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	courty.	delive.	electro	facade	kicker	meadow	office	pipes	playgr.	relief	relief.	terrace	terrai.

diffmvs_AUTHOR		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

viewmambaseed2359dif		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

viewmanbaseed2359cas		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	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	0.00 1

EIA-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	0.00 1

ETV-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	0.00 1

CS-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	0.00 1

SMA-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	0.00 1
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
Fast-Effi-MVS+-dtu		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

Effi-MVS+-dtu		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	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	0.00 1

SPE-MVS-test		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	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	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	0.00 1

EC-MVSNet		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	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	0.00 1

v144192		0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 18	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17

v1921920		0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 18	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17

v1192		0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 18	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17

v1144		0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 18	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17

v148		0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 18	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17

v7n		0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 18	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17

v1240		0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 18	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17

v8		0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 18	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17

v10		0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 18	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17

v2v482		0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 18	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17

V42		0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 18	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17

GA-MVS		0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17	0.40 18	0.40 17	0.40 17	0.40 17	0.40 17	0.40 17

Fast-Effi-MVS+		0.41 29	0.41 29	0.41 29	0.41 29	0.41 29	0.41 29	0.41 29	0.41 29	0.41 29	0.41 29	0.41 30	0.41 29	0.41 29	0.41 29	0.41 29	0.41 29

Effi-MVS+		0.53 30	0.53 30	0.53 30	0.53 30	0.53 30	0.53 30	0.53 30	0.53 30	0.53 30	0.53 30	0.53 31	0.53 30	0.53 30	0.53 30	0.53 30	0.53 30

CDS-MVSNet		0.88 31	0.88 31	0.88 31	0.88 31	0.88 31	0.88 31	0.88 31	0.88 31	0.88 31	0.88 31	0.88 32	0.88 31	0.88 31	0.88 31	0.88 31	0.88 31
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		0.88 31	0.88 31	0.88 31	0.88 31	0.88 31	0.88 31	0.88 31	0.88 31	0.88 31	0.88 31	0.88 32	0.88 31	0.88 31	0.88 31	0.88 31	0.88 31

MDA-MVSNet-bldmvs		1.20 33	1.20 33	1.20 33	1.20 33	1.20 34	1.20 34	1.20 34	1.20 34	1.20 34	1.20 34	1.20 35	1.20 34	1.20 34	1.20 33	1.20 34	1.20 34

CVMVSNet		1.42 34	1.42 34	1.42 34	1.42 34	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 36	1.42 35	1.42 35	1.42 34	1.42 35	1.42 35

EU-MVSNet		1.42 34	1.42 34	1.42 34	1.42 34	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 36	1.42 35	1.42 35	1.42 34	1.42 35	1.42 35

PS-CasMVS		1.42 34	1.42 34	1.42 34	1.42 34	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 36	1.42 35	1.42 35	1.42 34	1.42 35	1.42 35

UniMVSNet_NR-MVSNet		1.42 34	1.42 34	1.42 34	1.42 34	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 36	1.42 35	1.42 35	1.42 34	1.42 35	1.42 35

PEN-MVS		1.42 34	1.42 34	1.42 34	1.42 34	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 36	1.42 35	1.42 35	1.42 34	1.42 35	1.42 35

TransMVSNet (Re)		1.42 34	1.42 34	1.42 34	1.42 34	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 36	1.42 35	1.42 35	1.42 34	1.42 35	1.42 35

DTE-MVSNet		1.42 34	1.42 34	1.42 34	1.42 34	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 36	1.42 35	1.42 35	1.42 34	1.42 35	1.42 35

DU-MVS		1.42 34	1.42 34	1.42 34	1.42 34	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 36	1.42 35	1.42 35	1.42 34	1.42 35	1.42 35

UniMVSNet (Re)		1.42 34	1.42 34	1.42 34	1.42 34	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 36	1.42 35	1.42 35	1.42 34	1.42 35	1.42 35

CP-MVSNet		1.42 34	1.42 34	1.42 34	1.42 34	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 36	1.42 35	1.42 35	1.42 34	1.42 35	1.42 35

WR-MVS_H		1.42 34	1.42 34	1.42 34	1.42 34	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 36	1.42 35	1.42 35	1.42 34	1.42 35	1.42 35

WR-MVS		1.42 34	1.42 34	1.42 34	1.42 34	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 36	1.42 35	1.42 35	1.42 34	1.42 35	1.42 35

NR-MVSNet		1.42 34	1.42 34	1.42 34	1.42 34	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 36	1.42 35	1.42 35	1.42 34	1.42 35	1.42 35

Baseline_NR-MVSNet		1.42 34	1.42 34	1.42 34	1.42 34	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 36	1.42 35	1.42 35	1.42 34	1.42 35	1.42 35

TranMVSNet+NR-MVSNet		1.42 34	1.42 34	1.42 34	1.42 34	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 35	1.42 36	1.42 35	1.42 35	1.42 34	1.42 35	1.42 35

CDPH-MVS		6.66 49	6.66 49	6.66 49	6.66 49	6.66 50	6.66 50	6.66 50	6.66 50	6.66 50	6.66 50	6.66 51	6.66 50	6.66 50	6.66 49	6.66 50	6.66 50

