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.

xxxxxxxxxxxxxcwj		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	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

CS-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

abl_6				0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1			0.00 1	0.00 1

DROMVSNet		0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	0.00 1	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 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

v1921920		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

v1192		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

v1144		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

v148		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

v7n		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

v1240		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

v8		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

v10		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

v2v482		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

V42		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

GA-MVS		0.40 14	0.40 14	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 15	0.40 16	0.40 15	0.40 14	0.40 14	0.40 15	0.40 15

Fast-Effi-MVS+		0.41 26	0.41 26	0.41 27	0.41 27	0.41 27	0.41 27	0.41 27	0.41 27	0.41 27	0.41 27	0.41 28	0.41 27	0.41 26	0.41 26	0.41 27	0.41 27

Effi-MVS+		0.53 27	0.53 27	0.53 28	0.53 28	0.53 28	0.53 28	0.53 28	0.53 28	0.53 28	0.53 28	0.53 29	0.53 28	0.53 27	0.53 27	0.53 28	0.53 28

CDS-MVSNet		0.88 28	0.88 28	0.88 29	0.88 29	0.88 29	0.88 29	0.88 29	0.88 29	0.88 29	0.88 29	0.88 30	0.88 29	0.88 28	0.88 28	0.88 29	0.88 29
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS		0.88 28	0.88 28	0.88 29	0.88 29	0.88 29	0.88 29	0.88 29	0.88 29	0.88 29	0.88 29	0.88 30	0.88 29	0.88 28	0.88 28	0.88 29	0.88 29

DeepMVS_CX						1.00 31	1.00 31	1.00 31	1.00 31	1.00 31	1.00 31	1.00 32	1.00 31	1.00 30		1.00 31	1.00 31

MDA-MVSNet-bldmvs		1.20 30	1.20 30	1.20 31	1.20 31	1.20 32	1.20 32	1.20 32	1.20 32	1.20 32	1.20 32	1.20 33	1.20 32	1.20 31	1.20 30	1.20 32	1.20 32

CVMVSNet		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

EU-MVSNet		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

PS-CasMVS		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

UniMVSNet_NR-MVSNet		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

PEN-MVS		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

TransMVSNet (Re)		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

DTE-MVSNet		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

DU-MVS		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

UniMVSNet (Re)		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

CP-MVSNet		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

WR-MVS_H		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

WR-MVS		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

NR-MVSNet		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

Baseline_NR-MVSNet		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

TranMVSNet+NR-MVSNet		1.42 31	1.42 31	1.42 32	1.42 32	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 33	1.42 34	1.42 33	1.42 32	1.42 31	1.42 33	1.42 33

CDPH-MVS		6.66 46	6.66 46	6.66 47	6.66 47	6.66 48	6.66 48	6.66 48	6.66 48	6.66 48	6.66 48	6.66 49	6.66 48	6.66 47	6.66 46	6.66 48	6.66 48

MDTV_nov1_ep13_2view		9.99 47	9.99 47	9.99 48	9.99 48	9.99 49	9.99 49	9.99 49	9.99 49	9.99 51	9.99 49	9.99 52	9.99 49	9.99 48	9.99 47	9.99 49	9.99 49

MDTV_nov1_ep13		9.99 47	9.99 47	9.99 48	9.99 48	9.99 49	9.99 49	9.99 49	9.99 49	9.99 51	9.99 49	9.99 52	9.99 49	9.99 48	9.99 47	9.99 49	9.99 49

test_method		18.19 49	15.64 49	21.17 50	19.00 50	22.00 51	22.50 51	38.00 52	15.50 51	7.50 49	13.00 51	7.00 50	19.00 52	15.50 51	15.50 49	21.00 51	21.00 51

GeoE		20.05 50	18.83 50	21.47 51	25.60 51	29.60 52	22.50 51	31.20 51	19.10 52	8.30 50	13.50 52	9.40 51	17.80 51	14.10 50	17.50 50	23.40 52	28.60 52

GBi-Net		39.84 51	35.75 51	44.63 52	43.04 52	49.88 53	51.06 53	86.51 54	35.34 53	17.20 53	29.83 53	15.85 54	43.43 55	35.35 52	35.70 51	26.51 55	48.28 55

X-MVS		52.20 52	52.20 52	52.20 53	52.20 53	52.20 54	52.20 54	52.20 53	52.20 54	52.20 63	52.20 54	52.20 73	52.20 56	52.20 53	52.20 52	52.20 56	52.20 56

new_pmnet		75.00 53	74.67 53	75.39 54	85.42 56	96.03 58	98.77 57	173.23 55	69.57 55	36.19 54	56.93 55	117.43 78	32.98 53	85.38 61	68.41 53	25.74 53	28.95 53

