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.

viewmacassd2359aftdt		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

viewmsd2359difaftdt		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1

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 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 20	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19

v1921920		0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 20	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19

v1192		0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 20	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19

v1144		0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 20	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19

v148		0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 20	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19

v7n		0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 20	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19

v1240		0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 20	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19

v8		0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 20	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19

v10		0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 20	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19

v2v482		0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 20	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19

V42		0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 20	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19

GA-MVS		0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19	0.40 20	0.40 19	0.40 19	0.40 19	0.40 19	0.40 19

Fast-Effi-MVS+		0.41 31	0.41 31	0.41 31	0.41 31	0.41 31	0.41 31	0.41 31	0.41 31	0.41 31	0.41 31	0.41 32	0.41 31	0.41 31	0.41 31	0.41 31	0.41 31

Effi-MVS+		0.53 32	0.53 32	0.53 32	0.53 32	0.53 32	0.53 32	0.53 32	0.53 32	0.53 32	0.53 32	0.53 33	0.53 32	0.53 32	0.53 32	0.53 32	0.53 32

CDS-MVSNet		0.88 33	0.88 33	0.88 33	0.88 33	0.88 33	0.88 33	0.88 33	0.88 33	0.88 33	0.88 33	0.88 34	0.88 33	0.88 33	0.88 33	0.88 33	0.88 33
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		0.88 33	0.88 33	0.88 33	0.88 33	0.88 33	0.88 33	0.88 33	0.88 33	0.88 33	0.88 33	0.88 34	0.88 33	0.88 33	0.88 33	0.88 33	0.88 33

MDA-MVSNet-bldmvs		1.20 35	1.20 35	1.20 35	1.20 35	1.20 36	1.20 36	1.20 36	1.20 36	1.20 36	1.20 36	1.20 37	1.20 36	1.20 36	1.20 35	1.20 36	1.20 36

CVMVSNet		1.42 36	1.42 36	1.42 36	1.42 36	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 38	1.42 37	1.42 37	1.42 36	1.42 37	1.42 37

EU-MVSNet		1.42 36	1.42 36	1.42 36	1.42 36	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 38	1.42 37	1.42 37	1.42 36	1.42 37	1.42 37

PS-CasMVS		1.42 36	1.42 36	1.42 36	1.42 36	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 38	1.42 37	1.42 37	1.42 36	1.42 37	1.42 37

UniMVSNet_NR-MVSNet		1.42 36	1.42 36	1.42 36	1.42 36	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 38	1.42 37	1.42 37	1.42 36	1.42 37	1.42 37

PEN-MVS		1.42 36	1.42 36	1.42 36	1.42 36	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 38	1.42 37	1.42 37	1.42 36	1.42 37	1.42 37

TransMVSNet (Re)		1.42 36	1.42 36	1.42 36	1.42 36	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 38	1.42 37	1.42 37	1.42 36	1.42 37	1.42 37

DTE-MVSNet		1.42 36	1.42 36	1.42 36	1.42 36	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 38	1.42 37	1.42 37	1.42 36	1.42 37	1.42 37

DU-MVS		1.42 36	1.42 36	1.42 36	1.42 36	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 38	1.42 37	1.42 37	1.42 36	1.42 37	1.42 37

UniMVSNet (Re)		1.42 36	1.42 36	1.42 36	1.42 36	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 38	1.42 37	1.42 37	1.42 36	1.42 37	1.42 37

CP-MVSNet		1.42 36	1.42 36	1.42 36	1.42 36	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 38	1.42 37	1.42 37	1.42 36	1.42 37	1.42 37

WR-MVS_H		1.42 36	1.42 36	1.42 36	1.42 36	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 38	1.42 37	1.42 37	1.42 36	1.42 37	1.42 37

WR-MVS		1.42 36	1.42 36	1.42 36	1.42 36	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 38	1.42 37	1.42 37	1.42 36	1.42 37	1.42 37

NR-MVSNet		1.42 36	1.42 36	1.42 36	1.42 36	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 38	1.42 37	1.42 37	1.42 36	1.42 37	1.42 37

Baseline_NR-MVSNet		1.42 36	1.42 36	1.42 36	1.42 36	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 38	1.42 37	1.42 37	1.42 36	1.42 37	1.42 37

TranMVSNet+NR-MVSNet		1.42 36	1.42 36	1.42 36	1.42 36	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 37	1.42 38	1.42 37	1.42 37	1.42 36	1.42 37	1.42 37

CDPH-MVS		6.66 51	6.66 51	6.66 51	6.66 51	6.66 52	6.66 52	6.66 52	6.66 52	6.66 52	6.66 52	6.66 53	6.66 52	6.66 52	6.66 51	6.66 52	6.66 52

MDTV_nov1_ep13_2view		9.99 52	9.99 52	9.99 52	9.99 52	9.99 53	9.99 53	9.99 53	9.99 53	9.99 55	9.99 53	9.99 56	9.99 53	9.99 53	9.99 52	9.99 53	9.99 53

