+
−
⇧
i
D
T
delivery_area (high-res multi-view) - Tolerance 5cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (95.03%)
3Dnovator - completeness (96.46%)
3Dnovator+
3Dnovator+ - accuracy (96.55%)
3Dnovator+ - completeness (96.45%)
ACMH
ACMH - accuracy (96.94%)
ACMH - completeness (86.14%)
ACMH+
ACMH+ - accuracy (97.18%)
ACMH+ - completeness (84.89%)
ACMM
ACMM - accuracy (97.16%)
ACMM - completeness (87.71%)
ACMMP
ACMMP - accuracy (97.60%)
ACMMP - completeness (95.53%)
ACMMPR
ACMMPR - accuracy (97.63%)
ACMMPR - completeness (96.25%)
ACMMP_NAP
ACMMP_NAP - accuracy (97.26%)
ACMMP_NAP - completeness (97.36%)
ACMP
ACMP - accuracy (97.23%)
ACMP - completeness (90.95%)
AdaColmap
AdaColmap - accuracy (95.02%)
AdaColmap - completeness (95.35%)
ADS-MVSNet
ADS-MVSNet - accuracy (75.59%)
ADS-MVSNet - completeness (86.59%)
ambc
ambc - accuracy (95.14%)
ambc - completeness (59.93%)
Anonymous20231206
Anonymous20231206 - accuracy (87.73%)
Anonymous20231206 - completeness (77.84%)
Anonymous202405211
Anonymous202405211 - accuracy (94.96%)
Anonymous202405211 - completeness (91.06%)
anonymousdsp
anonymousdsp - accuracy (92.05%)
anonymousdsp - completeness (83.97%)
APD-MVS
APD-MVS - accuracy (96.90%)
APD-MVS - completeness (97.09%)
APDe-MVS
APDe-MVS - accuracy (97.56%)
APDe-MVS - completeness (98.06%)
baseline1
baseline1 - accuracy (90.44%)
baseline1 - completeness (91.89%)
baseline2
baseline2 - accuracy (88.41%)
baseline2 - completeness (92.71%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (93.86%)
Baseline_NR-MVSNet - completeness (80.49%)
CANet
CANet - accuracy (95.41%)
CANet - completeness (98.05%)
CANet_DTU
CANet_DTU - accuracy (91.22%)
CANet_DTU - completeness (94.87%)
canonicalmvs
canonicalmvs - accuracy (96.41%)
canonicalmvs - completeness (95.44%)
casdiffmvs
casdiffmvs - accuracy (93.82%)
casdiffmvs - completeness (94.62%)
CDPH-MVS
CDPH-MVS - accuracy (95.84%)
CDPH-MVS - completeness (96.53%)
CDS-MVSNet
CDS-MVSNet - accuracy (90.82%)
CDS-MVSNet - completeness (89.75%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (87.86%)
CHOSEN 1792x2688 - completeness (96.56%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (68.80%)
CHOSEN 280x420 - completeness (93.42%)
CLD-MVS
CLD-MVS - accuracy (95.31%)
CLD-MVS - completeness (93.16%)
CMPMVS
CMPMVS - accuracy (81.97%)
CMPMVS - completeness (89.72%)
CNLPA
CNLPA - accuracy (94.73%)
CNLPA - completeness (93.83%)
CNVR-MVS
CNVR-MVS - accuracy (95.67%)
CNVR-MVS - completeness (98.59%)
COLMAP_ROB
COLMAP_ROB - accuracy (97.78%)
COLMAP_ROB - completeness (82.76%)
CostFormer
CostFormer - accuracy (85.70%)
CostFormer - completeness (91.65%)
CP-MVS
CP-MVS - accuracy (97.13%)
CP-MVS - completeness (95.90%)
CP-MVSNet
CP-MVSNet - accuracy (97.82%)
CP-MVSNet - completeness (81.04%)
CPTT-MVS
CPTT-MVS - accuracy (96.78%)
CPTT-MVS - completeness (93.75%)
CR-MVSNet
CR-MVSNet - accuracy (84.79%)
CR-MVSNet - completeness (85.52%)
CS-MVS
CS-MVS - accuracy (94.95%)
CS-MVS - completeness (95.52%)
CSCG
CSCG - accuracy (97.58%)
CSCG - completeness (97.90%)
CVMVSNet