N_pmnet		75.00 53	74.67 53	75.39 54	85.42 56	96.03 58	98.77 57	173.23 55	69.57 55	36.19 54	56.93 55	117.43 78	32.98 53	85.38 61	68.41 53	25.74 53	28.95 53

CANet		100.44 55	93.07 55	109.04 56	111.90 58	131.06 63	119.40 60	222.42 64	80.48 57	36.93 56	70.80 57	40.92 59	89.90 57	100.59 63	101.42 56	73.68 61	126.25 57

CANet_DTU		100.44 55	93.07 55	109.04 56	111.90 58	131.06 63	119.40 60	222.42 64	80.48 57	36.93 56	70.80 57	40.92 59	89.90 57	100.59 63	101.42 56	73.68 61	126.25 57

MVS_0304		100.44 55	93.07 55	109.04 56	111.90 58	131.06 63	119.40 60	222.42 64	80.48 57	36.93 56	70.80 57	40.92 59	89.90 57	100.59 63	101.42 56	73.68 61	126.25 57

UGNet		100.44 55	93.07 55	109.04 56	111.90 58	131.06 63	119.40 60	222.42 64	80.48 57	36.93 56	70.80 57	40.92 59	89.90 57	100.59 63	101.42 56	73.68 61	126.25 57
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 66	106.58 59	134.88 67	123.82 62	127.44 61	145.38 64	298.43 72	116.16 71	43.72 61	77.82 61	29.30 56	131.24 68	117.82 70	106.21 60	66.69 59	171.29 71

zzz-MVS		119.64 66	106.58 59	134.88 67	123.82 62	127.44 61	145.38 64	298.43 72	116.16 71	43.72 61	77.82 61	29.30 56	131.24 68	117.82 70	106.21 60	66.69 59	171.29 71

PVSNet_Blended_VisFu		129.22 68	115.76 68	144.92 69	140.60 71	162.80 74	166.50 73	281.20 69	114.70 61	55.50 66	96.20 63	51.80 70	140.60 70	114.70 67	114.70 69	85.10 65	155.40 61

PVSNet_BlendedMVS		129.22 68	115.76 68	144.92 69	140.60 71	162.80 74	166.50 73	281.20 69	114.70 61	55.50 66	96.20 63	51.80 70	140.60 70	114.70 67	114.70 69	85.10 65	155.40 61

PVSNet_Blended		129.22 68	115.76 68	144.92 69	140.60 71	162.80 74	166.50 73	281.20 69	114.70 61	55.50 66	96.20 63	51.80 70	140.60 70	114.70 67	114.70 69	85.10 65	155.40 61

FMVSNet5		116.86 59	110.47 61	124.32 60	131.47 64	157.41 67	150.67 66	199.64 57	115.30 64	56.61 69	97.70 66	51.77 63	117.26 61	77.26 54	113.14 62	90.25 68	160.68 64

test1		116.86 59	110.47 61	124.32 60	131.47 64	157.41 67	150.67 66	199.64 57	115.30 64	56.61 69	97.70 66	51.77 63	117.26 61	77.26 54	113.14 62	90.25 68	160.68 64

FMVSNet3		116.86 59	110.47 61	124.32 60	131.47 64	157.41 67	150.67 66	199.64 57	115.30 64	56.61 69	97.70 66	51.77 63	117.26 61	77.26 54	113.14 62	90.25 68	160.68 64

FMVSNet2		116.86 59	110.47 61	124.32 60	131.47 64	157.41 67	150.67 66	199.64 57	115.30 64	56.61 69	97.70 66	51.77 63	117.26 61	77.26 54	113.14 62	90.25 68	160.68 64

FMVSNet1		116.86 59	110.47 61	124.32 60	131.47 64	157.41 67	150.67 66	199.64 57	115.30 64	56.61 69	97.70 66	51.77 63	117.26 61	77.26 54	113.14 62	90.25 68	160.68 64

MIMVSNet1		116.86 59	110.47 61	124.32 60	131.47 64	157.41 67	150.67 66	199.64 57	115.30 64	56.61 69	97.70 66	51.77 63	117.26 61	77.26 54	113.14 62	90.25 68	160.68 64

MIMVSNet		116.86 59	110.47 61	124.32 60	131.47 64	157.41 67	150.67 66	199.64 57	115.30 64	56.61 69	97.70 66	51.77 63	117.26 61	77.26 54	113.14 62	90.25 68	160.68 64

FA-MVS(training)		203.85 71	180.15 71	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 72	197.39 72	137.78 76	239.26 73

SixPastTwentyTwo		210.90 72	189.75 72	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 73	208.00 73	144.02 77	250.52 74