MDTV_nov1_ep13		9.99 52	9.99 52	9.99 52	9.99 52	9.99 53	9.99 53	9.99 53	9.99 53	9.99 55	9.99 53	9.99 56	9.99 53	9.99 53	9.99 52	9.99 53	9.99 53

test_method		18.19 54	15.64 54	21.17 54	19.00 54	22.00 55	22.50 55	38.00 56	15.50 55	7.50 53	13.00 55	7.00 54	19.00 56	15.50 56	15.50 54	21.00 55	21.00 55

GeoE		20.05 55	18.83 55	21.47 55	25.60 55	29.60 56	22.50 55	31.20 55	19.10 56	8.30 54	13.50 56	9.40 55	17.80 55	14.10 55	17.50 55	23.40 56	28.60 56

GBi-Net		39.84 56	35.75 56	44.63 56	43.04 56	49.88 57	51.06 57	86.51 58	35.34 57	17.20 57	29.83 57	15.85 58	43.43 59	35.35 57	35.70 56	26.51 59	48.28 59

X-MVS		52.20 57	52.20 57	52.20 57	52.20 57	52.20 58	52.20 58	52.20 57	52.20 58	52.20 65	52.20 58	52.20 75	52.20 60	52.20 58	52.20 57	52.20 60	52.20 60

new_pmnet		75.00 58	74.67 58	75.39 58	85.42 60	96.03 62	98.77 61	173.23 59	69.57 59	36.19 58	56.93 59	117.43 81	32.98 57	85.38 66	68.41 58	25.74 57	28.95 57

N_pmnet		75.00 58	74.67 58	75.39 58	85.42 60	96.03 62	98.77 61	173.23 59	69.57 59	36.19 58	56.93 59	117.43 81	32.98 57	85.38 66	68.41 58	25.74 57	28.95 57

CANet		100.44 60	93.07 60	109.04 60	111.90 62	131.06 66	119.40 64	222.42 68	80.48 61	36.93 60	70.80 61	40.92 62	89.90 61	100.59 68	101.42 61	73.68 64	126.25 61

CANet_DTU		100.44 60	93.07 60	109.04 60	111.90 62	131.06 66	119.40 64	222.42 68	80.48 61	36.93 60	70.80 61	40.92 62	89.90 61	100.59 68	101.42 61	73.68 64	126.25 61

UGNet		100.44 60	93.07 60	109.04 60	111.90 62	131.06 66	119.40 64	222.42 68	80.48 61	36.93 60	70.80 61	40.92 62	89.90 61	100.59 68	101.42 61	73.68 64	126.25 61
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		116.86 63	110.47 64	124.32 63	131.47 66	157.41 69	150.67 68	199.64 61	115.30 67	56.61 71	97.70 68	51.77 65	117.26 64	77.26 59	113.14 65	90.25 70	160.68 67

test1		116.86 63	110.47 64	124.32 63	131.47 66	157.41 69	150.67 68	199.64 61	115.30 67	56.61 71	97.70 68	51.77 65	117.26 64	77.26 59	113.14 65	90.25 70	160.68 67

FMVSNet3		116.86 63	110.47 64	124.32 63	131.47 66	157.41 69	150.67 68	199.64 61	115.30 67	56.61 71	97.70 68	51.77 65	117.26 64	77.26 59	113.14 65	90.25 70	160.68 67

FMVSNet2		116.86 63	110.47 64	124.32 63	131.47 66	157.41 69	150.67 68	199.64 61	115.30 67	56.61 71	97.70 68	51.77 65	117.26 64	77.26 59	113.14 65	90.25 70	160.68 67

FMVSNet1		116.86 63	110.47 64	124.32 63	131.47 66	157.41 69	150.67 68	199.64 61	115.30 67	56.61 71	97.70 68	51.77 65	117.26 64	77.26 59	113.14 65	90.25 70	160.68 67

MIMVSNet1		116.86 63	110.47 64	124.32 63	131.47 66	157.41 69	150.67 68	199.64 61	115.30 67	56.61 71	97.70 68	51.77 65	117.26 64	77.26 59	113.14 65	90.25 70	160.68 67

MIMVSNet		116.86 63	110.47 64	124.32 63	131.47 66	157.41 69	150.67 68	199.64 61	115.30 67	56.61 71	97.70 68	51.77 65	117.26 64	77.26 59	113.14 65	90.25 70	160.68 67

ACMMP_NAP		119.64 70	106.58 63	134.88 70	123.82 65	127.44 65	145.38 67	298.43 75	116.16 74	43.72 64	77.82 64	29.30 60	131.24 71	117.82 74	106.21 64	66.69 63	171.29 74

PVSNet_Blended_VisFu		129.22 71	115.76 71	144.92 71	140.60 73	162.80 76	166.50 75	281.20 72	114.70 64	55.50 68	96.20 65	51.80 72	140.60 72	114.70 71	114.70 72	85.10 67	155.40 64