CVMVSNet - accuracy (85.22%)
CVMVSNet - completeness (83.75%)
DCV-MVSNet
DCV-MVSNet - accuracy (95.92%)
DCV-MVSNet - completeness (84.51%)
DeepC-MVS
DeepC-MVS - accuracy (97.19%)
DeepC-MVS - completeness (96.56%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (96.12%)
DeepC-MVS_fast - completeness (96.92%)
DeepMVS_CX
DeepMVS_CX - accuracy (47.68%)
DeepMVS_CX - completeness (48.96%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (95.71%)
DeepPCF-MVS - completeness (98.17%)
DELS-MVS
DELS-MVS - accuracy (95.13%)
DELS-MVS - completeness (97.34%)
diffmvs
diffmvs - accuracy (91.38%)
diffmvs - completeness (93.92%)
DPE-MVS
DPE-MVS - accuracy (97.47%)
DPE-MVS - completeness (98.64%)
DPM-MVS
DPM-MVS - accuracy (94.16%)
DPM-MVS - completeness (97.40%)
dps
dps - accuracy (85.17%)
dps - completeness (88.12%)
DTE-MVSNet
DTE-MVSNet - accuracy (97.95%)
DTE-MVSNet - completeness (78.56%)
DU-MVS
DU-MVS - accuracy (96.44%)
DU-MVS - completeness (86.02%)
DVP-MVS
DVP-MVS - accuracy (97.49%)
DVP-MVS - completeness (98.89%)
E-PMN
E-PMN - accuracy (70.48%)
E-PMN - completeness (19.02%)
Effi-MVS+
Effi-MVS+ - accuracy (93.53%)
Effi-MVS+ - completeness (93.31%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (94.73%)
Effi-MVS+-dtu - completeness (86.74%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (94.62%)
EG-PatchMatch MVS - completeness (86.20%)
EIA-MVS
EIA-MVS - accuracy (94.65%)
EIA-MVS - completeness (95.36%)
EMVS
EMVS - accuracy (71.02%)
EMVS - completeness (18.93%)
EPMVS
EPMVS - accuracy (78.86%)
EPMVS - completeness (91.98%)
EPNet
EPNet - accuracy (90.62%)
EPNet - completeness (96.81%)
EPNet_dtu
EPNet_dtu - accuracy (83.37%)
EPNet_dtu - completeness (88.74%)
EPP-MVSNet
EPP-MVSNet - accuracy (96.54%)
EPP-MVSNet - completeness (92.37%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (90.68%)
ET-MVSNet_ETH3D - completeness (94.66%)
ETV-MVS
ETV-MVS - accuracy (93.63%)
ETV-MVS - completeness (95.61%)
EU-MVSNet
EU-MVSNet - accuracy (87.89%)
EU-MVSNet - completeness (72.39%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (93.88%)
Fast-Effi-MVS+ - completeness (89.94%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (91.57%)
Fast-Effi-MVS+-dtu - completeness (86.83%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (90.53%)
FC-MVSNet-test - completeness (81.41%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (94.82%)
FC-MVSNet-train - completeness (88.63%)
FMVSNet1
FMVSNet1 - accuracy (95.16%)
FMVSNet1 - completeness (83.94%)
FMVSNet2
FMVSNet2 - accuracy (94.05%)
FMVSNet2 - completeness (86.19%)
FMVSNet3
FMVSNet3 - accuracy (93.46%)
FMVSNet3 - completeness (87.02%)
FMVSNet5
FMVSNet5 - accuracy (86.78%)
FMVSNet5 - completeness (76.28%)
FPMVS
FPMVS - accuracy (88.18%)
FPMVS - completeness (60.12%)
GA-MVS
GA-MVS - accuracy (91.46%)
GA-MVS - completeness (89.29%)
GBi-Net
GBi-Net - accuracy (94.05%)
GBi-Net - completeness (86.19%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (83.31%)
GG-mvs-BLEND - completeness (98.10%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (89.37%)