EG-PatchMatch MVS		402.98 74	364.36 74	448.05 76	435.50 79	473.00 84	489.60 83	910.20 84	338.60 78	127.30 78	205.10 75	123.50 80	434.60 77	450.70 79	447.70 77	291.10 80	511.90 77

ADS-MVSNet		452.36 76	406.02 76	506.42 80	534.76 86	628.22 88	552.79 85	1009.99 92	333.98 76	149.26 79	246.67 76	149.01 81	447.03 79	465.35 80	501.18 80	344.69 83	517.75 78

RPSCF		376.53 73	341.80 73	417.05 75	418.60 78	457.01 83	467.46 82	825.25 83	336.12 77	159.32 81	260.40 77	151.13 82	386.94 76	364.25 75	352.10 74	244.72 78	471.62 76

PatchmatchNet		452.63 77	410.20 77	502.13 79	520.70 85	614.40 86	546.00 84	1018.80 93	379.00 80	167.50 82	277.10 78	169.40 84	437.10 78	437.10 77	457.50 78	322.70 82	536.90 79
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
MS-PatchMatch		438.85 75	388.71 75	497.33 77	479.00 80	527.00 85	558.00 86	988.00 85	379.00 80	174.00 83	278.00 79	162.00 83	494.00 81	418.00 76	412.00 75	291.00 79	545.00 80

PMVS	743.55 2	836.66 99	637.90 96	1068.55 109	1306.50 117	875.12 102	1166.70 115	2629.00 113	512.24 91	196.22 85	282.69 80	237.15 92	597.87 86	842.47 102	765.54 101	514.99 99	950.09 100
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
DELS-MVS		458.84 78	423.31 78	500.30 78	511.99 84	616.59 87	578.86 87	991.10 86	355.79 79	158.99 80	319.09 81	190.62 86	453.64 80	437.73 78	439.52 76	307.20 81	603.81 81
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 79	472.40 79	607.16 82	690.38 94	718.85 91	636.03 88	1231.66 95	422.74 82	198.65 86	325.68 82	194.97 87	512.90 83	509.81 82	513.65 81	373.33 85	621.11 82

pmnet_mix02		659.48 93	547.83 87	789.74 97	720.05 95	846.87 101	740.59 92	2153.63 110	456.15 89	191.24 84	336.49 83	200.39 88	511.90 82	608.74 90	634.29 92	421.05 89	751.91 90

IterMVS		554.60 82	488.63 80	631.57 87	636.90 91	700.80 89	674.70 90	1271.10 97	430.50 83	207.10 88	370.50 84	202.70 89	611.80 87	534.20 85	545.30 84	387.80 86	636.40 83
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
IB-MVS	750.90 3	552.99 81	511.38 85	601.53 81	606.02 89	735.75 93	688.75 91	1183.86 94	436.09 84	210.63 89	397.40 85	233.85 91	551.05 84	521.77 83	533.78 83	368.88 84	721.05 89
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
ACMH+	702.88 1	670.82 94	589.81 94	765.33 96	662.52 93	701.42 90	795.24 94	1698.33 106	598.81 101	226.55 90	403.02 86	187.13 85	786.82 98	724.80 100	646.56 93	422.52 90	866.95 98

MVS_Test		654.54 87	583.51 88	737.40 90	721.80 96	822.10 95	808.60 95	1494.00 99	542.20 94	259.90 92	441.60 87	257.70 95	689.10 91	620.80 91	617.70 86	451.00 92	782.50 91

casdiffmvs		654.54 87	583.51 88	737.40 90	721.80 96	822.10 95	808.60 95	1494.00 99	542.20 94	259.90 92	441.60 87	257.70 95	689.10 91	620.80 91	617.70 86	451.00 92	782.50 91

diffmvs		654.54 87	583.51 88	737.40 90	721.80 96	822.10 95	808.60 95	1494.00 99	542.20 94	259.90 92	441.60 87	257.70 95	689.10 91	620.80 91	617.70 86	451.00 92	782.50 91

baseline2		654.54 87	583.51 88	737.40 90	721.80 96	822.10 95	808.60 95	1494.00 99	542.20 94	259.90 92	441.60 87	257.70 95	689.10 91	620.80 91	617.70 86	451.00 92	782.50 91

baseline1		654.54 87	583.51 88	737.40 90	721.80 96	822.10 95	808.60 95	1494.00 99	542.20 94	259.90 92	441.60 87	257.70 95	689.10 91	620.80 91	617.70 86	451.00 92	782.50 91

baseline		654.54 87	583.51 88	737.40 90	721.80 96	822.10 95	808.60 95	1494.00 99	542.20 94	259.90 92	441.60 87	257.70 95	689.10 91	620.80 91	617.70 86	451.00 92	782.50 91