PVSNet_BlendedMVS		129.22 71	115.76 71	144.92 71	140.60 73	162.80 76	166.50 75	281.20 72	114.70 64	55.50 68	96.20 65	51.80 72	140.60 72	114.70 71	114.70 72	85.10 67	155.40 64

PVSNet_Blended		129.22 71	115.76 71	144.92 71	140.60 73	162.80 76	166.50 75	281.20 72	114.70 64	55.50 68	96.20 65	51.80 72	140.60 72	114.70 71	114.70 72	85.10 67	155.40 64

FA-MVS(training)		203.85 74	180.15 74	231.50 74	222.82 76	259.22 79	245.99 78	478.61 77	172.32 77	82.03 79	130.35 75	72.14 78	221.74 76	190.35 75	197.39 75	137.78 78	239.26 75

SixPastTwentyTwo		210.90 75	189.75 75	235.58 75	225.41 77	284.88 80	267.17 79	485.88 78	164.28 76	76.51 78	137.62 76	76.69 79	214.49 75	206.28 76	208.00 76	144.02 79	250.52 76

WB-MVS		316.93 76	277.98 76	362.37 77	386.49 79	371.32 85	360.90 84	844.52 86	232.58 78	102.36 80	215.57 78	104.13 80	287.33 78	336.96 78	318.49 77	192.62 80	366.78 78

RPSCF		376.53 77	341.80 77	417.05 78	418.60 81	457.01 86	467.46 85	825.25 85	336.12 80	159.32 84	260.40 80	151.13 85	386.94 79	364.25 79	352.10 78	244.72 81	471.62 79

EG-PatchMatch MVS		402.98 78	364.36 78	448.05 79	435.50 82	473.00 87	489.60 86	910.20 87	338.60 81	127.30 81	205.10 77	123.50 83	434.60 80	450.70 83	447.70 81	291.10 83	511.90 80

MS-PatchMatch		438.85 79	388.71 79	497.33 80	479.00 83	527.00 88	558.00 89	988.00 88	379.00 83	174.00 86	278.00 82	162.00 86	494.00 84	418.00 80	412.00 79	291.00 82	545.00 83

ADS-MVSNet		452.36 80	406.02 80	506.42 83	534.76 89	628.22 91	552.79 88	1009.99 95	333.98 79	149.26 82	246.67 79	149.01 84	447.03 82	465.35 84	501.18 84	344.69 86	517.75 81

PatchmatchNet		452.63 81	410.20 81	502.13 82	520.70 88	614.40 89	546.00 87	1018.80 96	379.00 83	167.50 85	277.10 81	169.40 87	437.10 81	437.10 81	457.50 82	322.70 85	536.90 82
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
DELS-MVS		458.84 82	423.31 82	500.30 81	511.99 87	616.59 90	578.86 90	991.10 89	355.79 82	158.99 83	319.09 84	190.62 89	453.64 83	437.73 82	439.52 80	307.20 84	603.81 84
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 83	472.40 83	607.16 85	690.38 97	718.85 94	636.03 91	1231.66 98	422.74 85	198.65 89	325.68 85	194.97 90	512.90 86	509.81 86	513.65 85	373.33 88	621.11 85

gm-plane-assit		551.84 84	503.49 85	608.24 86	411.90 80	370.41 81	267.30 80	710.53 81	454.42 88	785.72 128	491.23 101	326.12 110	881.92 105	538.27 90	650.05 99	592.08 107	693.94 87

IB-MVS	750.90 3	552.99 85	511.38 89	601.53 84	606.02 92	735.75 96	688.75 94	1183.86 97	436.09 87	210.63 92	397.40 88	233.85 94	551.05 87	521.77 87	533.78 87	368.88 87	721.05 92
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
IterMVS		554.60 86	488.63 84	631.57 90	636.90 94	700.80 92	674.70 93	1271.10 100	430.50 86	207.10 91	370.50 87	202.70 92	611.80 90	534.20 89	545.30 88	387.80 89	636.40 86
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
GG-mvs-BLEND		557.53 87	503.49 85	620.58 87	485.90 84	370.41 81	267.30 80	710.53 81	454.42 88	785.72 128	491.23 101	326.12 110	881.92 105	538.27 90	650.05 99	592.08 107	693.94 87

gg-mvs-nofinetune		557.53 87	503.49 85	620.58 87	485.90 84	370.41 81	267.30 80	710.53 81	454.42 88	785.72 128	491.23 101	326.12 110	881.92 105	538.27 90	650.05 99	592.08 107	693.94 87

CR-MVSNet		557.53 87	503.49 85	620.58 87	485.90 84	370.41 81	267.30 80	710.53 81	454.42 88	785.72 128	491.23 101	326.12 110	881.92 105	538.27 90	650.05 99	592.08 107	693.94 87