gg-mvs-nofinetune - completeness (95.22%)
Gipuma
Gipuma - accuracy (94.59%)
Gipuma - completeness (32.51%)
gm-plane-assit
gm-plane-assit - accuracy (92.29%)
gm-plane-assit - completeness (68.29%)
HFP-MVS
HFP-MVS - accuracy (97.26%)
HFP-MVS - completeness (96.46%)
HPM-MVS++
HPM-MVS++ - accuracy (95.39%)
HPM-MVS++ - completeness (97.71%)
HQP-MVS
HQP-MVS - accuracy (95.01%)
HQP-MVS - completeness (92.37%)
HyFIR lowres test
HyFIR lowres test - accuracy (92.17%)
HyFIR lowres test - completeness (94.64%)
IB-MVS
IB-MVS - accuracy (91.77%)
IB-MVS - completeness (95.39%)
IS_MVSNet
IS_MVSNet - accuracy (95.56%)
IS_MVSNet - completeness (93.90%)
IterMVS
IterMVS - accuracy (91.24%)
IterMVS - completeness (81.17%)
IterMVS-LS
IterMVS-LS - accuracy (93.66%)
IterMVS-LS - completeness (84.11%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (92.11%)
IterMVS-SCA-FT - completeness (81.11%)
LGP-MVS_train
LGP-MVS_train - accuracy (97.35%)
LGP-MVS_train - completeness (90.23%)
LS3D
LS3D - accuracy (97.49%)
LS3D - completeness (89.39%)
LTVRE_ROB
LTVRE_ROB - accuracy (96.94%)
LTVRE_ROB - completeness (82.64%)
MAR-MVS
MAR-MVS - accuracy (94.24%)
MAR-MVS - completeness (95.89%)
MCST-MVS
MCST-MVS - accuracy (95.40%)
MCST-MVS - completeness (98.34%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (90.88%)
MDA-MVSNet-bldmvs - completeness (74.87%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (83.88%)
MDTV_nov1_ep13 - completeness (90.14%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (86.75%)
MDTV_nov1_ep13_2view - completeness (81.94%)
MIMVSNet
MIMVSNet - accuracy (85.95%)
MIMVSNet - completeness (84.68%)
MIMVSNet1
MIMVSNet1 - accuracy (91.99%)
MIMVSNet1 - completeness (70.79%)
MP-MVS
MP-MVS - accuracy (97.31%)
MP-MVS - completeness (96.33%)
MS-PatchMatch
MS-PatchMatch - accuracy (88.18%)
MS-PatchMatch - completeness (90.42%)
MSDG
MSDG - accuracy (92.97%)
MSDG - completeness (86.83%)
MSLP-MVS++
MSLP-MVS++ - accuracy (95.83%)
MSLP-MVS++ - completeness (95.93%)
MSP-MVS
MSP-MVS - accuracy (97.77%)
MSP-MVS - completeness (98.11%)
MVE
MVE - accuracy (57.24%)
MVE - completeness (29.77%)
MVS-HIRNet
MVS-HIRNet - accuracy (69.38%)
MVS-HIRNet - completeness (82.84%)
MVSTER
MVSTER - accuracy (89.80%)
MVSTER - completeness (90.05%)
MVS_0304
MVS_0304 - accuracy (96.00%)
MVS_0304 - completeness (97.60%)
MVS_111021_LR
MVS_111021_LR - accuracy (92.28%)
MVS_111021_LR - completeness (95.89%)
MVS_Test
MVS_Test - accuracy (91.74%)
MVS_Test - completeness (95.27%)
NCCC
NCCC - accuracy (95.42%)
NCCC - completeness (97.93%)
new-patchmatchnet
new-patchmatchnet - accuracy (81.87%)
new-patchmatchnet - completeness (70.90%)
new_pmnet
new_pmnet - accuracy (72.08%)
new_pmnet - completeness (64.89%)
NR-MVSNet
NR-MVSNet - accuracy (96.44%)
NR-MVSNet - completeness (86.02%)
N_pmnet
N_pmnet - accuracy (73.72%)
N_pmnet - completeness (75.61%)
OMC-MVS
OMC-MVS - accuracy (96.26%)
OMC-MVS - completeness (94.35%)
OpenMVS
OpenMVS - accuracy (93.61%)
OpenMVS - completeness (96.55%)
OPM-MVS
OPM-MVS - accuracy (96.52%)
OPM-MVS - completeness (91.78%)