Gipuma		587.77 86	529.57 86	655.67 88	637.00 92	733.00 92	749.00 93	1245.00 96	525.00 92	269.00 98	445.00 93	253.00 93	637.00 89	525.00 84	525.00 82	397.00 87	701.00 88
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
new-patchmatchnet		712.65 95	632.59 95	806.05 100	787.79 102	936.25 105	882.47 102	1795.72 107	528.60 93	244.29 91	471.90 94	257.36 94	681.47 90	705.16 99	659.05 98	444.55 91	869.82 99

tmp_tt				299.50 74	365.00 76	54.00 57	649.00 89	241.00 68	159.00 73	204.00 87	479.00 95	308.00 104	243.00 75	246.00 74	82.00 55	95.00 75

IterMVS-LS		714.97 96	638.00 97	804.77 99	793.60 103	914.20 103	886.50 104	1612.70 105	588.30 100	285.30 99	491.20 96	278.40 102	759.20 97	677.40 98	681.30 99	491.30 98	835.20 97
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
GG-mvs-BLEND		557.53 83	503.49 81	620.58 84	485.90 81	370.41 79	267.30 78	710.53 79	454.42 85	785.72 124	491.23 97	326.12 106	881.92 101	538.27 86	650.05 94	592.08 103	693.94 84

gm-plane-assit		551.84 80	503.49 81	608.24 83	411.90 77	370.41 79	267.30 78	710.53 79	454.42 85	785.72 124	491.23 97	326.12 106	881.92 101	538.27 86	650.05 94	592.08 103	693.94 84

gg-mvs-nofinetune		557.53 83	503.49 81	620.58 84	485.90 81	370.41 79	267.30 78	710.53 79	454.42 85	785.72 124	491.23 97	326.12 106	881.92 101	538.27 86	650.05 94	592.08 103	693.94 84

CR-MVSNet		557.53 83	503.49 81	620.58 84	485.90 81	370.41 79	267.30 78	710.53 79	454.42 85	785.72 124	491.23 97	326.12 106	881.92 101	538.27 86	650.05 94	592.08 103	693.94 84

MSLP-MVS++		993.91 103	732.21 99	1299.24 113	1631.22 120	1345.26 118	1480.05 119	2524.20 112	735.65 103	463.57 114	499.89 101	302.78 103	1292.66 115	675.99 97	612.79 85	403.71 88	953.11 102

FPMVS		1356.65 115	1072.60 113	1688.04 117	1840.79 121	1397.01 119	1793.24 123	4397.86 124	804.66 104	408.78 109	538.65 102	407.36 115	894.84 106	1587.73 118	1286.38 117	792.73 113	1486.39 116

MVSTER		834.63 98	737.03 100	948.49 101	988.86 105	1140.51 116	1129.34 114	1832.80 109	682.42 102	319.01 100	550.98 103	311.35 105	872.51 100	763.95 101	757.83 100	548.41 100	952.20 101

RPMNet		858.01 100	961.99 106	736.69 89	550.05 87	1120.24 114	1212.05 116	463.05 74	485.90 90	550.05 116	580.05 104	890.05 137	559.05 85	1485.90 117	1185.90 115	1085.90 121	985.90 103

CSCG		727.26 97	663.25 98	801.94 98	590.65 88	811.25 94	854.12 101	1805.32 108	816.43 106	388.25 104	612.42 105	345.37 112	621.61 88	507.46 81	471.55 79	551.65 101	1078.31 110

ACMH	935.68 4	948.23 102	857.00 102	1054.67 108	946.00 104	970.00 106	1125.00 113	2467.00 111	823.00 107	330.00 102	622.00 106	211.00 90	891.00 105	970.00 105	1061.00 112	569.00 102	1342.00 112
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMM	1129.18 5	1047.56 109	912.90 103	1204.67 110	1040.21 112	1016.71 113	1105.32 111	2918.67 116	813.91 105	327.22 101	665.34 107	267.72 101	1192.58 114	1091.35 113	991.88 105	643.99 108	1543.40 119
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
TSAR-MVS + GP.		1239.27 112	1094.74 115	1407.89 114	1220.99 116	1845.47 123	1680.98 122	3191.81 117	1098.41 117	362.98 103	679.12 108	339.31 111	1323.06 116	1173.24 116	1093.83 113	667.49 109	1433.78 115

MVS_111021_LR		1055.24 110	916.36 104	1217.27 111	1129.93 115	1268.26 117	1313.88 118	2635.76 114	923.19 108	396.92 108	704.88 109	327.66 110	1136.32 113	965.38 104	946.95 102	690.83 111	1278.20 111