Gipuma		587.77 90	529.57 90	655.67 91	637.00 95	733.00 95	749.00 96	1245.00 99	525.00 95	269.00 102	445.00 97	253.00 96	637.00 92	525.00 88	525.00 86	397.00 90	701.00 91
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MVS_Test		654.54 91	583.51 92	737.40 93	721.80 99	822.10 98	808.60 98	1494.00 102	542.20 97	259.90 95	441.60 90	257.70 98	689.10 94	620.80 95	617.70 90	451.00 95	782.50 94

casdiffmvs		654.54 91	583.51 92	737.40 93	721.80 99	822.10 98	808.60 98	1494.00 102	542.20 97	259.90 95	441.60 90	257.70 98	689.10 94	620.80 95	617.70 90	451.00 95	782.50 94
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 91	583.51 92	737.40 93	721.80 99	822.10 98	808.60 98	1494.00 102	542.20 97	259.90 95	441.60 90	257.70 98	689.10 94	620.80 95	617.70 90	451.00 95	782.50 94
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 91	583.51 92	737.40 93	721.80 99	822.10 98	808.60 98	1494.00 102	542.20 97	259.90 95	441.60 90	257.70 98	689.10 94	620.80 95	617.70 90	451.00 95	782.50 94

baseline1		654.54 91	583.51 92	737.40 93	721.80 99	822.10 98	808.60 98	1494.00 102	542.20 97	259.90 95	441.60 90	257.70 98	689.10 94	620.80 95	617.70 90	451.00 95	782.50 94

casdiffmvs_mvg		654.54 91	583.51 92	737.40 93	721.80 99	822.10 98	808.60 98	1494.00 102	542.20 97	259.90 95	441.60 90	257.70 98	689.10 94	620.80 95	617.70 90	451.00 95	782.50 94
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 91	583.51 92	737.40 93	721.80 99	822.10 98	808.60 98	1494.00 102	542.20 97	259.90 95	441.60 90	257.70 98	689.10 94	620.80 95	617.70 90	451.00 95	782.50 94

pmnet_mix02		659.48 98	547.83 91	789.74 101	720.05 98	846.87 105	740.59 95	2153.63 114	456.15 92	191.24 87	336.49 86	200.39 91	511.90 85	608.74 94	634.29 97	421.05 92	751.91 93

ACMH+	702.88 1	670.82 99	589.81 99	765.33 100	662.52 96	701.42 93	795.24 97	1698.33 110	598.81 105	226.55 93	403.02 89	187.13 88	786.82 102	724.80 105	646.56 98	422.52 93	866.95 102

new-patchmatchnet		712.65 100	632.59 100	806.05 104	787.79 106	936.25 109	882.47 106	1795.72 111	528.60 96	244.29 94	471.90 98	257.36 97	681.47 93	705.16 104	659.05 103	444.55 94	869.82 103

IterMVS-LS		714.97 101	638.00 102	804.77 103	793.60 107	914.20 107	886.50 108	1612.70 109	588.30 104	285.30 103	491.20 100	278.40 106	759.20 101	677.40 103	681.30 104	491.30 102	835.20 101
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CSCG		727.26 102	663.25 103	801.94 102	590.65 91	811.25 97	854.12 105	1805.32 112	816.43 110	388.25 108	612.42 109	345.37 116	621.61 91	507.46 85	471.55 83	551.65 105	1078.31 114

MVSTER		834.63 103	737.03 105	948.49 105	988.86 109	1140.51 120	1129.34 118	1832.80 113	682.42 106	319.01 104	550.98 107	311.35 109	872.51 104	763.95 106	757.83 105	548.41 104	952.20 105

PMVS	743.55 2	836.66 104	637.90 101	1068.55 113	1306.50 121	875.12 106	1166.70 119	2629.00 117	512.24 94	196.22 88	282.69 83	237.15 95	597.87 89	842.47 107	765.54 106	514.99 103	950.09 104
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
RPMNet		858.01 105	961.99 111	736.69 92	550.05 90	1120.24 118	1212.05 120	463.05 76	485.90 93	550.05 120	580.05 108	890.05 141	559.05 88	1485.90 122	1185.90 120	1085.90 125	985.90 107

PatchT		878.42 106	785.05 106	987.36 106	1050.05 117	922.05 108	1111.05 116	677.05 80	950.05 113	1285.90 156	750.05 115	640.05 127	850.05 103	950.05 108	950.05 108	950.05 118	333.05 77

ACMH	935.68 4	948.23 107	857.00 107	1054.67 112	946.00 108	970.00 110	1125.00 117	2467.00 115	823.00 111	330.00 106	622.00 110	211.00 93	891.00 109	970.00 110	1061.00 117	569.00 106	1342.00 116
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MSLP-MVS++		993.91 108	732.21 104	1299.24 117	1631.22 124	1345.26 122	1480.05 123	2524.20 116	735.65 107	463.57 118	499.89 105	302.78 107	1292.66 119	675.99 102	612.79 89	403.71 91	953.11 106

