+
−
⇧
i
D
T
terrace (high-res multi-view) - Tolerance 2cm
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (91.66%)
3Dnovator - completeness (88.61%)
3Dnovator+
3Dnovator+ - accuracy (95.39%)
3Dnovator+ - completeness (85.92%)
ACMH
ACMH - accuracy (93.49%)
ACMH - completeness (79.74%)
ACMH+
ACMH+ - accuracy (95.52%)
ACMH+ - completeness (79.58%)
ACMM
ACMM - accuracy (96.19%)
ACMM - completeness (84.13%)
ACMMP
ACMMP - accuracy (96.35%)
ACMMP - completeness (85.75%)
ACMMPR
ACMMPR - accuracy (95.97%)
ACMMPR - completeness (86.10%)
ACMMP_NAP
ACMMP_NAP - accuracy (94.48%)
ACMMP_NAP - completeness (86.57%)
ACMP
ACMP - accuracy (96.14%)
ACMP - completeness (84.45%)
AdaColmap
AdaColmap - accuracy (91.87%)
AdaColmap - completeness (84.67%)
ADS-MVSNet
ADS-MVSNet - accuracy (52.99%)
ADS-MVSNet - completeness (81.53%)
ambc
ambc - accuracy (85.94%)
ambc - completeness (61.29%)
Anonymous20231206
Anonymous20231206 - accuracy (69.83%)
Anonymous20231206 - completeness (82.10%)
Anonymous202405211
Anonymous202405211 - accuracy (88.92%)
Anonymous202405211 - completeness (83.21%)
anonymousdsp
anonymousdsp - accuracy (96.35%)
anonymousdsp - completeness (79.53%)
APD-MVS
APD-MVS - accuracy (94.47%)
APD-MVS - completeness (86.88%)
APDe-MVS
APDe-MVS - accuracy (94.77%)
APDe-MVS - completeness (87.69%)
baseline1
baseline1 - accuracy (82.05%)
baseline1 - completeness (89.60%)
baseline2
baseline2 - accuracy (84.19%)
baseline2 - completeness (88.89%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (85.83%)
Baseline_NR-MVSNet - completeness (84.92%)
CANet
CANet - accuracy (89.87%)
CANet - completeness (89.50%)
CANet_DTU
CANet_DTU - accuracy (84.67%)
CANet_DTU - completeness (87.57%)
canonicalmvs
canonicalmvs - accuracy (91.17%)
canonicalmvs - completeness (87.32%)
casdiffmvs
casdiffmvs - accuracy (88.59%)
casdiffmvs - completeness (89.08%)
CDPH-MVS
CDPH-MVS - accuracy (93.47%)
CDPH-MVS - completeness (87.23%)
CDS-MVSNet
CDS-MVSNet - accuracy (83.65%)
CDS-MVSNet - completeness (82.70%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (69.63%)
CHOSEN 1792x2688 - completeness (91.90%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (60.61%)
CHOSEN 280x420 - completeness (77.43%)
CLD-MVS
CLD-MVS - accuracy (86.45%)
CLD-MVS - completeness (88.41%)
CMPMVS
CMPMVS - accuracy (75.63%)
CMPMVS - completeness (75.26%)
CNLPA
CNLPA - accuracy (91.96%)
CNLPA - completeness (80.84%)
CNVR-MVS
CNVR-MVS - accuracy (92.17%)
CNVR-MVS - completeness (88.79%)
COLMAP_ROB
COLMAP_ROB - accuracy (96.79%)
COLMAP_ROB - completeness (75.67%)
CostFormer
CostFormer - accuracy (72.59%)
CostFormer - completeness (87.67%)
CP-MVS
CP-MVS - accuracy (95.81%)
CP-MVS - completeness (85.73%)
CP-MVSNet
CP-MVSNet - accuracy (92.85%)
CP-MVSNet - completeness (80.22%)
CPTT-MVS
CPTT-MVS - accuracy (95.28%)
CPTT-MVS - completeness (83.14%)
CR-MVSNet
CR-MVSNet - accuracy (83.61%)
CR-MVSNet - completeness (78.77%)
CS-MVS
