.62 15	1983.08 238	2156.14 240	1463.89 259	1414.80 261	1517.00 265	5239.20 253	867.40 295	3310.30 257	1128.70 258	3489.90 257	366.75 250	2030.20 270	2427.60 257	1160.60 289	844.46 259
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
OpenMVS	2352.88 13	2263.08 241	2530.89 244	1459.67 258	1767.00 272	1591.00 268	7932.00 270	399.00 257	3643.00 259	1176.00 259	3569.00 259	297.00 240	1927.00 266	3302.00 264	693.00 252	861.00 260

MVS-HIRNet		2125.39 239	2452.68 242	1143.53 247	2938.33 302	1446.92 264	6083.19 256	391.74 255	3801.71 261	1202.10 260	3439.72 256	492.73 259	1304.35 255	3048.25 263	676.32 246	679.32 247

ZD-MVS					1584.00 262	1821.00 285		378.00 254	3721.00 260	1231.00 261	1833.00 242	321.00 244	1224.00 254	2103.00 255	692.00 251

DeepPCF-MVS	3452.42 18	2670.71 250	3021.57 252	1618.12 261	2377.67 288	1751.39 281	8915.70 277	567.44 283	4569.74 270	1236.84 262	4615.63 268	513.23 260	2291.32 272	3515.48 268	882.39 269	811.66 253

PLC	2858.82 16	2192.92 240	2474.00 243	1349.67 251	1407.00 260	1356.00 262	7164.00 262	475.00 268	3970.00 262	1237.00 263	3765.00 261	451.00 256	1891.00 264	3006.00 262	791.00 263	802.00 251
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
Vis-MVSNet		2877.42 253	3170.00 256	1999.67 274	1673.00 263	2042.00 291	8593.00 275	474.00 267	6452.00 287	1268.00 264	5125.00 275	339.00 246	3004.00 288	4222.00 278	384.00 235	953.00 270
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
DeepC-MVS	3917.13 19	3155.06 256	3601.83 259	1814.72 269	2515.52 291	1941.53 286	10432.50 292	589.42 284	4789.45 271	1298.65 265	7677.31 293	578.35 267	2589.53 278	3611.78 270	923.52 272	913.10 265
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
test_0728_THIRD									5016.02 274	1363.85 266	4894.28 272	387.23 251	2023.43 267	3973.88 272	620.04 243	732.56 248

test0726					1725.60 265	1598.35 269	9203.30 278	315.86 245	5016.02 274	1363.85 266	4894.28 272	387.23 251

SD-MVS		2654.53 249	3055.56 254	1451.45 256	1725.60 265	1598.35 269	9203.30 278	315.86 245	5016.02 274	1363.85 266	4894.28 272	387.23 251	2023.43 267	3973.88 272	620.04 243	732.56 248
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	2531.17 246	2839.56 249	1606.00 260	1732.00 268	1557.00 267	8375.00 274	483.00 269	4370.00 268	1371.00 269	4200.00 263	350.00 247	2207.00 271	3877.00 271	798.00 264	1054.00 281

SteuartSystems-ACMMP		2891.50 254	3284.78 257	1711.67 264	1954.00 275	1655.00 275	10117.00 291	445.00 263	5102.00 277	1375.00 270	5126.00 276	351.00 248	2638.00 284	4402.00 279	691.00 250	842.00 258
Skip Steuart: Steuart Systems R&D Blog.
AdaColmap		2570.77 248	2948.61 251	1437.24 255	1873.64 274	1526.60 266	7819.77 269	373.97 252	4970.45 272	1479.29 271	4648.46 269	525.80 262	1904.97 265	4150.42 276	695.69 253	880.14 264