our_test_3
our_test_3 - accuracy (88.87%)
our_test_3 - completeness (79.57%)
PatchMatch-RL
PatchMatch-RL - accuracy (88.00%)
PatchMatch-RL - completeness (91.10%)
PatchmatchNet
PatchmatchNet - accuracy (81.55%)
PatchmatchNet - completeness (91.04%)
Patchmtry
Patchmtry - accuracy (83.74%)
Patchmtry - completeness (87.41%)
PatchT
PatchT - accuracy (82.58%)
PatchT - completeness (86.09%)
PCF-MVS
PCF-MVS - accuracy (95.80%)
PCF-MVS - completeness (96.23%)
PEN-MVS
PEN-MVS - accuracy (97.97%)
PEN-MVS - completeness (79.83%)
PGM-MVS
PGM-MVS - accuracy (97.45%)
PGM-MVS - completeness (95.90%)
PHI-MVS
PHI-MVS - accuracy (96.55%)
PHI-MVS - completeness (97.57%)
PLC
PLC - accuracy (95.03%)
PLC - completeness (90.35%)
PM-MVS
PM-MVS - accuracy (90.16%)
PM-MVS - completeness (76.08%)
pm-mvs1
pm-mvs1 - accuracy (93.66%)
pm-mvs1 - completeness (85.32%)
PMMVS
PMMVS - accuracy (75.05%)
PMMVS - completeness (91.92%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (90.67%)
pmmvs-eth3d - completeness (76.04%)
PMMVS2
PMMVS2 - accuracy (63.08%)
PMMVS2 - completeness (44.70%)
pmmvs3
pmmvs3 - accuracy (78.57%)
pmmvs3 - completeness (64.49%)
pmmvs5
pmmvs5 - accuracy (90.64%)
pmmvs5 - completeness (86.26%)
pmmvs6
pmmvs6 - accuracy (94.61%)
pmmvs6 - completeness (81.39%)
pmnet_mix02
pmnet_mix02 - accuracy (81.10%)
pmnet_mix02 - completeness (80.17%)
PMVS
PMVS - accuracy (96.02%)
PMVS - completeness (33.20%)
PS-CasMVS
PS-CasMVS - accuracy (97.92%)
PS-CasMVS - completeness (80.67%)
PVSNet_Blended
PVSNet_Blended - accuracy (92.74%)
PVSNet_Blended - completeness (96.98%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (92.74%)
PVSNet_BlendedMVS - completeness (96.98%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (95.65%)
PVSNet_Blended_VisFu - completeness (95.15%)
QAPM
QAPM - accuracy (94.82%)
QAPM - completeness (97.09%)
RPMNet
RPMNet - accuracy (84.79%)
RPMNet - completeness (85.52%)
RPSCF
RPSCF - accuracy (95.94%)
RPSCF - completeness (80.18%)
SCA
SCA - accuracy (90.31%)
SCA - completeness (85.24%)
SD-MVS
SD-MVS - accuracy (96.19%)
SD-MVS - completeness (97.89%)
SED-MVS
SED-MVS - accuracy (97.39%)
SED-MVS - completeness (98.92%)
SF-MVS
SF-MVS - accuracy (95.93%)
SF-MVS - completeness (98.24%)
SMA-MVS
SMA-MVS - accuracy (97.36%)
SMA-MVS - completeness (97.77%)
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 (97.36%)
SteuartSystems-ACMMP - completeness (97.36%)
TAMVS
TAMVS - accuracy (83.12%)
TAMVS - completeness (88.12%)
TAPA-MVS
TAPA-MVS - accuracy (95.99%)
TAPA-MVS - completeness (93.73%)
TDRefinement
TDRefinement - accuracy (98.10%)
TDRefinement - completeness (81.45%)
test-mter
test-mter - accuracy (76.58%)
test-mter - completeness (90.24%)
test1
test1 - accuracy (94.05%)
test1 - completeness (86.19%)
test123
test123 - accuracy (1.18%)
test123 - completeness (0.14%)
testgi
testgi - accuracy (88.18%)
testgi - completeness (78.51%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (75.11%)
TESTMET0.1,1 - completeness (91.26%)
testmvs
testmvs - accuracy (0.96%)
testmvs - completeness (0.21%)
test_part1