ACMP	1170.86 6	1091.37 111	943.23 105	1264.21 112	1112.10 114	1138.94 115	1276.90 117	2675.36 115	989.62 110	426.15 112	742.77 110	349.09 114	1454.51 119	1047.36 112	969.90 104	640.22 107	1364.94 114
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PatchT		878.42 101	785.05 101	987.36 102	1050.05 113	922.05 104	1111.05 112	677.05 78	950.05 109	1285.90 152	750.05 111	640.05 123	850.05 99	950.05 103	950.05 103	950.05 114	333.05 75

DeepC-MVS_fast	2081.98 8	1311.87 114	1172.50 116	1474.47 115	1411.78 118	1397.23 120	1519.03 120	3401.40 120	1201.29 118	417.90 110	801.95 112	976.25 142	1409.37 117	1114.52 114	1201.12 116	687.33 110	1515.14 118
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ACMMPR		1265.65 113	1083.59 114	1478.06 116	1441.06 119	1438.61 121	1540.68 121	3284.05 119	1219.68 119	458.81 113	803.22 113	346.91 113	1421.66 118	1126.11 115	1150.51 114	722.08 112	1500.09 117

3Dnovator	2220.89 9	2303.77 124	2037.00 126	2615.00 127	2617.00 132	2967.00 133	2616.00 127	5882.00 135	1928.00 130	589.00 117	907.00 114	528.00 119	2443.00 132	2370.00 132	2392.00 133	1543.00 137	3167.00 130

OpenMVS	2049.89 7	1895.92 116	1721.29 117	2099.67 118	2064.00 122	2419.00 126	2138.00 124	4572.00 125	1541.00 124	548.00 115	937.00 115	580.00 120	1983.00 121	1971.00 124	1993.00 122	1293.00 127	2608.00 123

3Dnovator+	3173.67 12	2938.77 135	2519.43 131	3428.00 137	3256.00 140	3708.00 143	3443.00 139	7516.00 142	2525.00 138	1121.00 147	972.00 116	925.00 139	3192.00 139	2899.00 140	2897.00 144	2040.00 148	3710.00 141

CMPMVS	2507.20 10	2083.60 118	1983.13 122	2200.81 120	2582.70 131	3097.30 134	2332.10 125	4364.50 123	1390.00 120	653.68 120	997.75 117	742.65 130	1880.20 120	2298.80 130	2413.60 134	1391.70 131	2941.80 128
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
ambc			999.00 107		999.00 106	999.00 107	999.00 105		999.00 111	999.00 134	999.00 118	999.00 143	999.00 107	999.00 106	999.00 106	999.00 115	999.00 104

EPMVS		999.00 104	999.00 107	999.00 103	999.00 106	999.00 107	999.00 105	999.00 87	999.00 111	999.00 134	999.00 118	999.00 143	999.00 107	999.00 106	999.00 106	999.00 115	999.00 104

uanet_test		1000.00 105	1000.00 109	1000.00 104	1000.00 108	1000.00 109	1000.00 107	1000.00 88	1000.00 113	1000.00 136	1000.00 120	1000.00 145	1000.00 109	1000.00 108	1000.00 108	1000.00 117	1000.00 106

sosnet		1000.00 105	1000.00 109	1000.00 104	1000.00 108	1000.00 109	1000.00 107	1000.00 88	1000.00 113	1000.00 136	1000.00 120	1000.00 145	1000.00 109	1000.00 108	1000.00 108	1000.00 117	1000.00 106

USDC		1000.00 105	1000.00 109	1000.00 104	1000.00 108	1000.00 109	1000.00 107	1000.00 88	1000.00 113	1000.00 136	1000.00 120	1000.00 145	1000.00 109	1000.00 108	1000.00 108	1000.00 117	1000.00 106

TinyColmap		1000.00 105	1000.00 109	1000.00 104	1000.00 108	1000.00 109	1000.00 107	1000.00 88	1000.00 113	1000.00 136	1000.00 120	1000.00 145	1000.00 109	1000.00 108	1000.00 108	1000.00 117	1000.00 106

Vis-MVSNet		2390.77 127	1976.57 121	2874.00 134	2644.00 133	3248.00 137	3040.00 134	7371.00 141	1627.00 125	421.00 111	1200.00 124	622.00 122	2251.00 123	2326.00 131	2052.00 126	1517.00 136	2761.00 127
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
PCF-MVS	3738.24 13	2129.60 119	1746.89 118	2576.10 126	2258.22 127	2263.67 124	2650.06 131	6361.78 137	1676.15 126	695.66 121	1209.77 125	737.88 127	2237.28 122	2083.02 126	1835.31 118	1253.58 126	2422.45 121
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
SD-MVS		2324.36 125	1910.97 120	2806.65 133	2945.31 135	3305.03 139	3267.51 136	5962.25 136	1896.37 129	848.15 129	1224.25 126	661.55 124	2707.30 134	1913.40 120	1871.41 119	1109.38 122	2504.79 122
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
tpm cat1		2652.13 129	2606.66 134	2705.18 129	3151.86 137	6902.39 154	3612.17 141	5463.78 132	1457.76 121	391.31 105	1358.61 127	446.44 116	2360.09 127	2296.48 127	2290.90 129	1251.84 123	3494.04 135