CS-MVS - accuracy (92.63%)
CS-MVS - completeness (88.15%)
CSCG
CSCG - accuracy (95.96%)
CSCG - completeness (87.26%)
CVMVSNet
CVMVSNet - accuracy (81.86%)
CVMVSNet - completeness (76.92%)
DCV-MVSNet
DCV-MVSNet - accuracy (90.41%)
DCV-MVSNet - completeness (83.35%)
DeepC-MVS
DeepC-MVS - accuracy (95.69%)
DeepC-MVS - completeness (86.79%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (93.41%)
DeepC-MVS_fast - completeness (88.12%)
DeepMVS_CX
DeepMVS_CX - accuracy (23.59%)
DeepMVS_CX - completeness (21.42%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (92.36%)
DeepPCF-MVS - completeness (83.75%)
DELS-MVS
DELS-MVS - accuracy (89.65%)
DELS-MVS - completeness (89.13%)
diffmvs
diffmvs - accuracy (82.85%)
diffmvs - completeness (87.80%)
DPE-MVS
DPE-MVS - accuracy (94.55%)
DPE-MVS - completeness (87.64%)
DPM-MVS
DPM-MVS - accuracy (90.19%)
DPM-MVS - completeness (89.86%)
dps
dps - accuracy (71.39%)
dps - completeness (82.25%)
DTE-MVSNet
DTE-MVSNet - accuracy (93.18%)
DTE-MVSNet - completeness (80.75%)
DU-MVS
DU-MVS - accuracy (93.20%)
DU-MVS - completeness (83.30%)
DVP-MVS
DVP-MVS - accuracy (93.27%)
DVP-MVS - completeness (88.50%)
E-PMN
E-PMN - accuracy (54.14%)
E-PMN - completeness (24.49%)
Effi-MVS+
Effi-MVS+ - accuracy (91.18%)
Effi-MVS+ - completeness (86.18%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (92.84%)
Effi-MVS+-dtu - completeness (82.47%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (89.59%)
EG-PatchMatch MVS - completeness (84.84%)
EIA-MVS
EIA-MVS - accuracy (91.36%)
EIA-MVS - completeness (87.22%)
EMVS
EMVS - accuracy (53.55%)
EMVS - completeness (22.63%)
EPMVS
EPMVS - accuracy (57.23%)
EPMVS - completeness (88.28%)
EPNet
EPNet - accuracy (86.49%)
EPNet - completeness (87.82%)
EPNet_dtu
EPNet_dtu - accuracy (77.07%)
EPNet_dtu - completeness (85.69%)
EPP-MVSNet
EPP-MVSNet - accuracy (95.76%)
EPP-MVSNet - completeness (83.33%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (89.03%)
ET-MVSNet_ETH3D - completeness (87.30%)
ETV-MVS
ETV-MVS - accuracy (92.33%)
ETV-MVS - completeness (87.63%)
EU-MVSNet
EU-MVSNet - accuracy (82.40%)
EU-MVSNet - completeness (69.78%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (90.05%)
Fast-Effi-MVS+ - completeness (86.43%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (85.86%)
Fast-Effi-MVS+-dtu - completeness (84.84%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (85.06%)
FC-MVSNet-test - completeness (62.99%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (90.03%)
FC-MVSNet-train - completeness (85.92%)
FMVSNet1
FMVSNet1 - accuracy (87.98%)
FMVSNet1 - completeness (84.59%)
FMVSNet2
FMVSNet2 - accuracy (86.04%)
FMVSNet2 - completeness (87.37%)
FMVSNet3
FMVSNet3 - accuracy (84.62%)
FMVSNet3 - completeness (88.64%)
FMVSNet5
FMVSNet5 - accuracy (65.24%)
FMVSNet5 - completeness (84.92%)
FPMVS
FPMVS - accuracy (87.84%)
FPMVS - completeness (58.96%)
GA-MVS
GA-MVS - accuracy (83.97%)
