+
−
⇧
i
D
T
terrace (high-res multi-view) - Tolerance 5cm
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (96.69%)
3Dnovator - completeness (96.38%)
3Dnovator+
3Dnovator+ - accuracy (97.70%)
3Dnovator+ - completeness (93.72%)
ACMH
ACMH - accuracy (97.72%)
ACMH - completeness (90.57%)
ACMH+
ACMH+ - accuracy (98.56%)
ACMH+ - completeness (88.85%)
ACMM
ACMM - accuracy (98.51%)
ACMM - completeness (90.96%)
ACMMP
ACMMP - accuracy (98.39%)
ACMMP - completeness (93.57%)
ACMMPR
ACMMPR - accuracy (98.26%)
ACMMPR - completeness (93.61%)
ACMMP_NAP
ACMMP_NAP - accuracy (97.40%)
ACMMP_NAP - completeness (93.74%)
ACMP
ACMP - accuracy (98.47%)
ACMP - completeness (91.37%)
AdaColmap
AdaColmap - accuracy (95.95%)
AdaColmap - completeness (93.52%)
ADS-MVSNet
ADS-MVSNet - accuracy (77.53%)
ADS-MVSNet - completeness (91.93%)
ambc
ambc - accuracy (93.45%)
ambc - completeness (74.99%)
Anonymous20231206
Anonymous20231206 - accuracy (89.93%)
Anonymous20231206 - completeness (90.41%)
Anonymous202405211
Anonymous202405211 - accuracy (97.39%)
Anonymous202405211 - completeness (89.69%)
anonymousdsp
anonymousdsp - accuracy (98.70%)
anonymousdsp - completeness (89.59%)
APD-MVS
APD-MVS - accuracy (97.83%)
APD-MVS - completeness (94.83%)
APDe-MVS
APDe-MVS - accuracy (97.87%)
APDe-MVS - completeness (95.52%)
baseline1
baseline1 - accuracy (95.20%)
baseline1 - completeness (96.90%)
baseline2
baseline2 - accuracy (93.21%)
baseline2 - completeness (95.83%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (97.04%)
Baseline_NR-MVSNet - completeness (92.04%)
CANet
CANet - accuracy (95.30%)
CANet - completeness (97.34%)
CANet_DTU
CANet_DTU - accuracy (92.59%)
CANet_DTU - completeness (96.63%)
canonicalmvs
canonicalmvs - accuracy (97.57%)
canonicalmvs - completeness (93.25%)
casdiffmvs
casdiffmvs - accuracy (96.21%)
casdiffmvs - completeness (95.26%)
CDPH-MVS
CDPH-MVS - accuracy (97.12%)
CDPH-MVS - completeness (94.18%)
CDS-MVSNet
CDS-MVSNet - accuracy (94.21%)
CDS-MVSNet - completeness (91.57%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (83.85%)
CHOSEN 1792x2688 - completeness (97.46%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (78.79%)
CHOSEN 280x420 - completeness (93.56%)
CLD-MVS
CLD-MVS - accuracy (95.85%)
CLD-MVS - completeness (95.25%)
CMPMVS
CMPMVS - accuracy (88.84%)
CMPMVS - completeness (84.19%)
CNLPA
CNLPA - accuracy (96.23%)
CNLPA - completeness (92.48%)
CNVR-MVS
CNVR-MVS - accuracy (96.34%)
CNVR-MVS - completeness (95.89%)
COLMAP_ROB
COLMAP_ROB - accuracy (98.77%)
COLMAP_ROB - completeness (86.30%)
CostFormer
CostFormer - accuracy (84.69%)
CostFormer - completeness (93.37%)
CP-MVS
CP-MVS - accuracy (98.23%)
CP-MVS - completeness (93.27%)
CP-MVSNet
CP-MVSNet - accuracy (98.46%)
CP-MVSNet - completeness (90.94%)
CPTT-MVS
CPTT-MVS - accuracy (97.70%)
CPTT-MVS - completeness (90.72%)
CR-MVSNet
CR-MVSNet - accuracy (93.24%)
CR-MVSNet - completeness (91.46%)
CS-MVS
CS-MVS - accuracy (97.41%)
CS-MVS - completeness (95.95%)
CSCG
CSCG - accuracy (98.68%)
CSCG - completeness (92.32%)
CVMVSNet
CVMVSNet - accuracy (91.05%)
CVMVSNet - completeness (87.77%)
DCV-MVSNet
DCV-MVSNet - accuracy (97.99%)
DCV-MVSNet - completeness (89.65%)