MDTV_nov1_ep13_2view		9.99 50	9.99 50	9.99 50	9.99 50	9.99 51	9.99 51	9.99 51	9.99 51	9.99 53	9.99 51	9.99 54	9.99 51	9.99 51	9.99 50	9.99 51	9.99 51

MDTV_nov1_ep13		9.99 50	9.99 50	9.99 50	9.99 50	9.99 51	9.99 51	9.99 51	9.99 51	9.99 53	9.99 51	9.99 54	9.99 51	9.99 51	9.99 50	9.99 51	9.99 51

test_method		18.19 52	15.64 52	21.17 52	19.00 52	22.00 53	22.50 53	38.00 54	15.50 53	7.50 51	13.00 53	7.00 52	19.00 54	15.50 54	15.50 52	21.00 53	21.00 53

GeoE		20.05 53	18.83 53	21.47 53	25.60 53	29.60 54	22.50 53	31.20 53	19.10 54	8.30 52	13.50 54	9.40 53	17.80 53	14.10 53	17.50 53	23.40 54	28.60 54

GBi-Net		39.84 54	35.75 54	44.63 54	43.04 54	49.88 55	51.06 55	86.51 56	35.34 55	17.20 55	29.83 55	15.85 56	43.43 57	35.35 55	35.70 54	26.51 57	48.28 57

X-MVS		52.20 55	52.20 55	52.20 55	52.20 55	52.20 56	52.20 56	52.20 55	52.20 56	52.20 63	52.20 56	52.20 73	52.20 58	52.20 56	52.20 55	52.20 58	52.20 58

new_pmnet		75.00 56	74.67 56	75.39 56	85.42 58	96.03 60	98.77 59	173.23 57	69.57 57	36.19 56	56.93 57	117.43 79	32.98 55	85.38 64	68.41 56	25.74 55	28.95 55

N_pmnet		75.00 56	74.67 56	75.39 56	85.42 58	96.03 60	98.77 59	173.23 57	69.57 57	36.19 56	56.93 57	117.43 79	32.98 55	85.38 64	68.41 56	25.74 55	28.95 55

CANet		100.44 58	93.07 58	109.04 58	111.90 60	131.06 64	119.40 62	222.42 66	80.48 59	36.93 58	70.80 59	40.92 60	89.90 59	100.59 66	101.42 59	73.68 62	126.25 59

CANet_DTU		100.44 58	93.07 58	109.04 58	111.90 60	131.06 64	119.40 62	222.42 66	80.48 59	36.93 58	70.80 59	40.92 60	89.90 59	100.59 66	101.42 59	73.68 62	126.25 59

UGNet		100.44 58	93.07 58	109.04 58	111.90 60	131.06 64	119.40 62	222.42 66	80.48 59	36.93 58	70.80 59	40.92 60	89.90 59	100.59 66	101.42 59	73.68 62	126.25 59
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
ACMMP_NAP		119.64 68	106.58 61	134.88 68	123.82 63	127.44 63	145.38 65	298.43 73	116.16 72	43.72 62	77.82 62	29.30 58	131.24 69	117.82 72	106.21 62	66.69 61	171.29 72

FMVSNet5		116.86 61	110.47 62	124.32 61	131.47 64	157.41 67	150.67 66	199.64 59	115.30 65	56.61 69	97.70 66	51.77 63	117.26 62	77.26 57	113.14 63	90.25 68	160.68 65

test1		116.86 61	110.47 62	124.32 61	131.47 64	157.41 67	150.67 66	199.64 59	115.30 65	56.61 69	97.70 66	51.77 63	117.26 62	77.26 57	113.14 63	90.25 68	160.68 65

FMVSNet3		116.86 61	110.47 62	124.32 61	131.47 64	157.41 67	150.67 66	199.64 59	115.30 65	56.61 69	97.70 66	51.77 63	117.26 62	77.26 57	113.14 63	90.25 68	160.68 65

FMVSNet2		116.86 61	110.47 62	124.32 61	131.47 64	157.41 67	150.67 66	199.64 59	115.30 65	56.61 69	97.70 66	51.77 63	117.26 62	77.26 57	113.14 63	90.25 68	160.68 65

FMVSNet1		116.86 61	110.47 62	124.32 61	131.47 64	157.41 67	150.67 66	199.64 59	115.30 65	56.61 69	97.70 66	51.77 63	117.26 62	77.26 57	113.14 63	90.25 68	160.68 65

MIMVSNet1		116.86 61	110.47 62	124.32 61	131.47 64	157.41 67	150.67 66	199.64 59	115.30 65	56.61 69	97.70 66	51.77 63	117.26 62	77.26 57	113.14 63	90.25 68	160.68 65

MIMVSNet		116.86 61	110.47 62	124.32 61	131.47 64	157.41 67	150.67 66	199.64 59	115.30 65	56.61 69	97.70 66	51.77 63	117.26 62	77.26 57	113.14 63	90.25 68	160.68 65

