+
−
⇧
i
D
T
courtyard (high-res multi-view) - Tolerance 5cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (92.99%)
3Dnovator - completeness (96.86%)
3Dnovator+
3Dnovator+ - accuracy (96.17%)
3Dnovator+ - completeness (95.83%)
ACMH
ACMH - accuracy (95.29%)
ACMH - completeness (86.19%)
ACMH+
ACMH+ - accuracy (95.19%)
ACMH+ - completeness (85.21%)
ACMM
ACMM - accuracy (97.21%)
ACMM - completeness (89.61%)
ACMMP
ACMMP - accuracy (97.20%)
ACMMP - completeness (94.61%)
ACMMPR
ACMMPR - accuracy (97.55%)
ACMMPR - completeness (96.61%)
ACMMP_NAP
ACMMP_NAP - accuracy (97.11%)
ACMMP_NAP - completeness (96.95%)
ACMP
ACMP - accuracy (96.58%)
ACMP - completeness (88.15%)
AdaColmap
AdaColmap - accuracy (95.96%)
AdaColmap - completeness (96.25%)
ADS-MVSNet
ADS-MVSNet - accuracy (81.90%)
ADS-MVSNet - completeness (81.24%)
ambc
ambc - accuracy (98.09%)
ambc - completeness (55.61%)
Anonymous20231206
Anonymous20231206 - accuracy (94.00%)
Anonymous20231206 - completeness (72.09%)
Anonymous202405211
Anonymous202405211 - accuracy (94.51%)
Anonymous202405211 - completeness (85.13%)
anonymousdsp
anonymousdsp - accuracy (88.43%)
anonymousdsp - completeness (71.44%)
APD-MVS
APD-MVS - accuracy (97.30%)
APD-MVS - completeness (97.06%)
APDe-MVS
APDe-MVS - accuracy (96.66%)
APDe-MVS - completeness (97.57%)
baseline1
baseline1 - accuracy (93.07%)
baseline1 - completeness (88.30%)
baseline2
baseline2 - accuracy (92.64%)
baseline2 - completeness (83.22%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (96.45%)
Baseline_NR-MVSNet - completeness (75.95%)
CANet
CANet - accuracy (95.90%)
CANet - completeness (94.13%)
CANet_DTU
CANet_DTU - accuracy (93.12%)
CANet_DTU - completeness (88.88%)
canonicalmvs
canonicalmvs - accuracy (93.94%)
canonicalmvs - completeness (88.94%)
casdiffmvs
casdiffmvs - accuracy (93.25%)
casdiffmvs - completeness (87.25%)
CDPH-MVS
CDPH-MVS - accuracy (96.31%)
CDPH-MVS - completeness (96.04%)
CDS-MVSNet
CDS-MVSNet - accuracy (94.55%)
CDS-MVSNet - completeness (80.94%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (90.33%)
CHOSEN 1792x2688 - completeness (91.97%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (79.60%)
CHOSEN 280x420 - completeness (86.54%)
CLD-MVS
CLD-MVS - accuracy (95.39%)
CLD-MVS - completeness (87.69%)
CMPMVS
CMPMVS - accuracy (84.99%)
CMPMVS - completeness (85.40%)
CNLPA
CNLPA - accuracy (94.62%)
CNLPA - completeness (92.85%)
CNVR-MVS
CNVR-MVS - accuracy (96.56%)
CNVR-MVS - completeness (98.03%)
COLMAP_ROB
COLMAP_ROB - accuracy (95.97%)
COLMAP_ROB - completeness (86.44%)
CostFormer
CostFormer - accuracy (88.92%)
CostFormer - completeness (86.50%)
CP-MVS
CP-MVS - accuracy (97.56%)
CP-MVS - completeness (96.13%)
CP-MVSNet
CP-MVSNet - accuracy (97.06%)
CP-MVSNet - completeness (72.09%)
CPTT-MVS
CPTT-MVS - accuracy (96.84%)
CPTT-MVS - completeness (93.33%)
CR-MVSNet
CR-MVSNet - accuracy (90.36%)
CR-MVSNet - completeness (81.77%)