DeepC-MVS
DeepC-MVS - accuracy (98.06%)
DeepC-MVS - completeness (93.65%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (96.71%)
DeepC-MVS_fast - completeness (95.00%)
DeepMVS_CX
DeepMVS_CX - accuracy (54.91%)
DeepMVS_CX - completeness (52.37%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (95.82%)
DeepPCF-MVS - completeness (90.15%)
DELS-MVS
DELS-MVS - accuracy (96.01%)
DELS-MVS - completeness (95.55%)
diffmvs
diffmvs - accuracy (93.03%)
diffmvs - completeness (95.10%)
DPE-MVS
DPE-MVS - accuracy (97.96%)
DPE-MVS - completeness (95.79%)
DPM-MVS
DPM-MVS - accuracy (94.91%)
DPM-MVS - completeness (96.01%)
dps
dps - accuracy (85.10%)
dps - completeness (90.63%)
DTE-MVSNet
DTE-MVSNet - accuracy (98.44%)
DTE-MVSNet - completeness (90.73%)
DU-MVS
DU-MVS - accuracy (98.61%)
DU-MVS - completeness (91.22%)
DVP-MVS
DVP-MVS - accuracy (97.51%)
DVP-MVS - completeness (96.30%)
E-PMN
E-PMN - accuracy (75.10%)
E-PMN - completeness (35.34%)
Effi-MVS+
Effi-MVS+ - accuracy (96.22%)
Effi-MVS+ - completeness (93.49%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (97.12%)
Effi-MVS+-dtu - completeness (88.79%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (95.99%)
EG-PatchMatch MVS - completeness (93.15%)
EIA-MVS
EIA-MVS - accuracy (96.89%)
EIA-MVS - completeness (94.40%)
EMVS
EMVS - accuracy (74.83%)
EMVS - completeness (33.51%)
EPMVS
EPMVS - accuracy (80.37%)
EPMVS - completeness (95.15%)
EPNet
EPNet - accuracy (93.41%)
EPNet - completeness (93.96%)
EPNet_dtu
EPNet_dtu - accuracy (87.81%)
EPNet_dtu - completeness (93.71%)
EPP-MVSNet
EPP-MVSNet - accuracy (98.87%)
EPP-MVSNet - completeness (91.68%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (95.22%)
ET-MVSNet_ETH3D - completeness (96.03%)
ETV-MVS
ETV-MVS - accuracy (97.46%)
ETV-MVS - completeness (95.90%)
EU-MVSNet
EU-MVSNet - accuracy (90.61%)
EU-MVSNet - completeness (83.77%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (95.92%)
Fast-Effi-MVS+ - completeness (93.46%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (93.78%)
Fast-Effi-MVS+-dtu - completeness (92.46%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (95.13%)
FC-MVSNet-test - completeness (88.41%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (97.05%)
FC-MVSNet-train - completeness (92.97%)
FMVSNet1
FMVSNet1 - accuracy (97.34%)
FMVSNet1 - completeness (91.77%)
FMVSNet2
FMVSNet2 - accuracy (96.17%)
FMVSNet2 - completeness (94.89%)
FMVSNet3
FMVSNet3 - accuracy (95.12%)
FMVSNet3 - completeness (96.07%)
FMVSNet5
FMVSNet5 - accuracy (88.48%)
FMVSNet5 - completeness (94.06%)
FPMVS
FPMVS - accuracy (94.43%)
FPMVS - completeness (70.02%)
GA-MVS
GA-MVS - accuracy (92.95%)
GA-MVS - completeness (93.13%)
GBi-Net
GBi-Net - accuracy (96.17%)
GBi-Net - completeness (94.89%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (83.55%)
GG-mvs-BLEND - completeness (96.58%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (93.24%)
gg-mvs-nofinetune - completeness (97.55%)
Gipuma
Gipuma - accuracy (97.23%)
Gipuma - completeness (54.81%)
gm-plane-assit
gm-plane-assit - accuracy (92.20%)
gm-plane-assit - completeness (96.54%)
HFP-MVS
HFP-MVS - accuracy (98.19%)