LF4IMVS		2699.50 251	3049.67 253	1649.00 262	1755.00 269	1689.00 276	8330.00 273	464.00 266	4997.00 273	1528.00 272	4763.00 271	568.00 266	2296.00 273	4215.00 277	827.00 266	962.00 271

tpmrst		2557.50 247	2847.12 250	1688.66 263	1784.08 273	1778.25 282	7445.50 268	342.14 248	4471.54 269	1534.55 273	4382.10 267	530.10 263	2361.21 274	4142.81 275	991.22 275	926.51 266

CHOSEN 280x420		2340.81 243	2643.03 246	1434.14 252	2025.55 281	1629.36 272	6542.40 258	412.49 258	4219.70 265	1547.02 274	4328.52 264	650.74 275	1798.26 261	3333.17 265	727.72 254	874.79 261

CHOSEN 1792x2688		2340.81 243	2643.03 246	1434.14 252	2025.55 281	1629.36 272	6542.40 258	412.49 258	4219.70 265	1547.02 274	4328.52 264	650.74 275	1798.26 261	3333.17 265	727.72 254	874.79 261

HyFIR lowres test		2340.81 243	2643.03 246	1434.14 252	2025.55 281	1629.36 272	6542.40 258	412.49 258	4219.70 265	1547.02 274	4328.52 264	650.74 275	1798.26 261	3333.17 265	727.72 254	874.79 261

DPM-MVS		3268.00 257	3762.89 260	1783.33 267	1756.00 270	1806.00 283	12319.00 294	307.00 243	6319.00 285	1557.00 277	5763.00 278	302.00 242	2609.00 280	5061.00 283	482.00 238	935.00 268

OPM-MVS		3268.00 257	3762.89 260	1783.33 267	1756.00 270	1806.00 283	12319.00 294	307.00 243	6319.00 285	1557.00 277	5763.00 278	302.00 242	2609.00 280	5061.00 283	482.00 238	935.00 268
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
EGC-MVSNET		2819.75 252	3096.89 255	1988.33 273	3105.00 303	2241.00 293	9480.00 282	640.00 289	4209.00 264	1583.00 279	4740.00 270	547.00 265	2797.00 286	2644.00 260	924.00 273	927.00 267

tpm2		3617.85 261	4007.23 263	2449.73 281	2012.71 277	1698.05 277	7351.19 264	869.29 296	6132.06 280	1588.28 280	8007.42 296	1281.09 302	3888.11 300	7472.04 301	1351.00 291	1763.02 297

tpm cat1		3617.85 261	4007.23 263	2449.73 281	2012.71 277	1698.05 277	7351.19 264	869.29 296	6132.06 280	1588.28 280	8007.42 296	1281.09 302	3888.11 300	7472.04 301	1351.00 291	1763.02 297

CostFormer		3617.85 261	4007.23 263	2449.73 281	2012.71 277	1698.05 277	7351.19 264	869.29 296	6132.06 280	1588.28 280	8007.42 296	1281.09 302	3888.11 300	7472.04 301	1351.00 291	1763.02 297

tpm		3617.85 261	4007.23 263	2449.73 281	2012.71 277	1698.05 277	7351.19 264	869.29 296	6132.06 280	1588.28 280	8007.42 296	1281.09 302	3888.11 300	7472.04 301	1351.00 291	1763.02 297

DVP-MVS++		3981.10 267	4731.32 272	1730.42 265	2191.51 284	1949.98 287	16473.90 303	355.33 249	7172.90 296	1622.98 284	7879.79 294	434.33 254	2428.11 276	5762.12 286	689.04 248	813.18 254

DVP-MVS		3981.10 267	4731.32 272	1730.42 265	2191.51 284	1949.98 287	16473.90 303	355.33 249	7172.90 296	1622.98 284	7879.79 294	434.33 254	2428.11 276	5762.12 286	689.04 248	813.18 254
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
OpenMVS_ROB	1936.51 10	1959.51 237	2224.88 241	1163.39 248	1253.91 256	1434.22 263	7065.71 261	272.76 241	2472.29 252	1647.54 286	3538.72 258	200.37 227	1496.48 257	2575.17 259	997.45 276	559.48 238