EPMVS		999.00 109	999.00 112	999.00 107	999.00 110	999.00 111	999.00 109	999.00 90	999.00 115	999.00 138	999.00 122	999.00 147	999.00 111	999.00 111	999.00 111	999.00 119	999.00 108

uanet_test		1000.00 110	1000.00 114	1000.00 108	1000.00 112	1000.00 113	1000.00 111	1000.00 91	1000.00 117	1000.00 140	1000.00 124	1000.00 149	1000.00 113	1000.00 113	1000.00 113	1000.00 121	1000.00 110

sosnet		1000.00 110	1000.00 114	1000.00 108	1000.00 112	1000.00 113	1000.00 111	1000.00 91	1000.00 117	1000.00 140	1000.00 124	1000.00 149	1000.00 113	1000.00 113	1000.00 113	1000.00 121	1000.00 110

USDC		1000.00 110	1000.00 114	1000.00 108	1000.00 112	1000.00 113	1000.00 111	1000.00 91	1000.00 117	1000.00 140	1000.00 124	1000.00 149	1000.00 113	1000.00 113	1000.00 113	1000.00 121	1000.00 110

TinyColmap		1000.00 110	1000.00 114	1000.00 108	1000.00 112	1000.00 113	1000.00 111	1000.00 91	1000.00 117	1000.00 140	1000.00 124	1000.00 149	1000.00 113	1000.00 113	1000.00 113	1000.00 121	1000.00 110

ACMM	1129.18 5	1047.56 114	912.90 108	1204.67 114	1040.21 116	1016.71 117	1105.32 115	2918.67 120	813.91 109	327.22 105	665.34 111	267.72 105	1192.58 118	1091.35 118	991.88 110	643.99 112	1543.40 123
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MVS_111021_LR		1055.24 115	916.36 109	1217.27 115	1129.93 119	1268.26 121	1313.88 122	2635.76 118	923.19 112	396.92 112	704.88 113	327.66 114	1136.32 117	965.38 109	946.95 107	690.83 115	1278.20 115

ACMP	1170.86 6	1091.37 116	943.23 110	1264.21 116	1112.10 118	1138.94 119	1276.90 121	2675.36 119	989.62 114	426.15 116	742.77 114	349.09 118	1454.51 123	1047.36 117	969.90 109	640.22 111	1364.94 118
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
TSAR-MVS + GP.		1239.27 117	1094.74 120	1407.89 118	1220.99 120	1845.47 127	1680.98 126	3191.81 121	1098.41 121	362.98 107	679.12 112	339.31 115	1323.06 120	1173.24 121	1093.83 118	667.49 113	1433.78 119

ACMMPR		1265.65 118	1083.59 119	1478.06 120	1441.06 123	1438.61 125	1540.68 125	3284.05 123	1219.68 123	458.81 117	803.22 117	346.91 117	1421.66 122	1126.11 120	1150.51 119	722.08 116	1500.09 121

DeepC-MVS_fast	2081.98 8	1311.87 119	1172.50 121	1474.47 119	1411.78 122	1397.23 124	1519.03 124	3401.40 124	1201.29 122	417.90 114	801.95 116	976.25 146	1409.37 121	1114.52 119	1201.12 121	687.33 114	1515.14 122
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
FPMVS		1356.65 120	1072.60 118	1688.04 121	1840.79 125	1397.01 123	1793.24 127	4397.86 128	804.66 108	408.78 113	538.65 106	407.36 119	894.84 110	1587.73 123	1286.38 122	792.73 117	1486.39 120

OpenMVS	2049.89 7	1895.92 121	1721.29 122	2099.67 122	2064.00 126	2419.00 130	2138.00 128	4572.00 129	1541.00 128	548.00 119	937.00 119	580.00 124	1983.00 125	1971.00 129	1993.00 127	1293.00 131	2608.00 127

MVS-HIRNet		1975.98 122	1797.02 124	2184.76 123	2111.07 127	2443.03 131	2503.43 130	4063.71 125	1684.46 131	711.34 126	1456.05 134	848.70 139	2396.26 134	1900.93 124	1915.01 125	1322.75 132	2330.99 124

CMPMVS	2507.20 10	2083.60 123	1983.13 127	2200.81 124	2582.70 135	3097.30 138	2332.10 129	4364.50 127	1390.00 124	653.68 124	997.75 121	742.65 134	1880.20 124	2298.80 135	2413.60 139	1391.70 135	2941.80 132
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
PCF-MVS	3738.24 13	2129.60 124	1746.89 123	2576.10 130	2258.22 131	2263.67 128	2650.06 135	6361.78 141	1676.15 130	695.66 125	1209.77 129	737.88 131	2237.28 126	2083.02 131	1835.31 123	1253.58 130	2422.45 125
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
CHOSEN 280x420		2225.10 125	1992.66 128	2496.28 125	2192.10 128	2641.81 132	2621.41 132	5345.34 133	2116.46 136	1002.26 144	1683.84 139	837.43 135	2338.65 128	1920.94 126	2020.28 128	1477.92 137	2727.86 128

CHOSEN 1792x2688		2225.10 125	1992.66 128	2496.28 125	2192.10 128	2641.81 132	2621.41 132	5345.34 133	2116.46 136	1002.26 144	1683.84 139	837.43 135	2338.65 128	1920.94 126	2020.28 128	1477.92 137	2727.86 128