HFP-MVS - completeness (93.66%)
HPM-MVS++
HPM-MVS++ - accuracy (96.73%)
HPM-MVS++ - completeness (94.47%)
HQP-MVS
HQP-MVS - accuracy (96.34%)
HQP-MVS - completeness (92.96%)
HyFIR lowres test
HyFIR lowres test - accuracy (92.14%)
HyFIR lowres test - completeness (95.27%)
IB-MVS
IB-MVS - accuracy (94.84%)
IB-MVS - completeness (95.88%)
IS_MVSNet
IS_MVSNet - accuracy (98.66%)
IS_MVSNet - completeness (91.95%)
IterMVS
IterMVS - accuracy (89.29%)
IterMVS - completeness (92.67%)
IterMVS-LS
IterMVS-LS - accuracy (94.34%)
IterMVS-LS - completeness (93.34%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (92.68%)
IterMVS-SCA-FT - completeness (91.31%)
LGP-MVS_train
LGP-MVS_train - accuracy (98.52%)
LGP-MVS_train - completeness (92.27%)
LS3D
LS3D - accuracy (98.42%)
LS3D - completeness (88.50%)
LTVRE_ROB
LTVRE_ROB - accuracy (98.72%)
LTVRE_ROB - completeness (82.60%)
MAR-MVS
MAR-MVS - accuracy (95.05%)
MAR-MVS - completeness (93.42%)
MCST-MVS
MCST-MVS - accuracy (96.93%)
MCST-MVS - completeness (98.31%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (90.04%)
MDA-MVSNet-bldmvs - completeness (82.85%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (84.56%)
MDTV_nov1_ep13 - completeness (90.36%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (84.56%)
MDTV_nov1_ep13_2view - completeness (90.36%)
MIMVSNet
MIMVSNet - accuracy (89.18%)
MIMVSNet - completeness (94.63%)
MIMVSNet1
MIMVSNet1 - accuracy (92.91%)
MIMVSNet1 - completeness (87.41%)
MP-MVS
MP-MVS - accuracy (98.04%)
MP-MVS - completeness (93.30%)
MS-PatchMatch
MS-PatchMatch - accuracy (90.67%)
MS-PatchMatch - completeness (95.86%)
MSDG
MSDG - accuracy (95.59%)
MSDG - completeness (92.83%)
MSLP-MVS++
MSLP-MVS++ - accuracy (95.49%)
MSLP-MVS++ - completeness (96.51%)
MSP-MVS
MSP-MVS - accuracy (95.77%)
MSP-MVS - completeness (96.98%)
MVE
MVE - accuracy (59.35%)
MVE - completeness (27.56%)
MVS-HIRNet
MVS-HIRNet - accuracy (82.62%)
MVS-HIRNet - completeness (90.07%)
MVSTER
MVSTER - accuracy (94.66%)
MVSTER - completeness (96.73%)
MVS_0304
MVS_0304 - accuracy (96.47%)
MVS_0304 - completeness (96.88%)
MVS_111021_LR
MVS_111021_LR - accuracy (95.85%)
MVS_111021_LR - completeness (93.66%)
MVS_Test
MVS_Test - accuracy (93.79%)
MVS_Test - completeness (96.84%)
NCCC
NCCC - accuracy (96.56%)
NCCC - completeness (95.44%)
new-patchmatchnet
new-patchmatchnet - accuracy (87.99%)
new-patchmatchnet - completeness (85.64%)
new_pmnet
new_pmnet - accuracy (82.37%)
new_pmnet - completeness (77.66%)
NR-MVSNet
NR-MVSNet - accuracy (98.57%)
NR-MVSNet - completeness (91.99%)
N_pmnet
N_pmnet - accuracy (75.03%)
N_pmnet - completeness (86.35%)
OMC-MVS
OMC-MVS - accuracy (97.37%)
OMC-MVS - completeness (92.08%)
OpenMVS
OpenMVS - accuracy (95.86%)
OpenMVS - completeness (95.48%)
OPM-MVS
OPM-MVS - accuracy (97.22%)
OPM-MVS - completeness (93.66%)
PatchMatch-RL
PatchMatch-RL - accuracy (94.41%)
PatchMatch-RL - completeness (89.78%)
PatchmatchNet
PatchmatchNet - accuracy (82.35%)
PatchmatchNet - completeness (93.92%)
PatchT
PatchT - accuracy (86.33%)
PatchT - completeness (96.07%)
PCF-MVS
PCF-MVS - accuracy (96.46%)
PCF-MVS - completeness (93.03%)
PEN-MVS
PEN-MVS - accuracy (98.49%)