TAPA-MVS	6309.84 21	3374.90 259	3806.99 262	2078.63 276	2535.47 292	2499.25 301	8816.16 276	456.05 265	6255.60 284	1664.52 287	6704.88 283	629.95 273	2768.38 285	6343.93 297	856.35 268	968.25 272
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
TSAR-MVS + MP.		3528.01 260	4065.89 267	1914.35 270	2349.10 287	2141.30 292	12362.70 296	417.60 262	6717.80 291	1759.40 288	6497.50 281	518.18 261	2629.38 283	5164.32 285	806.40 265	972.38 273
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
3Dnovator+	3414.41 17	3146.67 255	3537.00 258	1975.67 271	2310.00 286	2005.00 290	10100.00 290	626.00 288	5753.00 278	1803.00 289	5179.00 277	487.00 258	2622.00 282	4550.00 280	1025.00 284	1300.00 288

ITE_SJBPF				2014.00 275	1998.00 276	1992.00 289		701.00 291	5989.00 279	1812.00 290	3612.00 260	650.00 274	2852.00 287	4601.00 281	1195.00 290	1198.00 287

MVS_111021_HR		3742.80 265	4330.34 268	1980.20 272	2484.31 290	2259.52 294	14973.80 301	515.90 282	6500.13 288	1949.21 291	6146.89 280	535.66 264	2593.66 279	4880.76 282	986.37 274	1087.43 282

FOURS1					2643.17 293	2465.14 296	13996.40 298	493.26 270	7619.38 299	2107.24 292

PC_three_1452									7619.38 299	2107.24 292	7416.93 290	610.24 270	3088.29 293	6075.14 293	1078.39 285	1159.26 283

test_one_0601					2643.17 293	2465.14 296		493.26 270	7619.38 299	2107.24 292	7416.93 290	610.24 270

SED-MVS		4062.74 270	4671.13 271	2237.56 277	2643.17 293	2465.14 296	13996.40 298	493.26 270	7619.38 299	2107.24 292	7416.93 290	610.24 270	3088.29 293	6075.14 293	1078.39 285	1159.26 283

IU-MVS					2725.60 298	2598.35 302		515.86 278	7016.02 292	2363.85 296				5973.88 289	1620.04 297	1732.56 293

test_241102_TWO								515.86 278	7016.02 292	2363.85 296	6894.28 284	887.23 288	3023.43 289	5973.88 289	1620.04 297	1732.56 293

test_241102_ONE					2725.60 298	2598.35 302		515.86 278	7016.02 292	2363.85 296	6894.28 284	887.23 288	3023.43 289

MSP-MVS		4296.20 271	4911.12 275	2451.45 285	2725.60 298	2598.35 302	16203.30 302	515.86 278	7016.02 292	2363.85 296	6894.28 284	887.23 288	3023.43 289	5973.88 289	1620.04 297	1732.56 293
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
GST-MVS		4000.00 269	4533.33 270	2400.00 280	2400.00 289	2400.00 295	7200.00 263	2400.00 312	7200.00 298	2400.00 300	7200.00 288	2400.00 306	2400.00 275	7200.00 299	2400.00 303	2400.00 302

MAR-MVS		3973.16 266	4387.92 269	2728.86 287	3345.27 304	3341.39 308	11403.90 293	798.76 293	6555.62 290	2569.29 301	6514.86 282	834.97 287	3237.43 297	5891.08 288	1577.54 296	1607.76 289
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		4380.83 272	4906.56 274	2803.67 288	3844.00 305	3116.00 307	13454.00 297	901.00 300	6511.00 289	2794.00 302	7365.00 289	754.00 284	3634.00 298	6622.00 298	1914.00 302	1661.00 292

OMC-MVS		5022.26 273	5748.82 276	2842.58 289	4905.27 307	3101.27 306	14933.60 300	812.24 294	9278.40 303	2959.29 303	8800.17 300	1092.24 300	3806.30 299	7568.54 305	1389.60 295	1620.18 291