CostFormer		2652.13 129	2606.66 134	2705.18 129	3151.86 137	6902.39 154	3612.17 141	5463.78 132	1457.76 121	391.31 105	1358.61 127	446.44 116	2360.09 127	2296.48 127	2290.90 129	1251.84 123	3494.04 135

tpm		2652.13 129	2606.66 134	2705.18 129	3151.86 137	6902.39 154	3612.17 141	5463.78 132	1457.76 121	391.31 105	1358.61 127	446.44 116	2360.09 127	2296.48 127	2290.90 129	1251.84 123	3494.04 135

MVS-HIRNet		1975.98 117	1797.02 119	2184.76 119	2111.07 123	2443.03 127	2503.43 126	4063.71 121	1684.46 127	711.34 122	1456.05 130	848.70 135	2396.26 130	1900.93 119	1915.01 120	1322.75 128	2330.99 120

DeepPCF-MVS	3033.31 11	2362.79 126	2183.15 128	2572.38 125	2349.28 128	2383.16 125	2740.92 132	5212.97 128	2043.02 131	751.44 123	1466.47 131	1327.42 155	2904.33 135	2573.45 137	2227.77 127	1475.33 132	3260.73 132

DVP-MVS		3258.34 141	2529.80 132	4108.31 145	4005.62 148	4693.14 149	4737.88 152	10195.40 152	2408.38 136	941.44 130	1505.82 132	734.32 126	3438.27 144	2449.15 133	2386.04 132	1331.25 129	3531.75 139
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
SteuartSystems-ACMMP		2615.00 128	2242.57 129	3049.50 135	2828.00 134	2801.00 132	3323.00 138	6648.00 139	2491.00 137	1023.00 143	1605.00 133	697.00 125	2926.00 137	2502.00 134	2279.00 128	1549.00 138	3323.00 134
Skip Steuart: Steuart Systems R&D Blog.
AdaColmap		2288.90 123	2080.73 127	2531.77 124	2485.98 130	2757.87 131	2974.47 133	4914.62 126	2255.54 135	804.63 128	1611.14 134	842.30 134	2657.83 133	2056.92 125	1960.62 121	1353.09 130	3080.73 129

CHOSEN 280x420		2225.10 120	1992.66 123	2496.28 121	2192.10 124	2641.81 128	2621.41 128	5345.34 129	2116.46 132	1002.26 140	1683.84 135	837.43 131	2338.65 124	1920.94 121	2020.28 123	1477.92 133	2727.86 124

CHOSEN 1792x2688		2225.10 120	1992.66 123	2496.28 121	2192.10 124	2641.81 128	2621.41 128	5345.34 129	2116.46 132	1002.26 140	1683.84 135	837.43 131	2338.65 124	1920.94 121	2020.28 123	1477.92 133	2727.86 124

HyFIR lowres test		2225.10 120	1992.66 123	2496.28 121	2192.10 124	2641.81 128	2621.41 128	5345.34 129	2116.46 132	1002.26 140	1683.84 135	837.43 131	2338.65 124	1920.94 121	2020.28 123	1477.92 133	2727.86 124

OMC-MVS		4439.92 147	3906.78 147	5061.92 150	4748.70 153	5679.38 151	5855.03 157	9923.00 150	4023.36 153	1740.95 158	1693.78 138	1693.78 159	4658.45 151	4254.77 150	4135.74 150	3445.36 154	5866.63 151

tpmrst		2688.71 132	2604.46 133	2787.00 132	2472.96 129	3190.36 135	3313.69 137	5003.06 127	1837.26 128	1097.38 146	1721.89 139	1012.20 150	2415.09 131	2970.27 145	2736.80 141	2419.79 151	4762.44 148

TSAR-MVS + ACMM		3184.92 138	2679.45 139	3774.64 144	3302.51 141	4168.07 145	4256.74 148	8947.31 148	2634.53 141	1026.25 144	1723.72 140	1043.87 151	3387.29 142	2794.29 138	2687.41 138	1727.73 145	3704.25 140