GA-MVS - completeness (86.32%)
GBi-Net
GBi-Net - accuracy (86.04%)
GBi-Net - completeness (87.37%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (60.02%)
GG-mvs-BLEND - completeness (88.65%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (79.81%)
gg-mvs-nofinetune - completeness (90.92%)
Gipuma
Gipuma - accuracy (90.91%)
Gipuma - completeness (39.62%)
gm-plane-assit
gm-plane-assit - accuracy (79.09%)
gm-plane-assit - completeness (90.81%)
HFP-MVS
HFP-MVS - accuracy (95.81%)
HFP-MVS - completeness (86.30%)
HPM-MVS++
HPM-MVS++ - accuracy (93.17%)
HPM-MVS++ - completeness (87.32%)
HQP-MVS
HQP-MVS - accuracy (92.28%)
HQP-MVS - completeness (86.30%)
HyFIR lowres test
HyFIR lowres test - accuracy (81.98%)
HyFIR lowres test - completeness (88.31%)
IB-MVS
IB-MVS - accuracy (87.05%)
IB-MVS - completeness (88.77%)
IS_MVSNet
IS_MVSNet - accuracy (94.82%)
IS_MVSNet - completeness (84.70%)
IterMVS
IterMVS - accuracy (79.45%)
IterMVS - completeness (84.30%)
IterMVS-LS
IterMVS-LS - accuracy (86.15%)
IterMVS-LS - completeness (84.82%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (83.41%)
IterMVS-SCA-FT - completeness (71.63%)
LGP-MVS_train
LGP-MVS_train - accuracy (96.28%)
LGP-MVS_train - completeness (84.80%)
LS3D
LS3D - accuracy (95.86%)
LS3D - completeness (77.97%)
LTVRE_ROB
LTVRE_ROB - accuracy (95.46%)
LTVRE_ROB - completeness (64.73%)
MAR-MVS
MAR-MVS - accuracy (89.52%)
MAR-MVS - completeness (86.95%)
MCST-MVS
MCST-MVS - accuracy (92.58%)
MCST-MVS - completeness (91.63%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (78.75%)
MDA-MVSNet-bldmvs - completeness (74.72%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (71.70%)
MDTV_nov1_ep13 - completeness (84.24%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (71.70%)
MDTV_nov1_ep13_2view - completeness (84.24%)
MIMVSNet
MIMVSNet - accuracy (66.45%)
MIMVSNet - completeness (86.87%)
MIMVSNet1
MIMVSNet1 - accuracy (70.98%)
MIMVSNet1 - completeness (75.46%)
MP-MVS
MP-MVS - accuracy (95.45%)
MP-MVS - completeness (85.87%)
MS-PatchMatch
MS-PatchMatch - accuracy (79.22%)
MS-PatchMatch - completeness (89.56%)
MSDG
MSDG - accuracy (89.97%)
MSDG - completeness (83.47%)
MSLP-MVS++
MSLP-MVS++ - accuracy (89.42%)
MSLP-MVS++ - completeness (88.97%)
MSP-MVS
MSP-MVS - accuracy (91.12%)
MSP-MVS - completeness (88.32%)
MVE
MVE - accuracy (38.85%)
MVE - completeness (16.07%)
MVS-HIRNet
MVS-HIRNet - accuracy (71.17%)
MVS-HIRNet - completeness (83.02%)
MVSTER
MVSTER - accuracy (86.61%)
MVSTER - completeness (88.53%)
MVS_0304
MVS_0304 - accuracy (91.93%)
MVS_0304 - completeness (89.28%)
MVS_111021_LR
MVS_111021_LR - accuracy (90.24%)
MVS_111021_LR - completeness (83.22%)
MVS_Test
MVS_Test - accuracy (85.33%)
MVS_Test - completeness (90.13%)
NCCC
NCCC - accuracy (92.57%)
NCCC - completeness (88.44%)
new-patchmatchnet
new-patchmatchnet - accuracy (57.99%)
new-patchmatchnet - completeness (74.61%)
new_pmnet