PVSNet_Blended_VisFu		129.22 69	115.76 69	144.92 69	140.60 71	162.80 74	166.50 73	281.20 70	114.70 62	55.50 66	96.20 63	51.80 70	140.60 70	114.70 69	114.70 70	85.10 65	155.40 62

PVSNet_BlendedMVS		129.22 69	115.76 69	144.92 69	140.60 71	162.80 74	166.50 73	281.20 70	114.70 62	55.50 66	96.20 63	51.80 70	140.60 70	114.70 69	114.70 70	85.10 65	155.40 62

PVSNet_Blended		129.22 69	115.76 69	144.92 69	140.60 71	162.80 74	166.50 73	281.20 70	114.70 62	55.50 66	96.20 63	51.80 70	140.60 70	114.70 69	114.70 70	85.10 65	155.40 62

FA-MVS(training)		203.85 72	180.15 72	231.50 72	222.82 74	259.22 77	245.99 76	478.61 75	172.32 75	82.03 77	130.35 73	72.14 76	221.74 74	190.35 73	197.39 73	137.78 76	239.26 73

SixPastTwentyTwo		210.90 73	189.75 73	235.58 73	225.41 75	284.88 78	267.17 77	485.88 76	164.28 74	76.51 76	137.62 74	76.69 77	214.49 73	206.28 74	208.00 74	144.02 77	250.52 74

WB-MVS		316.93 74	277.98 74	362.37 75	386.49 77	371.32 83	360.90 82	844.52 84	232.58 76	102.36 78	215.57 76	104.13 78	287.33 76	336.96 76	318.49 75	192.62 78	366.78 76

RPSCF		376.53 75	341.80 75	417.05 76	418.60 79	457.01 84	467.46 83	825.25 83	336.12 78	159.32 82	260.40 78	151.13 83	386.94 77	364.25 77	352.10 76	244.72 79	471.62 77

EG-PatchMatch MVS		402.98 76	364.36 76	448.05 77	435.50 80	473.00 85	489.60 84	910.20 85	338.60 79	127.30 79	205.10 75	123.50 81	434.60 78	450.70 81	447.70 79	291.10 81	511.90 78

MS-PatchMatch		438.85 77	388.71 77	497.33 78	479.00 81	527.00 86	558.00 87	988.00 86	379.00 81	174.00 84	278.00 80	162.00 84	494.00 82	418.00 78	412.00 77	291.00 80	545.00 81

ADS-MVSNet		452.36 78	406.02 78	506.42 81	534.76 87	628.22 89	552.79 86	1009.99 93	333.98 77	149.26 80	246.67 77	149.01 82	447.03 80	465.35 82	501.18 82	344.69 84	517.75 79

PatchmatchNet		452.63 79	410.20 79	502.13 80	520.70 86	614.40 87	546.00 85	1018.80 94	379.00 81	167.50 83	277.10 79	169.40 85	437.10 79	437.10 79	457.50 80	322.70 83	536.90 80
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
DELS-MVS		458.84 80	423.31 80	500.30 79	511.99 85	616.59 88	578.86 88	991.10 87	355.79 80	158.99 81	319.09 82	190.62 87	453.64 81	437.73 80	439.52 78	307.20 82	603.81 82
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
dps		534.60 81	472.40 81	607.16 83	690.38 95	718.85 92	636.03 89	1231.66 96	422.74 83	198.65 87	325.68 83	194.97 88	512.90 84	509.81 84	513.65 83	373.33 86	621.11 83

IterMVS		554.60 84	488.63 82	631.57 88	636.90 92	700.80 90	674.70 91	1271.10 98	430.50 84	207.10 89	370.50 85	202.70 90	611.80 88	534.20 87	545.30 86	387.80 87	636.40 84
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
GG-mvs-BLEND		557.53 85	503.49 83	620.58 85	485.90 82	370.41 79	267.30 78	710.53 79	454.42 86	785.72 126	491.23 99	326.12 108	881.92 103	538.27 88	650.05 97	592.08 105	693.94 85

gm-plane-assit		551.84 82	503.49 83	608.24 84	411.90 78	370.41 79	267.30 78	710.53 79	454.42 86	785.72 126	491.23 99	326.12 108	881.92 103	538.27 88	650.05 97	592.08 105	693.94 85

gg-mvs-nofinetune		557.53 85	503.49 83	620.58 85	485.90 82	370.41 79	267.30 78	710.53 79	454.42 86	785.72 126	491.23 99	326.12 108	881.92 103	538.27 88	650.05 97	592.08 105	693.94 85

CR-MVSNet		557.53 85	503.49 83	620.58 85	485.90 82	370.41 79	267.30 78	710.53 79	454.42 86	785.72 126	491.23 99	326.12 108	881.92 103	538.27 88	650.05 97	592.08 105	693.94 85