CS-MVS
CS-MVS - accuracy (95.94%)
CS-MVS - completeness (87.37%)
CSCG
CSCG - accuracy (96.06%)
CSCG - completeness (96.55%)
CVMVSNet
CVMVSNet - accuracy (87.33%)
CVMVSNet - completeness (79.69%)
DCV-MVSNet
DCV-MVSNet - accuracy (94.05%)
DCV-MVSNet - completeness (84.65%)
DeepC-MVS
DeepC-MVS - accuracy (97.57%)
DeepC-MVS - completeness (94.83%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (96.83%)
DeepC-MVS_fast - completeness (97.43%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (94.11%)
DeepPCF-MVS - completeness (95.58%)
DELS-MVS
DELS-MVS - accuracy (92.84%)
DELS-MVS - completeness (94.69%)
diffmvs
diffmvs - accuracy (91.36%)
diffmvs - completeness (85.45%)
DPE-MVS
DPE-MVS - accuracy (95.87%)
DPE-MVS - completeness (97.77%)
DPM-MVS
DPM-MVS - accuracy (95.29%)
DPM-MVS - completeness (95.78%)
dps
dps - accuracy (87.67%)
dps - completeness (84.51%)
DTE-MVSNet
DTE-MVSNet - accuracy (97.40%)
DTE-MVSNet - completeness (72.59%)
DU-MVS
DU-MVS - accuracy (96.45%)
DU-MVS - completeness (75.95%)
DVP-MVS
DVP-MVS - accuracy (96.28%)
DVP-MVS - completeness (97.59%)
E-PMN
E-PMN - accuracy (88.26%)
E-PMN - completeness (36.25%)
Effi-MVS+
Effi-MVS+ - accuracy (94.29%)
Effi-MVS+ - completeness (85.53%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (95.13%)
Effi-MVS+-dtu - completeness (81.38%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (95.89%)
EG-PatchMatch MVS - completeness (77.74%)
EIA-MVS
EIA-MVS - accuracy (96.54%)
EIA-MVS - completeness (86.88%)
EMVS
EMVS - accuracy (87.75%)
EMVS - completeness (36.41%)
EPMVS
EPMVS - accuracy (87.04%)
EPMVS - completeness (86.73%)
EPNet
EPNet - accuracy (97.25%)
EPNet - completeness (95.67%)
EPNet_dtu
EPNet_dtu - accuracy (95.68%)
EPNet_dtu - completeness (92.57%)
EPP-MVSNet
EPP-MVSNet - accuracy (95.15%)
EPP-MVSNet - completeness (86.31%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (92.82%)
ET-MVSNet_ETH3D - completeness (62.90%)
ETV-MVS
ETV-MVS - accuracy (96.36%)
ETV-MVS - completeness (87.28%)
EU-MVSNet
EU-MVSNet - accuracy (88.36%)
EU-MVSNet - completeness (66.17%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (93.81%)
Fast-Effi-MVS+ - completeness (82.84%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (93.35%)
Fast-Effi-MVS+-dtu - completeness (80.35%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (94.97%)
FC-MVSNet-test - completeness (76.92%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (95.21%)
FC-MVSNet-train - completeness (86.55%)
FMVSNet1
FMVSNet1 - accuracy (92.40%)
FMVSNet1 - completeness (74.28%)
FMVSNet2
FMVSNet2 - accuracy (91.22%)
FMVSNet2 - completeness (78.18%)
FMVSNet3
FMVSNet3 - accuracy (89.78%)
FMVSNet3 - completeness (79.49%)
FMVSNet5
FMVSNet5 - accuracy (87.52%)
FMVSNet5 - completeness (67.42%)
FPMVS
FPMVS - accuracy (92.52%)
FPMVS - completeness (70.48%)
GA-MVS
GA-MVS - accuracy (92.32%)
GA-MVS - completeness (79.93%)
GBi-Net
GBi-Net - accuracy (91.22%)