new_pmnet - accuracy (54.36%)
new_pmnet - completeness (58.41%)
NR-MVSNet
NR-MVSNet - accuracy (93.16%)
NR-MVSNet - completeness (85.13%)
N_pmnet
N_pmnet - accuracy (46.33%)
N_pmnet - completeness (76.22%)
OMC-MVS
OMC-MVS - accuracy (94.84%)
OMC-MVS - completeness (82.34%)
OpenMVS
OpenMVS - accuracy (88.72%)
OpenMVS - completeness (87.52%)
OPM-MVS
OPM-MVS - accuracy (94.12%)
OPM-MVS - completeness (85.74%)
PatchMatch-RL
PatchMatch-RL - accuracy (86.45%)
PatchMatch-RL - completeness (77.10%)
PatchmatchNet
PatchmatchNet - accuracy (67.33%)
PatchmatchNet - completeness (86.08%)
PatchT
PatchT - accuracy (71.63%)
PatchT - completeness (85.67%)
PCF-MVS
PCF-MVS - accuracy (92.72%)
PCF-MVS - completeness (84.75%)
PEN-MVS
PEN-MVS - accuracy (93.05%)
PEN-MVS - completeness (81.44%)
PGM-MVS
PGM-MVS - accuracy (95.79%)
PGM-MVS - completeness (86.18%)
PHI-MVS
PHI-MVS - accuracy (92.58%)
PHI-MVS - completeness (86.14%)
PLC
PLC - accuracy (93.37%)
PLC - completeness (81.66%)
PM-MVS
PM-MVS - accuracy (85.83%)
PM-MVS - completeness (72.90%)
pm-mvs1
pm-mvs1 - accuracy (86.64%)
pm-mvs1 - completeness (83.13%)
PMMVS
PMMVS - accuracy (83.42%)
PMMVS - completeness (81.96%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (85.58%)
pmmvs-eth3d - completeness (81.14%)
PMMVS2
PMMVS2 - accuracy (34.87%)
PMMVS2 - completeness (41.17%)
pmmvs3
pmmvs3 - accuracy (73.47%)
pmmvs3 - completeness (72.80%)
pmmvs5
pmmvs5 - accuracy (81.30%)
pmmvs5 - completeness (85.72%)
pmmvs6
pmmvs6 - accuracy (87.36%)
pmmvs6 - completeness (79.47%)
pmnet_mix02
pmnet_mix02 - accuracy (58.27%)
pmnet_mix02 - completeness (82.19%)
PMVS
PMVS - accuracy (94.94%)
PMVS - completeness (54.02%)
PS-CasMVS
PS-CasMVS - accuracy (92.88%)
PS-CasMVS - completeness (80.01%)
PVSNet_Blended
PVSNet_Blended - accuracy (87.61%)
PVSNet_Blended - completeness (88.18%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (87.61%)
PVSNet_BlendedMVS - completeness (88.18%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (91.41%)
PVSNet_Blended_VisFu - completeness (86.53%)
QAPM
QAPM - accuracy (88.29%)
QAPM - completeness (89.46%)
RPMNet
RPMNet - accuracy (83.64%)
RPMNet - completeness (78.65%)
RPSCF
RPSCF - accuracy (94.15%)
RPSCF - completeness (66.01%)
SCA
SCA - accuracy (71.30%)
SCA - completeness (83.71%)
SD-MVS
SD-MVS - accuracy (96.54%)
SD-MVS - completeness (85.48%)
SED-MVS
SED-MVS - accuracy (93.46%)
SED-MVS - completeness (88.67%)
SF-MVS
SF-MVS - accuracy (93.95%)
SF-MVS - completeness (88.75%)
SMA-MVS
SMA-MVS - accuracy (94.77%)
SMA-MVS - completeness (87.23%)
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 (94.72%)
SteuartSystems-ACMMP - completeness (87.82%)
TAMVS
TAMVS - accuracy (68.70%)
TAMVS - completeness (81.86%)
TAPA-MVS
TAPA-MVS - accuracy (94.00%)
TAPA-MVS - completeness (82.37%)
TDRefinement
TDRefinement - accuracy (97.33%)
TDRefinement - completeness (74.01%)
test-mter
test-mter - accuracy (75.38%)
test-mter - completeness (87.22%)