IB-MVS	750.90 3	552.99 83	511.38 87	601.53 82	606.02 90	735.75 94	688.75 92	1183.86 95	436.09 85	210.63 90	397.40 86	233.85 92	551.05 85	521.77 85	533.78 85	368.88 85	721.05 90
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
Gipuma		587.77 88	529.57 88	655.67 89	637.00 93	733.00 93	749.00 94	1245.00 97	525.00 93	269.00 100	445.00 95	253.00 94	637.00 90	525.00 86	525.00 84	397.00 88	701.00 89
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
pmnet_mix02		659.48 96	547.83 89	789.74 99	720.05 96	846.87 103	740.59 93	2153.63 112	456.15 90	191.24 85	336.49 84	200.39 89	511.90 83	608.74 92	634.29 95	421.05 90	751.91 91

MVS_Test		654.54 89	583.51 90	737.40 91	721.80 97	822.10 96	808.60 96	1494.00 100	542.20 95	259.90 93	441.60 88	257.70 96	689.10 92	620.80 93	617.70 88	451.00 93	782.50 92

casdiffmvs		654.54 89	583.51 90	737.40 91	721.80 97	822.10 96	808.60 96	1494.00 100	542.20 95	259.90 93	441.60 88	257.70 96	689.10 92	620.80 93	617.70 88	451.00 93	782.50 92
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		654.54 89	583.51 90	737.40 91	721.80 97	822.10 96	808.60 96	1494.00 100	542.20 95	259.90 93	441.60 88	257.70 96	689.10 92	620.80 93	617.70 88	451.00 93	782.50 92
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		654.54 89	583.51 90	737.40 91	721.80 97	822.10 96	808.60 96	1494.00 100	542.20 95	259.90 93	441.60 88	257.70 96	689.10 92	620.80 93	617.70 88	451.00 93	782.50 92

baseline1		654.54 89	583.51 90	737.40 91	721.80 97	822.10 96	808.60 96	1494.00 100	542.20 95	259.90 93	441.60 88	257.70 96	689.10 92	620.80 93	617.70 88	451.00 93	782.50 92

casdiffmvs_mvg		654.54 89	583.51 90	737.40 91	721.80 97	822.10 96	808.60 96	1494.00 100	542.20 95	259.90 93	441.60 88	257.70 96	689.10 92	620.80 93	617.70 88	451.00 93	782.50 92
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		654.54 89	583.51 90	737.40 91	721.80 97	822.10 96	808.60 96	1494.00 100	542.20 95	259.90 93	441.60 88	257.70 96	689.10 92	620.80 93	617.70 88	451.00 93	782.50 92

ACMH+	702.88 1	670.82 97	589.81 97	765.33 98	662.52 94	701.42 91	795.24 95	1698.33 108	598.81 103	226.55 91	403.02 87	187.13 86	786.82 100	724.80 103	646.56 96	422.52 91	866.95 100

new-patchmatchnet		712.65 98	632.59 98	806.05 102	787.79 104	936.25 107	882.47 104	1795.72 109	528.60 94	244.29 92	471.90 96	257.36 95	681.47 91	705.16 102	659.05 101	444.55 92	869.82 101

PMVS	743.55 2	836.66 102	637.90 99	1068.55 111	1306.50 119	875.12 104	1166.70 117	2629.00 115	512.24 92	196.22 86	282.69 81	237.15 93	597.87 87	842.47 105	765.54 104	514.99 101	950.09 102
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
IterMVS-LS		714.97 99	638.00 100	804.77 101	793.60 105	914.20 105	886.50 106	1612.70 107	588.30 102	285.30 101	491.20 98	278.40 104	759.20 99	677.40 101	681.30 102	491.30 100	835.20 99
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CSCG		727.26 100	663.25 101	801.94 100	590.65 89	811.25 95	854.12 103	1805.32 110	816.43 108	388.25 106	612.42 107	345.37 114	621.61 89	507.46 83	471.55 81	551.65 103	1078.31 112

MSLP-MVS++		993.91 106	732.21 102	1299.24 115	1631.22 122	1345.26 120	1480.05 121	2524.20 114	735.65 105	463.57 116	499.89 103	302.78 105	1292.66 117	675.99 100	612.79 87	403.71 89	953.11 104

MVSTER		834.63 101	737.03 103	948.49 103	988.86 107	1140.51 118	1129.34 116	1832.80 111	682.42 104	319.01 102	550.98 105	311.35 107	872.51 102	763.95 104	757.83 103	548.41 102	952.20 103

PatchT		878.42 104	785.05 104	987.36 104	1050.05 115	922.05 106	1111.05 114	677.05 78	950.05 111	1285.90 154	750.05 113	640.05 125	850.05 101	950.05 106	950.05 106	950.05 116	333.05 75

ACMH	935.68 4	948.23 105	857.00 105	1054.67 110	946.00 106	970.00 108	1125.00 115	2467.00 113	823.00 109	330.00 104	622.00 108	211.00 91	891.00 107	970.00 108	1061.00 115	569.00 104	1342.00 114
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMM	1129.18 5	1047.56 112	912.90 106	1204.67 112	1040.21 114	1016.71 115	1105.32 113	2918.67 118	813.91 107	327.22 103	665.34 109	267.72 103	1192.58 116	1091.35 116	991.88 108	643.99 110	1543.40 121
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MVS_111021_LR		1055.24 113	916.36 107	1217.27 113	1129.93 117	1268.26 119	1313.88 120	2635.76 116	923.19 110	396.92 110	704.88 111	327.66 112	1136.32 115	965.38 107	946.95 105	690.83 113	1278.20 113