GBi-Net - completeness (78.18%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (0.37%)
GG-mvs-BLEND - completeness (0.16%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (93.07%)
gg-mvs-nofinetune - completeness (83.31%)
Gipuma
Gipuma - accuracy (95.92%)
Gipuma - completeness (43.30%)
gm-plane-assit
gm-plane-assit - accuracy (95.81%)
gm-plane-assit - completeness (76.44%)
HFP-MVS
HFP-MVS - accuracy (97.34%)
HFP-MVS - completeness (97.16%)
HPM-MVS++
HPM-MVS++ - accuracy (97.79%)
HPM-MVS++ - completeness (97.93%)
HQP-MVS
HQP-MVS - accuracy (95.75%)
HQP-MVS - completeness (91.41%)
HyFIR lowres test
HyFIR lowres test - accuracy (91.24%)
HyFIR lowres test - completeness (90.77%)
IB-MVS
IB-MVS - accuracy (92.03%)
IB-MVS - completeness (90.15%)
IS_MVSNet
IS_MVSNet - accuracy (94.91%)
IS_MVSNet - completeness (87.43%)
IterMVS
IterMVS - accuracy (90.83%)
IterMVS - completeness (80.34%)
IterMVS-LS
IterMVS-LS - accuracy (93.18%)
IterMVS-LS - completeness (84.07%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (92.50%)
IterMVS-SCA-FT - completeness (80.15%)
LGP-MVS_train
LGP-MVS_train - accuracy (96.72%)
LGP-MVS_train - completeness (89.26%)
LS3D
LS3D - accuracy (96.47%)
LS3D - completeness (91.91%)
LTVRE_ROB
LTVRE_ROB - accuracy (96.33%)
LTVRE_ROB - completeness (77.47%)
MAR-MVS
MAR-MVS - accuracy (94.29%)
MAR-MVS - completeness (95.51%)
MCST-MVS
MCST-MVS - accuracy (95.30%)
MCST-MVS - completeness (98.31%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (74.25%)
MDA-MVSNet-bldmvs - completeness (52.74%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (88.83%)
MDTV_nov1_ep13 - completeness (82.22%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (91.40%)
MDTV_nov1_ep13_2view - completeness (71.14%)
MIMVSNet
MIMVSNet - accuracy (91.71%)
MIMVSNet - completeness (64.92%)
MIMVSNet1
MIMVSNet1 - accuracy (96.09%)
MIMVSNet1 - completeness (41.96%)
MP-MVS
MP-MVS - accuracy (98.19%)
MP-MVS - completeness (96.59%)
mPP-MVS
mPP-MVS - accuracy (98.24%)
mPP-MVS - completeness (95.90%)
MS-PatchMatch
MS-PatchMatch - accuracy (90.81%)
MS-PatchMatch - completeness (89.89%)
MSDG
MSDG - accuracy (92.55%)
MSDG - completeness (91.78%)
MSLP-MVS++
MSLP-MVS++ - accuracy (95.51%)
MSLP-MVS++ - completeness (96.52%)
MSP-MVS
MSP-MVS - accuracy (96.87%)
MSP-MVS - completeness (96.78%)
MVE
MVE - accuracy (56.34%)
MVE - completeness (15.07%)
MVS-HIRNet
MVS-HIRNet - accuracy (80.33%)
MVS-HIRNet - completeness (75.01%)
MVSTER
MVSTER - accuracy (89.14%)
MVSTER - completeness (88.11%)
MVS_0304
MVS_0304 - accuracy (96.06%)
MVS_0304 - completeness (91.85%)
MVS_111021_LR
MVS_111021_LR - accuracy (93.89%)
MVS_111021_LR - completeness (92.58%)
MVS_Test
MVS_Test - accuracy (92.12%)
MVS_Test - completeness (88.17%)
NCCC
NCCC - accuracy (96.84%)
NCCC - completeness (97.90%)
new-patchmatchnet
new-patchmatchnet - accuracy (93.28%)
new-patchmatchnet - completeness (64.83%)