LS3D		7684.71 275	8776.23 278	4410.16 291	5298.55 308	5631.53 310	34329.90 308	1504.57 310	11554.00 312	3896.41 304	15111.00 309	812.19 285	5985.63 305	3516.20 269	2963.23 304	1613.31 290

CLD-MVS		7338.25 274	8341.00 277	4330.00 290	4902.00 306	4991.00 309	23318.00 306	728.00 292	14437.00 313	4378.00 305	13379.00 308	824.00 286	5708.00 304	11429.00 314	1674.00 301	2291.00 301
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
MVE	10021.00 22	10550.67 283	10002.44 286	12195.33 300	6242.00 309	8768.00 312	30896.00 307	4451.00 313	10331.00 311	6247.00 306	18296.00 310	283.00 239	21484.00 314	7364.00 300	5912.00 306	6334.00 304
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CNLPA		10738.67 284	11772.44 287	7637.33 292	9120.00 310	8206.00 311	22252.00 305	2010.00 311	24984.00 314	7458.00 307	22596.00 311	2940.00 307	10260.00 313	11100.00 313	3492.00 305	4446.00 303

ZNCC-MVS		9999.00 276	9999.00 279	9999.00 293	9999.00 311	9999.00 313	9999.00 283	9999.00 316	9999.00 304	9999.00 308	9999.00 301	9999.00 309	9999.00 306	9999.00 306	9999.00 307	9999.00 305

patch_mono-2		10000.00 277	10000.00 280	10000.00 294	10000.00 312	10000.00 314	10000.00 284	10000.00 317	10000.00 305	10000.00 309	10000.00 302	10000.00 310	10000.00 307	10000.00 307	10000.00 308	10000.00 306

dcpmvs_2		10000.00 277	10000.00 280	10000.00 294	10000.00 312	10000.00 314	10000.00 284	10000.00 317	10000.00 305	10000.00 309	10000.00 302	10000.00 310	10000.00 307	10000.00 307	10000.00 308	10000.00 306

DCPMVS		10000.00 277	10000.00 280	10000.00 294	10000.00 312	10000.00 314	10000.00 284	10000.00 317	10000.00 305	10000.00 309	10000.00 302	10000.00 310	10000.00 307	10000.00 307	10000.00 308	10000.00 306

UA-Net		10000.00 277	10000.00 280	10000.00 294	10000.00 312	10000.00 314	10000.00 284	10000.00 317	10000.00 305	10000.00 309	10000.00 302	10000.00 310	10000.00 307	10000.00 307	10000.00 308	10000.00 306

uncertanet		10000.00 277	10000.00 280	10000.00 294	10000.00 312	10000.00 314	10000.00 284	10000.00 317	10000.00 305	10000.00 309	10000.00 302	10000.00 310	10000.00 307	10000.00 307	10000.00 308	10000.00 306

uanet		10000.00 277	10000.00 280	10000.00 294	10000.00 312	10000.00 314	10000.00 284	10000.00 317	10000.00 305	10000.00 309	10000.00 302	10000.00 310	10000.00 307	10000.00 307	10000.00 308	10000.00 306

LTVRE_ROB	20565.47 23	23378.08 285	22805.00 288	25097.33 301	15500.00 318	19201.00 320	42712.00 309	6055.00 314	38388.00 315	16926.00 315	38534.00 312	7071.00 308	35653.00 315	29475.00 315	10584.00 314	20438.00 313
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		32606.17 286	34443.44 289	27094.33 302	29249.00 319	25246.00 321	51144.00 310	6705.00 315	42886.00 316	22888.00 316	48534.00 313	13263.00 316	37507.00 316	79298.00 316	16024.00 315	18530.00 312

114514_t		99999.00 287	99999.00 290	99999.00 303	99999.00 320	99999.00 322	99999.00 311	99999.00 323	99999.00 317	99999.00 317	99999.00 314	99999.00 317	99999.00 317	99999.00 317	99999.00 316	99999.00 314