ACMP	1170.86 6	1091.37 114	943.23 108	1264.21 114	1112.10 116	1138.94 117	1276.90 119	2675.36 117	989.62 112	426.15 114	742.77 112	349.09 116	1454.51 121	1047.36 115	969.90 107	640.22 109	1364.94 116
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
RPMNet		858.01 103	961.99 109	736.69 90	550.05 88	1120.24 116	1212.05 118	463.05 74	485.90 91	550.05 118	580.05 106	890.05 139	559.05 86	1485.90 120	1185.90 118	1085.90 123	985.90 105

ambc			999.00 110		999.00 108	999.00 109	999.00 107		999.00 113	999.00 136	999.00 120	999.00 145	999.00 109	999.00 109	999.00 109	999.00 117	999.00 106

EPMVS		999.00 107	999.00 110	999.00 105	999.00 108	999.00 109	999.00 107	999.00 88	999.00 113	999.00 136	999.00 120	999.00 145	999.00 109	999.00 109	999.00 109	999.00 117	999.00 106

uanet_test		1000.00 108	1000.00 112	1000.00 106	1000.00 110	1000.00 111	1000.00 109	1000.00 89	1000.00 115	1000.00 138	1000.00 122	1000.00 147	1000.00 111	1000.00 111	1000.00 111	1000.00 119	1000.00 108

sosnet		1000.00 108	1000.00 112	1000.00 106	1000.00 110	1000.00 111	1000.00 109	1000.00 89	1000.00 115	1000.00 138	1000.00 122	1000.00 147	1000.00 111	1000.00 111	1000.00 111	1000.00 119	1000.00 108

USDC		1000.00 108	1000.00 112	1000.00 106	1000.00 110	1000.00 111	1000.00 109	1000.00 89	1000.00 115	1000.00 138	1000.00 122	1000.00 147	1000.00 111	1000.00 111	1000.00 111	1000.00 119	1000.00 108

TinyColmap		1000.00 108	1000.00 112	1000.00 106	1000.00 110	1000.00 111	1000.00 109	1000.00 89	1000.00 115	1000.00 138	1000.00 122	1000.00 147	1000.00 111	1000.00 111	1000.00 111	1000.00 119	1000.00 108

FPMVS		1356.65 118	1072.60 116	1688.04 119	1840.79 123	1397.01 121	1793.24 125	4397.86 126	804.66 106	408.78 111	538.65 104	407.36 117	894.84 108	1587.73 121	1286.38 120	792.73 115	1486.39 118

ACMMPR		1265.65 116	1083.59 117	1478.06 118	1441.06 121	1438.61 123	1540.68 123	3284.05 121	1219.68 121	458.81 115	803.22 115	346.91 115	1421.66 120	1126.11 118	1150.51 117	722.08 114	1500.09 119

TSAR-MVS + GP.		1239.27 115	1094.74 118	1407.89 116	1220.99 118	1845.47 125	1680.98 124	3191.81 119	1098.41 119	362.98 105	679.12 110	339.31 113	1323.06 118	1173.24 119	1093.83 116	667.49 111	1433.78 117

DeepC-MVS_fast	2081.98 8	1311.87 117	1172.50 119	1474.47 117	1411.78 120	1397.23 122	1519.03 122	3401.40 122	1201.29 120	417.90 112	801.95 114	976.25 144	1409.37 119	1114.52 117	1201.12 119	687.33 112	1515.14 120
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
OpenMVS	2049.89 7	1895.92 119	1721.29 120	2099.67 120	2064.00 124	2419.00 128	2138.00 126	4572.00 127	1541.00 126	548.00 117	937.00 117	580.00 122	1983.00 123	1971.00 127	1993.00 125	1293.00 129	2608.00 125

PCF-MVS	3738.24 13	2129.60 122	1746.89 121	2576.10 128	2258.22 129	2263.67 126	2650.06 133	6361.78 139	1676.15 128	695.66 123	1209.77 127	737.88 129	2237.28 124	2083.02 129	1835.31 121	1253.58 128	2422.45 123
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
MVS-HIRNet		1975.98 120	1797.02 122	2184.76 121	2111.07 125	2443.03 129	2503.43 128	4063.71 123	1684.46 129	711.34 124	1456.05 132	848.70 137	2396.26 132	1900.93 122	1915.01 123	1322.75 130	2330.99 122