HyFIR lowres test		2225.10 125	1992.66 128	2496.28 125	2192.10 128	2641.81 132	2621.41 132	5345.34 133	2116.46 136	1002.26 144	1683.84 139	837.43 135	2338.65 128	1920.94 126	2020.28 128	1477.92 137	2727.86 128

AdaColmap		2288.90 128	2080.73 132	2531.77 128	2485.98 134	2757.87 135	2974.47 137	4914.62 130	2255.54 139	804.63 132	1611.14 138	842.30 138	2657.83 137	2056.92 130	1960.62 126	1353.09 134	3080.73 133

3Dnovator	2220.89 9	2303.77 129	2037.00 131	2615.00 131	2617.00 136	2967.00 137	2616.00 131	5882.00 139	1928.00 134	589.00 121	907.00 118	528.00 123	2443.00 136	2370.00 137	2392.00 138	1543.00 141	3167.00 134

SD-MVS		2324.36 130	1910.97 125	2806.65 137	2945.31 139	3305.03 143	3267.51 140	5962.25 140	1896.37 133	848.15 133	1224.25 130	661.55 128	2707.30 138	1913.40 125	1871.41 124	1109.38 126	2504.79 126
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
DeepPCF-MVS	3033.31 11	2362.79 131	2183.15 133	2572.38 129	2349.28 132	2383.16 129	2740.92 136	5212.97 132	2043.02 135	751.44 127	1466.47 135	1327.42 159	2904.33 139	2573.45 142	2227.77 132	1475.33 136	3260.73 136

Vis-MVSNet		2390.77 132	1976.57 126	2874.00 138	2644.00 137	3248.00 141	3040.00 138	7371.00 145	1627.00 129	421.00 115	1200.00 128	622.00 126	2251.00 127	2326.00 136	2052.00 131	1517.00 140	2761.00 131
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
SteuartSystems-ACMMP		2615.00 133	2242.57 134	3049.50 139	2828.00 138	2801.00 136	3323.00 142	6648.00 143	2491.00 141	1023.00 147	1605.00 137	697.00 129	2926.00 141	2502.00 139	2279.00 133	1549.00 142	3323.00 138
Skip Steuart: Steuart Systems R&D Blog.
tpm cat1		2652.13 134	2606.66 139	2705.18 133	3151.86 141	6902.39 158	3612.17 145	5463.78 136	1457.76 125	391.31 109	1358.61 131	446.44 120	2360.09 131	2296.48 132	2290.90 134	1251.84 127	3494.04 139

CostFormer		2652.13 134	2606.66 139	2705.18 133	3151.86 141	6902.39 158	3612.17 145	5463.78 136	1457.76 125	391.31 109	1358.61 131	446.44 120	2360.09 131	2296.48 132	2290.90 134	1251.84 127	3494.04 139

tpm		2652.13 134	2606.66 139	2705.18 133	3151.86 141	6902.39 158	3612.17 145	5463.78 136	1457.76 125	391.31 109	1358.61 131	446.44 120	2360.09 131	2296.48 132	2290.90 134	1251.84 127	3494.04 139

tpmrst		2688.71 137	2604.46 138	2787.00 136	2472.96 133	3190.36 139	3313.69 141	5003.06 131	1837.26 132	1097.38 150	1721.89 143	1012.20 154	2415.09 135	2970.27 150	2736.80 146	2419.79 155	4762.44 152

COLMAP_ROB	3798.28 14	2690.62 138	2704.29 145	2674.67 132	3138.00 140	3522.00 146	3826.00 150	3219.00 122	2702.00 146	1138.00 154	2260.00 153	1212.00 158	2968.00 142	2936.00 149	2571.00 142	1759.00 150	3727.00 146
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
TAPA-MVS	5463.68 16	2764.21 139	2434.28 135	3149.14 140	3645.15 149	3257.60 142	3452.71 144	6526.32 142	2591.85 144	651.36 123	1964.77 151	947.44 144	2924.41 140	2523.36 140	2452.68 140	1694.86 147	3302.28 137
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
3Dnovator+	3173.67 12	2938.77 140	2519.43 136	3428.00 141	3256.00 144	3708.00 147	3443.00 143	7516.00 146	2525.00 142	1121.00 151	972.00 120	925.00 143	3192.00 143	2899.00 145	2897.00 149	2040.00 152	3710.00 145

DPM-MVS		3051.54 141	2661.57 142	3506.50 142	3532.00 147	3332.00 144	3744.00 148	7839.00 149	2772.00 147	985.00 136	1919.00 149	738.00 132	3319.00 144	2901.00 146	2715.00 144	1620.00 145	4254.00 149

OPM-MVS		3051.54 141	2661.57 142	3506.50 142	3532.00 147	3332.00 144	3744.00 148	7839.00 149	2772.00 147	985.00 136	1919.00 149	738.00 132	3319.00 144	2901.00 146	2715.00 144	1620.00 145	4254.00 149
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
TSAR-MVS + ACMM		3184.92 143	2679.45 144	3774.64 148	3302.51 145	4168.07 149	4256.74 152	8947.31 152	2634.53 145	1026.25 148	1723.72 144	1043.87 155	3387.29 146	2794.29 143	2687.41 143	1727.73 149	3704.25 144