new_pmnet
new_pmnet - accuracy (82.60%)
new_pmnet - completeness (49.19%)
NR-MVSNet
NR-MVSNet - accuracy (94.26%)
NR-MVSNet - completeness (77.73%)
N_pmnet
N_pmnet - accuracy (91.72%)
N_pmnet - completeness (68.97%)
OMC-MVS
OMC-MVS - accuracy (94.62%)
OMC-MVS - completeness (92.30%)
OpenMVS
OpenMVS - accuracy (92.79%)
OpenMVS - completeness (96.12%)
OPM-MVS
OPM-MVS - accuracy (96.67%)
OPM-MVS - completeness (91.27%)
our_test_3
our_test_3 - accuracy (91.78%)
our_test_3 - completeness (73.80%)
PatchMatch-RL
PatchMatch-RL - accuracy (92.20%)
PatchMatch-RL - completeness (88.53%)
PatchmatchNet
PatchmatchNet - accuracy (89.81%)
PatchmatchNet - completeness (84.08%)
PatchT
PatchT - accuracy (77.92%)
PatchT - completeness (79.02%)
PCF-MVS
PCF-MVS - accuracy (94.66%)
PCF-MVS - completeness (91.51%)
PEN-MVS
PEN-MVS - accuracy (97.20%)
PEN-MVS - completeness (72.67%)
PGM-MVS
PGM-MVS - accuracy (97.53%)
PGM-MVS - completeness (96.53%)
PHI-MVS
PHI-MVS - accuracy (94.95%)
PHI-MVS - completeness (94.97%)
PLC
PLC - accuracy (94.67%)
PLC - completeness (93.77%)
PM-MVS
PM-MVS - accuracy (92.11%)
PM-MVS - completeness (64.79%)
pm-mvs1
pm-mvs1 - accuracy (94.13%)
pm-mvs1 - completeness (77.21%)
PMMVS
PMMVS - accuracy (72.35%)
PMMVS - completeness (85.92%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (92.67%)
pmmvs-eth3d - completeness (66.35%)
PMMVS2
PMMVS2 - accuracy (75.19%)
PMMVS2 - completeness (34.15%)
pmmvs3
pmmvs3 - accuracy (78.33%)
pmmvs3 - completeness (54.53%)
pmmvs5
pmmvs5 - accuracy (89.24%)
pmmvs5 - completeness (75.80%)
pmmvs6
pmmvs6 - accuracy (94.84%)
pmmvs6 - completeness (72.39%)
pmnet_mix02
pmnet_mix02 - accuracy (90.19%)
pmnet_mix02 - completeness (74.16%)
PMVS
PMVS - accuracy (97.00%)
PMVS - completeness (58.40%)
PS-CasMVS
PS-CasMVS - accuracy (97.08%)
PS-CasMVS - completeness (71.86%)
PVSNet_Blended
PVSNet_Blended - accuracy (92.40%)
PVSNet_Blended - completeness (93.03%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (92.40%)
PVSNet_BlendedMVS - completeness (93.03%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (96.31%)
PVSNet_Blended_VisFu - completeness (89.66%)
QAPM
QAPM - accuracy (92.91%)
QAPM - completeness (96.63%)
RPMNet
RPMNet - accuracy (89.79%)
RPMNet - completeness (81.71%)
RPSCF
RPSCF - accuracy (95.72%)
RPSCF - completeness (81.01%)
SCA
SCA - accuracy (89.02%)
SCA - completeness (84.26%)
SD-MVS
SD-MVS - accuracy (96.72%)
SD-MVS - completeness (94.68%)
SED-MVS
SED-MVS - accuracy (96.08%)
SED-MVS - completeness (97.60%)
SF-MVS
SF-MVS - accuracy (95.30%)
SF-MVS - completeness (98.25%)
SMA-MVS
SMA-MVS - accuracy (97.43%)
SMA-MVS - completeness (97.72%)
sosnet
sosnet - accuracy (0.00%)
sosnet - completeness (0.00%)
sosnet-low-res
sosnet-low-res - accuracy (0.00%)
sosnet-low-res - completeness (0.00%)
SR-MVS
SR-MVS - accuracy (97.13%)
SR-MVS - completeness (96.04%)
SteuartSystems-ACMMP
SteuartSystems-ACMMP - accuracy (97.06%)