SD-MVS		2324.36 128	1910.97 123	2806.65 135	2945.31 137	3305.03 141	3267.51 138	5962.25 138	1896.37 131	848.15 131	1224.25 128	661.55 126	2707.30 136	1913.40 123	1871.41 122	1109.38 124	2504.79 124
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
Vis-MVSNet		2390.77 130	1976.57 124	2874.00 136	2644.00 135	3248.00 139	3040.00 136	7371.00 143	1627.00 127	421.00 113	1200.00 126	622.00 124	2251.00 125	2326.00 134	2052.00 129	1517.00 138	2761.00 129
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
CMPMVS	2507.20 10	2083.60 121	1983.13 125	2200.81 122	2582.70 133	3097.30 136	2332.10 127	4364.50 125	1390.00 122	653.68 122	997.75 119	742.65 132	1880.20 122	2298.80 133	2413.60 137	1391.70 133	2941.80 130
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
CHOSEN 280x420		2225.10 123	1992.66 126	2496.28 123	2192.10 126	2641.81 130	2621.41 130	5345.34 131	2116.46 134	1002.26 142	1683.84 137	837.43 133	2338.65 126	1920.94 124	2020.28 126	1477.92 135	2727.86 126

CHOSEN 1792x2688		2225.10 123	1992.66 126	2496.28 123	2192.10 126	2641.81 130	2621.41 130	5345.34 131	2116.46 134	1002.26 142	1683.84 137	837.43 133	2338.65 126	1920.94 124	2020.28 126	1477.92 135	2727.86 126

HyFIR lowres test		2225.10 123	1992.66 126	2496.28 123	2192.10 126	2641.81 130	2621.41 130	5345.34 131	2116.46 134	1002.26 142	1683.84 137	837.43 133	2338.65 126	1920.94 124	2020.28 126	1477.92 135	2727.86 126

3Dnovator	2220.89 9	2303.77 127	2037.00 129	2615.00 129	2617.00 134	2967.00 135	2616.00 129	5882.00 137	1928.00 132	589.00 119	907.00 116	528.00 121	2443.00 134	2370.00 135	2392.00 136	1543.00 139	3167.00 132

AdaColmap		2288.90 126	2080.73 130	2531.77 126	2485.98 132	2757.87 133	2974.47 135	4914.62 128	2255.54 137	804.63 130	1611.14 136	842.30 136	2657.83 135	2056.92 128	1960.62 124	1353.09 132	3080.73 131

DeepPCF-MVS	3033.31 11	2362.79 129	2183.15 131	2572.38 127	2349.28 130	2383.16 127	2740.92 134	5212.97 130	2043.02 133	751.44 125	1466.47 133	1327.42 157	2904.33 137	2573.45 140	2227.77 130	1475.33 134	3260.73 134

SteuartSystems-ACMMP		2615.00 131	2242.57 132	3049.50 137	2828.00 136	2801.00 134	3323.00 140	6648.00 141	2491.00 139	1023.00 145	1605.00 135	697.00 127	2926.00 139	2502.00 137	2279.00 131	1549.00 140	3323.00 136
Skip Steuart: Steuart Systems R&D Blog.
TAPA-MVS	5463.68 16	2764.21 137	2434.28 133	3149.14 138	3645.15 147	3257.60 140	3452.71 142	6526.32 140	2591.85 142	651.36 121	1964.77 149	947.44 142	2924.41 138	2523.36 138	2452.68 138	1694.86 145	3302.28 135
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
3Dnovator+	3173.67 12	2938.77 138	2519.43 134	3428.00 139	3256.00 142	3708.00 145	3443.00 141	7516.00 144	2525.00 140	1121.00 149	972.00 118	925.00 141	3192.00 141	2899.00 143	2897.00 147	2040.00 150	3710.00 143

DVP-MVS		3258.34 144	2529.80 135	4108.31 147	4005.62 150	4693.14 151	4737.88 154	10195.40 154	2408.38 138	941.44 132	1505.82 134	734.32 128	3438.27 146	2449.15 136	2386.04 135	1331.25 131	3531.75 141
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
tpmrst		2688.71 135	2604.46 136	2787.00 134	2472.96 131	3190.36 137	3313.69 139	5003.06 129	1837.26 130	1097.38 148	1721.89 141	1012.20 152	2415.09 133	2970.27 148	2736.80 144	2419.79 153	4762.44 150

tpm cat1		2652.13 132	2606.66 137	2705.18 131	3151.86 139	6902.39 156	3612.17 143	5463.78 134	1457.76 123	391.31 107	1358.61 129	446.44 118	2360.09 129	2296.48 130	2290.90 132	1251.84 125	3494.04 137

CostFormer		2652.13 132	2606.66 137	2705.18 131	3151.86 139	6902.39 156	3612.17 143	5463.78 134	1457.76 123	391.31 107	1358.61 129	446.44 118	2360.09 129	2296.48 130	2290.90 132	1251.84 125	3494.04 137

tpm		2652.13 132	2606.66 137	2705.18 131	3151.86 139	6902.39 156	3612.17 143	5463.78 134	1457.76 123	391.31 107	1358.61 129	446.44 118	2360.09 129	2296.48 130	2290.90 132	1251.84 125	3494.04 137

DPM-MVS		3051.54 139	2661.57 140	3506.50 140	3532.00 145	3332.00 142	3744.00 146	7839.00 147	2772.00 145	985.00 134	1919.00 147	738.00 130	3319.00 142	2901.00 144	2715.00 142	1620.00 143	4254.00 147