PEN-MVS - completeness (90.99%)
PGM-MVS
PGM-MVS - accuracy (98.08%)
PGM-MVS - completeness (93.69%)
PHI-MVS
PHI-MVS - accuracy (97.44%)
PHI-MVS - completeness (95.02%)
PLC
PLC - accuracy (96.67%)
PLC - completeness (92.26%)
PM-MVS
PM-MVS - accuracy (94.34%)
PM-MVS - completeness (86.81%)
pm-mvs1
pm-mvs1 - accuracy (97.25%)
pm-mvs1 - completeness (91.28%)
PMMVS
PMMVS - accuracy (93.88%)
PMMVS - completeness (90.24%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (94.07%)
pmmvs-eth3d - completeness (89.27%)
PMMVS2
PMMVS2 - accuracy (70.93%)
PMMVS2 - completeness (66.88%)
pmmvs3
pmmvs3 - accuracy (86.54%)
pmmvs3 - completeness (81.96%)
pmmvs5
pmmvs5 - accuracy (93.39%)
pmmvs5 - completeness (93.42%)
pmmvs6
pmmvs6 - accuracy (97.72%)
pmmvs6 - completeness (85.83%)
pmnet_mix02
pmnet_mix02 - accuracy (83.91%)
pmnet_mix02 - completeness (89.77%)
PMVS
PMVS - accuracy (98.17%)
PMVS - completeness (63.13%)
PS-CasMVS
PS-CasMVS - accuracy (98.49%)
PS-CasMVS - completeness (90.76%)
PVSNet_Blended
PVSNet_Blended - accuracy (95.28%)
PVSNet_Blended - completeness (96.45%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (95.28%)
PVSNet_BlendedMVS - completeness (96.45%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (96.51%)
PVSNet_Blended_VisFu - completeness (93.84%)
QAPM
QAPM - accuracy (95.41%)
QAPM - completeness (97.26%)
RPMNet
RPMNet - accuracy (93.23%)
RPMNet - completeness (91.55%)
RPSCF
RPSCF - accuracy (98.01%)
RPSCF - completeness (81.14%)
SCA
SCA - accuracy (84.45%)
SCA - completeness (93.25%)
SD-MVS
SD-MVS - accuracy (98.42%)
SD-MVS - completeness (93.35%)
SED-MVS
SED-MVS - accuracy (97.32%)
SED-MVS - completeness (96.49%)
SF-MVS
SF-MVS - accuracy (97.46%)
SF-MVS - completeness (96.62%)
SMA-MVS
SMA-MVS - accuracy (97.73%)
SMA-MVS - completeness (94.10%)
sosnet
sosnet - accuracy (0.00%)
sosnet - completeness (0.00%)
sosnet-low-res
sosnet-low-res - accuracy (0.00%)
sosnet-low-res - completeness (0.00%)
SteuartSystems-ACMMP
SteuartSystems-ACMMP - accuracy (97.97%)
SteuartSystems-ACMMP - completeness (94.51%)
TAMVS
TAMVS - accuracy (87.56%)
TAMVS - completeness (91.07%)
TAPA-MVS
TAPA-MVS - accuracy (97.28%)
TAPA-MVS - completeness (93.39%)
TDRefinement
TDRefinement - accuracy (99.00%)
TDRefinement - completeness (84.83%)
test-mter
test-mter - accuracy (87.79%)
test-mter - completeness (95.26%)
test1
test1 - accuracy (96.17%)
test1 - completeness (94.89%)
test123
test123 - accuracy (1.56%)
test123 - completeness (0.07%)
testgi
testgi - accuracy (87.99%)
testgi - completeness (88.37%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (86.91%)
TESTMET0.1,1 - completeness (96.05%)
testmvs
testmvs - accuracy (1.21%)
testmvs - completeness (0.11%)
test_part1
test_part1 - accuracy (98.97%)
test_part1 - completeness (86.63%)
thisisatest0515
thisisatest0515 - accuracy (97.05%)
thisisatest0515 - completeness (90.87%)
thisisatest0530
thisisatest0530 - accuracy (96.54%)
thisisatest0530 - completeness (93.76%)
TinyColmap
TinyColmap - accuracy (94.65%)
TinyColmap - completeness (88.03%)
tmp_tt
tmp_tt - accuracy (45.36%)
tmp_tt - completeness (65.35%)
tpm
tpm - accuracy (77.49%)
tpm - completeness (92.68%)
tpm cat1