MVS_111021_HR		3192.50 144	2773.91 146	3680.86 145	3515.58 146	3815.81 148	4020.82 151	7766.11 147	2775.23 149	1300.96 159	2221.19 152	1117.25 157	3420.01 147	2873.98 144	2835.60 147	2061.69 153	3778.31 147

MSP-MVS		3241.28 145	2825.26 147	3726.65 147	3945.31 151	4305.03 150	4267.51 154	6962.25 144	2896.37 150	1068.15 149	1824.25 146	1061.55 156	4307.30 153	3013.40 151	3171.41 151	1809.38 151	3504.79 142
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
DVP-MVS		3258.34 146	2529.80 137	4108.31 149	4005.62 152	4693.14 153	4737.88 156	10195.40 156	2408.38 140	941.44 134	1505.82 136	734.32 130	3438.27 148	2449.15 138	2386.04 137	1331.25 133	3531.75 143
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
PLC	4785.50 15	3275.54 147	3030.86 149	3561.00 144	4093.00 153	4596.00 152	5174.00 159	4267.00 126	3570.00 154	1495.00 160	2940.00 156	1594.00 161	3947.00 150	3817.00 154	3343.00 153	2390.00 154	1356.00 117
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
SED-MVS		3539.47 148	2909.05 148	4274.95 151	4528.93 155	4986.51 154	5003.31 158	8985.31 153	2904.53 151	1294.24 158	1839.12 147	1003.69 153	4135.17 151	2926.32 148	2897.04 150	1702.75 148	3806.13 148

MAR-MVS		3961.62 149	3726.55 151	4235.86 150	4107.62 154	6522.83 157	4862.93 157	7956.64 151	3380.98 153	1665.13 161	3231.54 157	1650.34 162	4357.29 154	3198.61 153	3209.42 152	2465.52 156	4892.15 153
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
DVP-MVS++		3961.71 150	3092.38 150	4975.92 153	4850.81 158	5691.32 156	5760.96 160	12294.80 158	2980.85 152	1135.72 153	1840.86 148	949.63 145	4197.95 152	3019.10 152	2873.21 148	1615.27 144	4291.72 151

TSAR-MVS + MP.		4216.58 151	4674.68 153	3682.13 146	3752.63 150	4315.48 151	4264.77 153	7782.51 148	2583.81 143	1125.68 152	16722.30 163	882.60 140	3589.10 149	2523.80 141	2486.45 141	1578.08 143	3208.34 135
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
OMC-MVS		4439.92 152	3906.78 152	5061.92 154	4748.70 157	5679.38 155	5855.03 161	9923.00 154	4023.36 157	1740.95 162	1693.78 142	1693.78 163	4658.45 155	4254.77 155	4135.74 155	3445.36 158	5866.63 155

DeepC-MVS	5581.15 17	4824.92 153	5020.53 154	4596.70 152	4714.52 156	3205.14 140	3108.50 139	10234.20 157	3823.34 156	1885.23 163	9002.42 160	2045.34 165	4715.23 156	7652.65 158	3993.41 154	2922.51 157	5421.41 154
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		6088.23 154	5315.97 155	6989.21 155	6522.51 159	8025.15 161	7938.31 162	15276.20 159	5401.97 159	1914.31 164	3802.65 158	1979.48 164	6704.11 158	5217.07 156	5137.16 156	3579.82 159	7648.29 156

CLD-MVS		6986.85 155	6222.57 156	7878.50 156	7707.00 160	8884.00 162	9025.00 163	15607.00 160	6148.00 160	2571.00 165	4822.00 159	2082.00 166	7875.00 160	6389.00 157	6449.00 157	4486.00 160	8784.00 158
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
LS3D		7481.83 156	6596.02 157	8515.28 157	9871.71 161	9844.03 163	9225.16 164	18308.40 161	5364.90 158	1267.41 155	2381.61 154	1512.79 160	7225.72 159	8875.69 159	9516.28 158	5193.26 161	8676.83 157

ACMMP		9999.00 157	9999.00 158	9999.00 158	9999.00 163	9999.00 164	9999.00 165	9999.00 155	9999.00 161	9999.00 167	9999.00 161	9999.00 168	9999.00 161	9999.00 160	9999.00 159	9999.00 163	9999.00 159
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	13278.69 158	12303.57 159	14416.33 159	9890.00 162	17107.00 165	4634.00 155	59884.00 164	3666.00 155	966.00 135	1792.00 145	896.00 142	5680.00 157	20677.00 163	23030.00 162	5444.00 162	18957.00 160
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CNLPA		17763.08 159	15907.71 160	19927.67 160	19334.00 165	22387.00 166	22896.00 166	38668.00 162	15772.00 162	7632.00 166	13229.00 162	7123.00 167	19334.00 162	15773.00 161	15700.00 160	11702.00 164	21370.00 161