OPM-MVS		3051.54 139	2661.57 140	3506.50 140	3532.00 145	3332.00 142	3744.00 146	7839.00 147	2772.00 145	985.00 134	1919.00 147	738.00 130	3319.00 142	2901.00 144	2715.00 142	1620.00 143	4254.00 147
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
TSAR-MVS + ACMM		3184.92 141	2679.45 142	3774.64 146	3302.51 143	4168.07 147	4256.74 150	8947.31 150	2634.53 143	1026.25 146	1723.72 142	1043.87 153	3387.29 144	2794.29 141	2687.41 141	1727.73 147	3704.25 142

COLMAP_ROB	3798.28 14	2690.62 136	2704.29 143	2674.67 130	3138.00 138	3522.00 144	3826.00 148	3219.00 120	2702.00 144	1138.00 152	2260.00 151	1212.00 156	2968.00 140	2936.00 147	2571.00 140	1759.00 148	3727.00 144
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
MVS_111021_HR		3192.50 142	2773.91 144	3680.86 143	3515.58 144	3815.81 146	4020.82 149	7766.11 145	2775.23 147	1300.96 157	2221.19 150	1117.25 155	3420.01 145	2873.98 142	2835.60 145	2061.69 151	3778.31 145

MSP-MVS		3241.28 143	2825.26 145	3726.65 145	3945.31 149	4305.03 148	4267.51 152	6962.25 142	2896.37 148	1068.15 147	1824.25 144	1061.55 154	4307.30 151	3013.40 149	3171.41 149	1809.38 149	3504.79 140
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
SED-MVS		3539.47 146	2909.05 146	4274.95 149	4528.93 153	4986.51 152	5003.31 156	8985.31 151	2904.53 149	1294.24 156	1839.12 145	1003.69 151	4135.17 149	2926.32 146	2897.04 148	1702.75 146	3806.13 146

PLC	4785.50 15	3275.54 145	3030.86 147	3561.00 142	4093.00 151	4596.00 150	5174.00 157	4267.00 124	3570.00 152	1495.00 158	2940.00 154	1594.00 159	3947.00 148	3817.00 152	3343.00 151	2390.00 152	1356.00 115
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
DVP-MVS++		3961.71 148	3092.38 148	4975.92 151	4850.81 156	5691.32 154	5760.96 158	12294.80 156	2980.85 150	1135.72 151	1840.86 146	949.63 143	4197.95 150	3019.10 150	2873.21 146	1615.27 142	4291.72 149

MAR-MVS		3961.62 147	3726.55 149	4235.86 148	4107.62 152	6522.83 155	4862.93 155	7956.64 149	3380.98 151	1665.13 159	3231.54 155	1650.34 160	4357.29 152	3198.61 151	3209.42 150	2465.52 154	4892.15 151
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
OMC-MVS		4439.92 150	3906.78 150	5061.92 152	4748.70 155	5679.38 153	5855.03 159	9923.00 152	4023.36 155	1740.95 160	1693.78 140	1693.78 161	4658.45 153	4254.77 153	4135.74 153	3445.36 156	5866.63 153

TSAR-MVS + MP.		4216.58 149	4674.68 151	3682.13 144	3752.63 148	4315.48 149	4264.77 151	7782.51 146	2583.81 141	1125.68 150	16722.30 161	882.60 138	3589.10 147	2523.80 139	2486.45 139	1578.08 141	3208.34 133
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
DeepC-MVS	5581.15 17	4824.92 151	5020.53 152	4596.70 150	4714.52 154	3205.14 138	3108.50 137	10234.20 155	3823.34 154	1885.23 161	9002.42 158	2045.34 163	4715.23 154	7652.65 156	3993.41 152	2922.51 155	5421.41 152
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
TSAR-MVS + COLMAP		6088.23 152	5315.97 153	6989.21 153	6522.51 157	8025.15 159	7938.31 160	15276.20 157	5401.97 157	1914.31 162	3802.65 156	1979.48 162	6704.11 156	5217.07 154	5137.16 154	3579.82 157	7648.29 154

CLD-MVS		6986.85 153	6222.57 154	7878.50 154	7707.00 158	8884.00 160	9025.00 161	15607.00 158	6148.00 158	2571.00 163	4822.00 157	2082.00 164	7875.00 158	6389.00 155	6449.00 155	4486.00 158	8784.00 156
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
LS3D		7481.83 154	6596.02 155	8515.28 155	9871.71 159	9844.03 161	9225.16 162	18308.40 159	5364.90 156	1267.41 153	2381.61 152	1512.79 158	7225.72 157	8875.69 157	9516.28 156	5193.26 159	8676.83 155

ACMMP		9999.00 155	9999.00 156	9999.00 156	9999.00 161	9999.00 162	9999.00 163	9999.00 153	9999.00 159	9999.00 165	9999.00 159	9999.00 166	9999.00 159	9999.00 158	9999.00 157	9999.00 161	9999.00 157
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
MVE	11086.50 18	13278.69 156	12303.57 157	14416.33 157	9890.00 160	17107.00 163	4634.00 153	59884.00 162	3666.00 153	966.00 133	1792.00 143	896.00 140	5680.00 155	20677.00 161	23030.00 160	5444.00 160	18957.00 158
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CNLPA		17763.08 157	15907.71 158	19927.67 158	19334.00 163	22387.00 164	22896.00 164	38668.00 160	15772.00 160	7632.00 164	13229.00 160	7123.00 165	19334.00 160	15773.00 159	15700.00 158	11702.00 162	21370.00 159