PHI-MVS		99999.00 287	99999.00 290	99999.00 303	99999.00 320	99999.00 322	99999.00 311	99999.00 323	99999.00 317	99999.00 317	99999.00 314	99999.00 317	99999.00 317	99999.00 317	99999.00 316	99999.00 314

XVG-OURS-SEG-HR		999999.00 291	999999.00 292	999999.00 305	999999.00 322	999999.00 324	999999.00 313	999999.00 325	999999.00 319	999999.00 319	999999.00 316	999999.00 319	999999.00 319	999999.00 319	999999.00 318	999999.00 316

XVG-OURS		999999.00 291	999999.00 292	999999.00 305	999999.00 322	999999.00 324	999999.00 313	999999.00 325	999999.00 319	999999.00 319	999999.00 316	999999.00 319	999999.00 319	999999.00 319	999999.00 318	999999.00 316

XVG-ACMP-BASELINE		999999.00 291	999999.00 292	999999.00 305	999999.00 322	999999.00 324	999999.00 313	999999.00 325	999999.00 319	999999.00 319	999999.00 316	999999.00 319	999999.00 319	999999.00 319	999999.00 318	999999.00 316

MVSMamba_PlusPlus		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

MGCFI-Net		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

sasdasda		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

dmvs_re		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

SDMVSNet		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

dmvs_testset		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

sd_testset		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

balanced_conf03		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

MonoMVSNet		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

test2506		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

test1111		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

ECVR-MVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

test_blank		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

tt0805		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

Anonymous20240521		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

cl22		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

miper_ehance_all_eth		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

miper_enhance_ethall		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

cl____		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

DIV-MVS_self_test		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

eth_miper_zixun_eth		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

ET-MVSNet_ETH3D		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

UniMVSNet_ETH3D		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

miper_lstm_enhance		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

D2MVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

test_yl		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

thisisatest0530		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

Anonymous20240529		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

Anonymous202405211		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

DCV-MVSNet		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

tttt0517		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

our_test_3		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

thisisatest0515		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

ppachtmachnet_test		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

SMA-MVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319
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		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part2					10000000.00 325	10000000.00 327				10000000.00 322

thres100view900		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

tfpnnormal		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

tfpn200view9		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

c3_l		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

IterMVS-SCA-FT		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

pmmvs6		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

pmmvs5		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

Anonymous20231211		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

pmmvs-eth3d		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

Anonymous20231206		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

SCA		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

Patchmatch-test		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

Patchmatch-RL test		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

canonicalmvs		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

anonymousdsp		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

FIs		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

FC-MVSNet-test		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

sosnet-low-res		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

AllTest		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

TestCases				10000000.00 308	10000000.00 325	10000000.00 327		10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

RRT-MVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

mamv4		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

HPM-MVS++		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

XVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

pm-mvs1		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

X-MVStestdata		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

APDe-MVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
APD-MVS_3200maxsize		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

pmmvs4		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

test-LLR		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

TESTMET0.1,1		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

test-mter		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

testgi		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

test20.03		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

thres600view7		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

MP-MVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

thres400		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

test123		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

thres200		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

test0.0.03 1		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

pmmvs3		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

EMVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

E-PMN		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

PGM-MVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

MCST-MVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

MVS_Test		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

PMMVS2		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

PM-MVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

HQP_MVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

plane_prior3						10000000.00 327			10000000.00 322	10000000.00 322

mPP-MVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

mvsmamba		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

HPM-MVS_fast		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

HPM-MVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
LPG-MVS_test		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

LGP-MVS_train				10000000.00 308	10000000.00 325	10000000.00 327		10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

EPNet_dtu		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP-NCC					10000000.00 325		10000000.00 316		10000000.00 322	10000000.00 322