test_part1 - accuracy (97.75%)
test_part1 - completeness (84.45%)
thisisatest0515
thisisatest0515 - accuracy (92.50%)
thisisatest0515 - completeness (85.59%)
thisisatest0530
thisisatest0530 - accuracy (91.31%)
thisisatest0530 - completeness (93.88%)
TinyColmap
TinyColmap - accuracy (92.76%)
TinyColmap - completeness (79.54%)
tmp_tt
tmp_tt - accuracy (15.86%)
tmp_tt - completeness (31.71%)
tpm
tpm - accuracy (79.50%)
tpm - completeness (86.84%)
tpm cat1
tpm cat1 - accuracy (83.26%)
tpm cat1 - completeness (88.58%)
tpmrst
tpmrst - accuracy (77.45%)
tpmrst - completeness (89.53%)
train_agg
train_agg - accuracy (93.78%)
train_agg - completeness (97.03%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (96.77%)
TranMVSNet+NR-MVSNet - completeness (84.80%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (94.05%)
TransMVSNet (Re) - completeness (81.35%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (96.46%)
TSAR-MVS + ACMM - completeness (96.73%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (94.28%)
TSAR-MVS + COLMAP - completeness (93.57%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (95.80%)
TSAR-MVS + GP. - completeness (96.21%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (96.50%)
TSAR-MVS + MP. - completeness (97.54%)
tttt0517
tttt0517 - accuracy (91.65%)
tttt0517 - completeness (93.74%)
UA-Net
UA-Net - accuracy (97.90%)
UA-Net - completeness (92.48%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (95.53%)
UGNet - completeness (92.71%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (96.60%)
UniMVSNet (Re) - completeness (87.38%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (96.71%)
UniMVSNet_ETH3D - completeness (85.88%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (96.55%)
UniMVSNet_NR-MVSNet - completeness (86.58%)
USDC
USDC - accuracy (92.22%)
USDC - completeness (86.21%)
Vis-MVSNet
Vis-MVSNet - accuracy (95.88%)
Vis-MVSNet - completeness (93.92%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (92.75%)
Vis-MVSNet (Re-imp) - completeness (92.68%)
WR-MVS_H
WR-MVS_H - accuracy (98.04%)
WR-MVS_H - completeness (82.33%)
X-MVS
X-MVS - accuracy (97.48%)
X-MVS - completeness (95.93%)
X-MVStestdata
X-MVStestdata - accuracy (97.48%)
X-MVStestdata - completeness (95.93%)
XVS
XVS - accuracy (97.48%)
XVS - completeness (95.93%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (95.93%)
xxxxxxxxxxxxxcwj - completeness (98.24%)
zzz-MVS
zzz-MVS - accuracy (96.18%)
zzz-MVS - completeness (96.68%)
Materials
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
Elevation range
:
-24.89 to 52.19
Transition
transition:
Intensity
Range:
0 to 300
Gamma:
1.00
Brightness:
0.00
Contrast:
0.00
Appearance
Point budget
:
1,000,000
Point size
:
1.00
Field of view
:
60
Opacity
:
1.00
Point sizing
Fixed
Attenuated
Adaptive
Adaptive
Quality
Squares
Circles
Interpolation
Squares
Eye-Dome-Lighting
Enable
Radius
:
1.4
Strength
:
1.0
Background
Gradient
Black
White
Tools
Navigation
Speed
:
53.4
Measurements
About this viewer
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