MVE	11086.50 18	13278.69 153	12303.57 154	14416.33 155	9890.00 158	17107.00 161	4634.00 151	59884.00 160	3666.00 151	966.00 131	1792.00 141	896.00 138	5680.00 153	20677.00 158	23030.00 157	5444.00 158	18957.00 156
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
MSP-MVS		3241.28 140	2825.26 142	3726.65 143	3945.31 147	4305.03 146	4267.51 150	6962.25 140	2896.37 146	1068.15 145	1824.25 142	1061.55 152	4307.30 149	3013.40 146	3171.41 146	1809.38 147	3504.79 138
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		3539.47 143	2909.05 143	4274.95 147	4528.93 151	4986.51 150	5003.31 154	8985.31 149	2904.53 147	1294.24 154	1839.12 143	1003.69 149	4135.17 147	2926.32 143	2897.04 145	1702.75 144	3806.13 144

DVP-MVS++		3961.71 145	3092.38 145	4975.92 149	4850.81 154	5691.32 152	5760.96 156	12294.80 154	2980.85 148	1135.72 149	1840.86 144	949.63 141	4197.95 148	3019.10 147	2873.21 143	1615.27 140	4291.72 147

DPM-MVS		3051.54 136	2661.57 137	3506.50 138	3532.00 143	3332.00 140	3744.00 144	7839.00 145	2772.00 143	985.00 132	1919.00 145	738.00 128	3319.00 140	2901.00 141	2715.00 139	1620.00 141	4254.00 145

OPM-MVS		3051.54 136	2661.57 137	3506.50 138	3532.00 143	3332.00 140	3744.00 144	7839.00 145	2772.00 143	985.00 132	1919.00 145	738.00 128	3319.00 140	2901.00 141	2715.00 139	1620.00 141	4254.00 145
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
TAPA-MVS	5463.68 16	2764.21 134	2434.28 130	3149.14 136	3645.15 145	3257.60 138	3452.71 140	6526.32 138	2591.85 140	651.36 119	1964.77 147	947.44 140	2924.41 136	2523.36 135	2452.68 135	1694.86 143	3302.28 133
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
MVS_111021_HR		3192.50 139	2773.91 141	3680.86 141	3515.58 142	3815.81 144	4020.82 147	7766.11 143	2775.23 145	1300.96 155	2221.19 148	1117.25 153	3420.01 143	2873.98 139	2835.60 142	2061.69 149	3778.31 143

COLMAP_ROB	3798.28 14	2690.62 133	2704.29 140	2674.67 128	3138.00 136	3522.00 142	3826.00 146	3219.00 118	2702.00 142	1138.00 150	2260.00 149	1212.00 154	2968.00 138	2936.00 144	2571.00 137	1759.00 146	3727.00 142
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
LS3D		7481.83 151	6596.02 152	8515.28 153	9871.71 157	9844.03 159	9225.16 160	18308.40 157	5364.90 154	1267.41 151	2381.61 150	1512.79 156	7225.72 155	8875.69 154	9516.28 153	5193.26 157	8676.83 153

LTVRE_ROB	38377.89 19	49656.08 156	18936.71 156	85495.33 158	306852.00 164	22526.00 163	29206.00 163	112098.00 162	30022.00 159	17348.00 165	2824.00 151	11239.00 165	29457.00 159	20569.00 157	19941.00 156	18011.00 161	25436.00 158
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
PLC	4785.50 15	3275.54 142	3030.86 144	3561.00 140	4093.00 149	4596.00 148	5174.00 155	4267.00 122	3570.00 150	1495.00 156	2940.00 152	1594.00 157	3947.00 146	3817.00 149	3343.00 148	2390.00 150	1356.00 113
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MAR-MVS		3961.62 144	3726.55 146	4235.86 146	4107.62 150	6522.83 153	4862.93 153	7956.64 147	3380.98 149	1665.13 157	3231.54 153	1650.34 158	4357.29 150	3198.61 148	3209.42 147	2465.52 152	4892.15 149
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
TSAR-MVS + COLMAP		6088.23 149	5315.97 150	6989.21 151	6522.51 155	8025.15 157	7938.31 158	15276.20 155	5401.97 155	1914.31 160	3802.65 154	1979.48 160	6704.11 154	5217.07 151	5137.16 151	3579.82 155	7648.29 152