ACMP_Plane					10000000.00 325		10000000.00 316		10000000.00 322	10000000.00 322

HQP4-MVS										10000000.00 322			10000000.00 322			10000000.00 319

CNVR-MVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

NCCC		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

CP-MVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

CPTT-MVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

HQP-MVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

IS-MVSNet		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

PAPM_NR		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

PAPR		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

Vis-MVSNet (Re-imp)		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

PatchMatch-RL		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

TDRefinement		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

EPP-MVSNet		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

PMMVS		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

PAPM		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

ACMMP		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319
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		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

wuyk23d		10000000.00 294	10000000.00 297	10000000.00 308	10000000.00 325	10000000.00 327	10000000.00 316	10000000.00 328	10000000.00 322	10000000.00 322	10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

APD-MVS		1000000000.00 403	1000000000.00 406	1000000000.00 419	1000000000.00 444	1000000000.00 444	1000000000.00 430	1000000000.00 444	1000000000.00 437	1000000000.00 438	1000000000.00 435	1000000000.00 440	1000000000.00 438	1000000000.00 437	1000000000.00 436	1000000000.00 434
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
WAC-MVS						248.46 189								422.23 182

MSC_two_6792asdad				2237.56 277	2643.17 293	2465.14 296		493.26 270					3088.29 293	6075.14 293	1078.39 285	1159.26 283

No_MVS				2237.56 277	2643.17 293	2465.14 296		493.26 270					3088.29 293	6075.14 293	1078.39 285	1159.26 283

eth-test2					1.42 84

eth-test					10000000.00 325

OPU-MVS				2451.45 285	2725.60 298	2598.35 302	9203.30 278				6894.28 284	887.23 288	3023.43 289	5973.88 289	1620.04 297	1732.56 293

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

test_0728_SECOND				1451.45 256	1725.60 265	1598.35 269	9203.30 278	315.86 245					2023.43 267	3973.88 272	620.04 243	732.56 248

GSMVS																10000000.00 319

sam_mvs1												10000000.00 322				10000000.00 319

sam_mvs												10000000.00 322

MTGPA								10000000.00 328

test_post1							10000000.00 316				10000000.00 319	10000000.00 322	10000000.00 322	10000000.00 322

test_post											10000000.00 319	10000000.00 322	10000000.00 322

patchmatchnet-post											10000000.00 319	10000000.00 322	10000000.00 322

MTMP							10000000.00 316	10000000.00 328

gm-plane-assit					611.29 222	600.33 230			579.21 183		567.40 179		531.67 210	503.93 189

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_prior				0.00 1	0.00 1	0.00 1		0.00 1					0.00 1			0.00 1

新几何2							0.00 1

旧先验1					0.00 1	0.00 1		0.00 1			0.00 1	0.00 1			0.00 1	0.00 1

无先验							0.00 1	0.00 1	0.00 1				0.00 1	0.00 1		0.00 1

原ACMM2							0.00 1

testdata2													0.00 1	0.00 1

segment_acmp												0.00 1

testdata1							0.00 1		0.00 1

plane_prior7					10000000.00 325	10000000.00 327

plane_prior6					10000000.00 325	10000000.00 327						10000000.00 322

plane_prior5								10000000.00 328					10000000.00 322	10000000.00 322	10000000.00 321	10000000.00 319

plane_prior4											10000000.00 319

plane_prior2							10000000.00 316		10000000.00 322

plane_prior1					10000000.00 325

plane_prior						1.00 78	2.00 116		2.00 117						2.00 115

n2								14.20 158

nn								1.42 86

door-mid								1.42 86

test11								1.00 79

door								99.00 207

HQP5-MVS						10000000.00 327

BP-MVS														10000000.00 322

HQP3-MVS								10000000.00 328							10000000.00 321

HQP2-MVS												10000000.00 322

NP-MVS					10000000.00 325	10000000.00 327					10000000.00 319

ACMMP++_ref															10000000.00 321

ACMMP++															10000000.00 321

Test By Simon												990.00 292

High-resolution multi-view benchmark