test1
test1 - accuracy (86.04%)
test1 - completeness (87.37%)
test123
test123 - accuracy (0.46%)
test123 - completeness (0.00%)
testgi
testgi - accuracy (69.14%)
testgi - completeness (78.67%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (73.59%)
TESTMET0.1,1 - completeness (88.61%)
testmvs
testmvs - accuracy (0.48%)
testmvs - completeness (0.01%)
test_part1
test_part1 - accuracy (94.98%)
test_part1 - completeness (82.59%)
thisisatest0515
thisisatest0515 - accuracy (92.53%)
thisisatest0515 - completeness (81.02%)
thisisatest0530
thisisatest0530 - accuracy (91.30%)
thisisatest0530 - completeness (84.60%)
TinyColmap
TinyColmap - accuracy (89.20%)
TinyColmap - completeness (74.91%)
tmp_tt
tmp_tt - accuracy (22.54%)
tmp_tt - completeness (32.33%)
tpm
tpm - accuracy (59.70%)
tpm - completeness (86.54%)
tpm cat1
tpm cat1 - accuracy (67.33%)
tpm cat1 - completeness (83.22%)
tpmrst
tpmrst - accuracy (59.43%)
tpmrst - completeness (87.72%)
train_agg
train_agg - accuracy (92.51%)
train_agg - completeness (87.21%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (93.26%)
TranMVSNet+NR-MVSNet - completeness (84.91%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (86.65%)
TransMVSNet (Re) - completeness (84.37%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (91.32%)
TSAR-MVS + ACMM - completeness (83.93%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (89.63%)
TSAR-MVS + COLMAP - completeness (82.67%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (91.45%)
TSAR-MVS + GP. - completeness (88.15%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (94.87%)
TSAR-MVS + MP. - completeness (86.68%)
tttt0517
tttt0517 - accuracy (91.54%)
tttt0517 - completeness (84.24%)
UA-Net
UA-Net - accuracy (96.66%)
UA-Net - completeness (80.83%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (88.28%)
UGNet - completeness (84.24%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (93.97%)
UniMVSNet (Re) - completeness (83.76%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (89.47%)
UniMVSNet_ETH3D - completeness (81.73%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (93.78%)
UniMVSNet_NR-MVSNet - completeness (85.30%)
USDC
USDC - accuracy (89.00%)
USDC - completeness (79.99%)
Vis-MVSNet
Vis-MVSNet - accuracy (89.48%)
Vis-MVSNet - completeness (84.47%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (89.12%)
Vis-MVSNet (Re-imp) - completeness (82.49%)
WR-MVS_H
WR-MVS_H - accuracy (93.07%)
WR-MVS_H - completeness (81.06%)
X-MVS
X-MVS - accuracy (95.85%)
X-MVS - completeness (85.66%)
X-MVStestdata
X-MVStestdata - accuracy (95.84%)
X-MVStestdata - completeness (85.67%)
XVS
XVS - accuracy (95.84%)
XVS - completeness (85.67%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (93.95%)
xxxxxxxxxxxxxcwj - completeness (88.75%)
zzz-MVS
zzz-MVS - accuracy (95.14%)
zzz-MVS - completeness (86.01%)
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