MSDG		31705.85 160	29167.57 162	34667.17 161	44079.00 166	28314.00 168	44778.00 168	43648.00 163	31045.00 164	14849.00 168	26179.00 164	13752.00 170	38088.00 164	30859.00 164	30835.00 163	22561.00 166	43189.00 163

LTVRE_ROB	38377.89 19	49656.08 161	18936.71 161	85495.33 162	306852.00 168	22526.00 167	29206.00 167	112098.00 166	30022.00 163	17348.00 169	2824.00 155	11239.00 169	29457.00 163	20569.00 162	19941.00 161	18011.00 165	25436.00 162
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
PHI-MVS		99999.00 162	99999.00 163	99999.00 163	99999.00 167	99999.00 169	99999.00 169	99999.00 165	99999.00 165	99999.00 170	99999.00 165	99999.00 171	99999.00 165	99999.00 165	99999.00 164	99999.00 167	99999.00 164

MGCFI-Net		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

sasdasda		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

dmvs_re		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

test2506		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

test1111		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

ECVR-MVS		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

ET-MVSNet_ETH3D		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

UniMVSNet_ETH3D		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

thisisatest0530		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

DCV-MVSNet		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

tttt0517		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

thisisatest0515		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

DPE-MVS		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
thres100view900		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

tfpnnormal		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

tfpn200view9		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

IterMVS-SCA-FT		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

pmmvs6		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

pmmvs5		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

Anonymous20231211		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

pmmvs-eth3d		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

Anonymous20231206		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

SCA		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

canonicalmvs		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

anonymousdsp		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

FC-MVSNet-train		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

UA-Net		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

FC-MVSNet-test		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

sosnet-low-res		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

DI_MVS_pp		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

HPM-MVS++		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

pm-mvs1		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

APDe-MVS		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
pmmvs4		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

test-LLR		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

TESTMET0.1,1		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

test-mter		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

testgi		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

test20.03		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

thres600view7		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

MP-MVS		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

thres400		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

test123		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

thres200		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

test0.0.03 1		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

pmmvs3		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

EMVS		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

E-PMN		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

PGM-MVS		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

MCST-MVS		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

PMMVS2		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

PM-MVS		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

LGP-MVS_train		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

EPNet_dtu		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

NCCC		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

CP-MVS		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

CPTT-MVS		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

HQP-MVS		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

IS_MVSNet		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

Vis-MVSNet (Re-imp)		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

PatchMatch-RL		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

TDRefinement		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

EPP-MVSNet		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

PMMVS		10000000.00 163	10000000.00 164	10000000.00 164	10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166	10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

APD-MVS		1000000000.00 230	1000000000.00 232	1000000000.00 231	1000000000.00 239	1000000000.00 239	1000000000.00 240	1000000000.00 235	1000000000.00 235	1000000000.00 240	1000000000.00 235	1000000000.00 242	1000000000.00 235	1000000000.00 234	1000000000.00 233	1000000000.00 237	1000000000.00 234
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
TPM-MVS					10000000.00 169	10000000.00 170	10000000.00 170			10000000.00 171	10000000.00 166	10000000.00 172	10000000.00 166			10000000.00 168	10000000.00 165
Ray Leroy Khuboni and Hongjun Xu: Textureless Resilient Propagation Matching in Multiple View Stereosis (TPM-MVS). SATNAC 2025
RE-MVS-def										610.10 122

9.14												0.00 1

SR-MVS					610.10 93			610.10 79				610.10 125

Anonymous202405211			10000000.00 164		10000000.00 169	10000000.00 170	10000000.00 170	10000000.00 167	10000000.00 166		10000000.00 166	10000000.00 172	10000000.00 166	10000000.00 166	10000000.00 165	10000000.00 168	10000000.00 165

our_test_3					9999.00 163	99.00 64	99.00 63

ambc			999.00 112		999.00 110	999.00 111	999.00 109		999.00 115	999.00 138	999.00 122	999.00 147	999.00 111	999.00 111	999.00 111	999.00 119	999.00 108

MTAPA										41.98 63		28.43 59

MTMP										10000000.00 171		31.71 61

Patchmatch-RL test							10000000.00 170

tmp_tt				299.50 76	365.00 78	54.00 61	649.00 92	241.00 71	159.00 75	204.00 90	479.00 99	308.00 108	243.00 77	246.00 77	82.00 60	95.00 77

XVS					52.20 57	52.20 58	52.20 58			52.20 65		52.20 75				52.20 60

X-MVStestdata					52.20 57	52.20 58	52.20 58			52.20 65		52.20 75				52.20 60

mPP-MVS					10000000.00 169							10000000.00 172

NP-MVS									10000000.00 166

Patchmtry						1825.90 126	885.90 107	1405.90 101		1285.90 156

DeepMVS_CX						1.00 35	1.00 35	1.00 35	1.00 35	1.00 35	1.00 35	1.00 36	1.00 35	1.00 35		1.00 35	1.00 35

High-resolution multi-view benchmark