LTVRE_ROB	38377.89 19	49656.08 159	18936.71 159	85495.33 160	306852.00 166	22526.00 165	29206.00 165	112098.00 164	30022.00 161	17348.00 167	2824.00 153	11239.00 167	29457.00 161	20569.00 160	19941.00 159	18011.00 163	25436.00 160
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		31705.85 158	29167.57 160	34667.17 159	44079.00 164	28314.00 166	44778.00 166	43648.00 161	31045.00 162	14849.00 166	26179.00 162	13752.00 168	38088.00 162	30859.00 162	30835.00 161	22561.00 164	43189.00 161

PHI-MVS		99999.00 160	99999.00 161	99999.00 161	99999.00 165	99999.00 167	99999.00 167	99999.00 163	99999.00 163	99999.00 168	99999.00 163	99999.00 169	99999.00 163	99999.00 163	99999.00 162	99999.00 165	99999.00 162

MGCFI-Net		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

sasdasda		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

dmvs_re		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

test2506		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

test1111		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

ECVR-MVS		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

ET-MVSNet_ETH3D		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

UniMVSNet_ETH3D		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

thisisatest0530		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

Anonymous202405211			10000000.00 162		10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164		10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

DCV-MVSNet		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

tttt0517		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

thisisatest0515		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

DPE-MVS		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
thres100view900		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

tfpnnormal		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

tfpn200view9		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

IterMVS-SCA-FT		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

pmmvs6		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

pmmvs5		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

Anonymous20231211		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

pmmvs-eth3d		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

Anonymous20231206		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

SCA		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

canonicalmvs		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

anonymousdsp		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

FC-MVSNet-train		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

UA-Net		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

FC-MVSNet-test		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

sosnet-low-res		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

DI_MVS_pp		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

HPM-MVS++		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

pm-mvs1		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

APDe-MVS		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
pmmvs4		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

test-LLR		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

TESTMET0.1,1		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

test-mter		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

testgi		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

test20.03		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

thres600view7		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

MP-MVS		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

thres400		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

test123		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

thres200		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

test0.0.03 1		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

pmmvs3		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

EMVS		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

E-PMN		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

PGM-MVS		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

MCST-MVS		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

PMMVS2		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

PM-MVS		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

LGP-MVS_train		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

EPNet_dtu		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

NCCC		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

CP-MVS		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

CPTT-MVS		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

HQP-MVS		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

IS_MVSNet		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

Vis-MVSNet (Re-imp)		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

PatchMatch-RL		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

TDRefinement		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

EPP-MVSNet		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

PMMVS		10000000.00 161	10000000.00 162	10000000.00 162	10000000.00 167	10000000.00 168	10000000.00 168	10000000.00 165	10000000.00 164	10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164	10000000.00 164	10000000.00 163	10000000.00 166	10000000.00 163

APD-MVS		1000000000.00 228	1000000000.00 230	1000000000.00 229	1000000000.00 237	1000000000.00 237	1000000000.00 238	1000000000.00 233	1000000000.00 233	1000000000.00 238	1000000000.00 233	1000000000.00 240	1000000000.00 233	1000000000.00 232	1000000000.00 231	1000000000.00 235	1000000000.00 232
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
TPM-MVS					10000000.00 167	10000000.00 168	10000000.00 168			10000000.00 169	10000000.00 164	10000000.00 170	10000000.00 164			10000000.00 166	10000000.00 163
Ray Leroy Khuboni and Hongjun Xu: Textureless Resilient Propagation Matching in Multiple View Stereosis (TPM-MVS). SATNAC 2025
RE-MVS-def										610.10 120

9.14												0.00 1

SR-MVS					610.10 91			610.10 77				610.10 123

our_test_3					9999.00 161	99.00 62	99.00 61

MTAPA										41.98 61		28.43 57

MTMP										10000000.00 169		31.71 59

Patchmatch-RL test							10000000.00 168

tmp_tt				299.50 74	365.00 76	54.00 59	649.00 90	241.00 69	159.00 73	204.00 88	479.00 97	308.00 106	243.00 75	246.00 75	82.00 58	95.00 75

XVS					52.20 55	52.20 56	52.20 56			52.20 63		52.20 73				52.20 58

X-MVStestdata					52.20 55	52.20 56	52.20 56			52.20 63		52.20 73				52.20 58

mPP-MVS					10000000.00 167							10000000.00 170

NP-MVS									10000000.00 164

Patchmtry						1825.90 124	885.90 105	1405.90 99		1285.90 154

DeepMVS_CX						1.00 33	1.00 33	1.00 33	1.00 33	1.00 33	1.00 33	1.00 34	1.00 33	1.00 33		1.00 33	1.00 33

High-resolution multi-view benchmark