tpm cat1 - accuracy (80.67%)
tpm cat1 - completeness (90.97%)
tpmrst
tpmrst - accuracy (76.38%)
tpmrst - completeness (94.07%)
train_agg
train_agg - accuracy (96.36%)
train_agg - completeness (94.00%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (98.63%)
TranMVSNet+NR-MVSNet - completeness (91.85%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (97.35%)
TransMVSNet (Re) - completeness (91.56%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (95.06%)
TSAR-MVS + ACMM - completeness (92.62%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (94.46%)
TSAR-MVS + COLMAP - completeness (93.01%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (96.47%)
TSAR-MVS + GP. - completeness (97.09%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (98.08%)
TSAR-MVS + MP. - completeness (94.99%)
tttt0517
tttt0517 - accuracy (96.63%)
tttt0517 - completeness (93.63%)
UA-Net
UA-Net - accuracy (98.89%)
UA-Net - completeness (90.96%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (95.32%)
UGNet - completeness (93.48%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (98.73%)
UniMVSNet (Re) - completeness (91.49%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (98.26%)
UniMVSNet_ETH3D - completeness (89.57%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (98.65%)
UniMVSNet_NR-MVSNet - completeness (92.11%)
USDC
USDC - accuracy (94.61%)
USDC - completeness (91.88%)
Vis-MVSNet
Vis-MVSNet - accuracy (96.32%)
Vis-MVSNet - completeness (94.36%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (97.08%)
Vis-MVSNet (Re-imp) - completeness (92.03%)
WR-MVS_H
WR-MVS_H - accuracy (98.38%)
WR-MVS_H - completeness (91.20%)
X-MVS
X-MVS - accuracy (98.19%)
X-MVS - completeness (93.43%)
X-MVStestdata
X-MVStestdata - accuracy (98.17%)
X-MVStestdata - completeness (93.51%)
XVS
XVS - accuracy (98.17%)
XVS - completeness (93.51%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (97.46%)
xxxxxxxxxxxxxcwj - completeness (96.62%)
zzz-MVS
zzz-MVS - accuracy (97.91%)
zzz-MVS - completeness (94.00%)
Attributes:
RGB
RGB and Elevation
Elevation
Level of Detail
RGB
Attribute Weights
RGB:
Intensity:
Elevation:
Classification:
Return Number:
Source ID:
RGB
Gamma:
1.00
Brightness:
0.00
Contrast:
0.00
Elevation
:
0.00 to 1.00
Transition
transition:
Intensity
Range:
0 to 300
Gamma:
1.00
Brightness:
0.00
Contrast:
0.00
:
1,000,000
:
1.00
:
60
:
1.00
Point Sizing
Fixed
Attenuated
Adaptive
Adaptive
Squares
Circles
Interpolation
Squares
Eye-Dome-Lighting
:
1.4
:
1.0
Background
Gradient
Black
White
Navigation
:
0.4
Potree
is a viewer for large point cloud / LIDAR data sets, developed at the Vienna University of Technology.
(github)
Author:
Markus Schütz
License:
FreeBSD (2-clause BSD)
Libraries:
three.js
Jquery
laszip
Plas.io (laslaz)
OpenLayers3
proj4js
tween
i18next
Donators:
rapidlasso
georepublic
sitn
Veesus
sigeom sa
Credits:
Michael Wimmer
&
Claus Scheiblauer
TU Wien, Insitute of Computer Graphics and Algorithms
Harvest4D
rapidlasso
georepublic
Howard Butler, Uday Verma, Connor Manning
Cloud Compare
sitn
loading 1 / 10
Fixed
Attenuated
Adaptive
Squares
Circles
Interpolation
RGB
RGB and Elevation
Elevation
Level of Detail