CLD-MVS		6986.85 150	6222.57 151	7878.50 152	7707.00 156	8884.00 158	9025.00 159	15607.00 156	6148.00 156	2571.00 161	4822.00 155	2082.00 162	7875.00 156	6389.00 152	6449.00 152	4486.00 156	8784.00 154
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
DeepC-MVS	5581.15 17	4824.92 148	5020.53 149	4596.70 148	4714.52 152	3205.14 136	3108.50 135	10234.20 153	3823.34 152	1885.23 159	9002.42 156	2045.34 161	4715.23 152	7652.65 153	3993.41 149	2922.51 153	5421.41 150
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ACMMP		9999.00 152	9999.00 153	9999.00 154	9999.00 159	9999.00 160	9999.00 161	9999.00 151	9999.00 157	9999.00 163	9999.00 157	9999.00 164	9999.00 157	9999.00 155	9999.00 154	9999.00 159	9999.00 155
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
CNLPA		17763.08 154	15907.71 155	19927.67 156	19334.00 161	22387.00 162	22896.00 162	38668.00 158	15772.00 158	7632.00 162	13229.00 158	7123.00 163	19334.00 158	15773.00 156	15700.00 155	11702.00 160	21370.00 157

TSAR-MVS + MP.		4216.58 146	4674.68 148	3682.13 142	3752.63 146	4315.48 147	4264.77 149	7782.51 144	2583.81 139	1125.68 148	16722.30 159	882.60 136	3589.10 145	2523.80 136	2486.45 136	1578.08 139	3208.34 131
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
MSDG		31705.85 155	29167.57 157	34667.17 157	44079.00 162	28314.00 164	44778.00 164	43648.00 159	31045.00 160	14849.00 164	26179.00 160	13752.00 166	38088.00 160	30859.00 159	30835.00 158	22561.00 162	43189.00 159

PHI-MVS		99999.00 157	99999.00 158	99999.00 159	99999.00 163	99999.00 165	99999.00 165	99999.00 161	99999.00 161	99999.00 166	99999.00 161	99999.00 167	99999.00 161	99999.00 160	99999.00 159	99999.00 163	99999.00 160

test2506		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

test1111		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

ECVR-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

ET-MVSNet_ETH3D		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

UniMVSNet_ETH3D		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

thisisatest0530		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

Anonymous202405211			10000000.00 159		10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162		10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

DCV-MVSNet		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

tttt0517		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

thisisatest0515		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

DPE-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part1		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

thres100view900		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

tfpnnormal		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

tfpn200view9		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

IterMVS-SCA-FT		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

pmmvs6		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

pmmvs5		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

Anonymous20231211		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

pmmvs-eth3d		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

Anonymous20231206		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

SCA		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

canonicalmvs		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

anonymousdsp		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

FC-MVSNet-train		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

UA-Net		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

FC-MVSNet-test		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

sosnet-low-res		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

DI_MVS_plusplus_trai		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

HPM-MVS++		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

pm-mvs1		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

APDe-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

pmmvs4		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

test-LLR		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

TESTMET0.1,1		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

test-mter		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

testgi		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

test20.03		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

thres600view7		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

MP-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

thres400		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

test123		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

thres200		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

test0.0.03 1		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

pmmvs3		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

EMVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

E-PMN		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

PGM-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

MCST-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

PMMVS2		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

PM-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

LGP-MVS_train		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

EPNet_dtu		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPNet		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

NCCC		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

CP-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

CPTT-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

HQP-MVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

IS_MVSNet		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

Vis-MVSNet (Re-imp)		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

PatchMatch-RL		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

TDRefinement		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

EPP-MVSNet		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

PMMVS		10000000.00 158	10000000.00 159	10000000.00 160	10000000.00 165	10000000.00 166	10000000.00 166	10000000.00 163	10000000.00 162	10000000.00 167	10000000.00 162	10000000.00 168	10000000.00 162	10000000.00 161	10000000.00 160	10000000.00 164	10000000.00 161

APD-MVS		1000000000.00 223	1000000000.00 225	1000000000.00 225	1000000000.00 232	1000000000.00 232	1000000000.00 233	1000000000.00 229	1000000000.00 229	1000000000.00 233	1000000000.00 228	1000000000.00 235	1000000000.00 228	1000000000.00 227	1000000000.00 226	1000000000.00 230	1000000000.00 227
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
RE-MVS-def										610.10 118

9.14												0.00 1

SR-MVS					610.10 90			610.10 77				610.10 121

our_test_3					9999.00 159	99.00 60	99.00 59

MTAPA										41.98 60		28.43 55

MTMP										10000000.00 167		31.71 58

Patchmatch-RL test							10000000.00 166

XVS					52.20 53	52.20 54	52.20 54			52.20 63		52.20 73				52.20 56

X-MVStestdata					52.20 53	52.20 54	52.20 54			52.20 63		52.20 73				52.20 56

mPP-MVS					10000000.00 165							10000000.00 168

NP-MVS									10000000.00 162

Patchmtry						1825.90 122	885.90 103	1405.90 98		1285.90 152

High-resolution multi-view benchmark