SteuartSystems-ACMMP - completeness (96.88%)
TAMVS
TAMVS - accuracy (90.57%)
TAMVS - completeness (76.68%)
TAPA-MVS
TAPA-MVS - accuracy (94.14%)
TAPA-MVS - completeness (91.89%)
TDRefinement
TDRefinement - accuracy (95.90%)
TDRefinement - completeness (82.08%)
test-mter
test-mter - accuracy (84.03%)
test-mter - completeness (78.52%)
test1
test1 - accuracy (91.22%)
test1 - completeness (78.18%)
test123
test123 - accuracy (0.62%)
test123 - completeness (0.01%)
testgi
testgi - accuracy (95.63%)
testgi - completeness (75.83%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (81.94%)
TESTMET0.1,1 - completeness (79.81%)
testmvs
testmvs - accuracy (0.83%)
testmvs - completeness (0.05%)
test_part1
test_part1 - accuracy (94.62%)
test_part1 - completeness (83.30%)
thisisatest0515
thisisatest0515 - accuracy (94.14%)
thisisatest0515 - completeness (76.48%)
thisisatest0530
thisisatest0530 - accuracy (93.17%)
thisisatest0530 - completeness (85.53%)
TinyColmap
TinyColmap - accuracy (93.84%)
TinyColmap - completeness (77.94%)
tmp_tt
tmp_tt - accuracy (36.05%)
tmp_tt - completeness (56.31%)
tpm
tpm - accuracy (91.11%)
tpm - completeness (83.19%)
tpm cat1
tpm cat1 - accuracy (89.31%)
tpm cat1 - completeness (85.08%)
tpmrst
tpmrst - accuracy (88.56%)
tpmrst - completeness (86.13%)
train_agg
train_agg - accuracy (97.35%)
train_agg - completeness (96.42%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (96.21%)
TranMVSNet+NR-MVSNet - completeness (76.01%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (94.38%)
TransMVSNet (Re) - completeness (78.32%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (96.07%)
TSAR-MVS + ACMM - completeness (95.69%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (94.62%)
TSAR-MVS + COLMAP - completeness (90.90%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (96.52%)
TSAR-MVS + GP. - completeness (87.81%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (96.87%)
TSAR-MVS + MP. - completeness (94.23%)
tttt0517
tttt0517 - accuracy (93.52%)
tttt0517 - completeness (85.33%)
UA-Net
UA-Net - accuracy (98.99%)
UA-Net - completeness (87.42%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (90.99%)
UGNet - completeness (87.02%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (96.09%)
UniMVSNet (Re) - completeness (76.77%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (97.31%)
UniMVSNet_ETH3D - completeness (76.51%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (95.80%)
UniMVSNet_NR-MVSNet - completeness (76.90%)
USDC
USDC - accuracy (92.93%)
USDC - completeness (80.86%)
Vis-MVSNet
Vis-MVSNet - accuracy (90.91%)
Vis-MVSNet - completeness (84.62%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (94.63%)
Vis-MVSNet (Re-imp) - completeness (86.64%)
WR-MVS_H
WR-MVS_H - accuracy (96.74%)
WR-MVS_H - completeness (72.47%)
X-MVS
X-MVS - accuracy (97.35%)
X-MVS - completeness (96.44%)
X-MVStestdata
X-MVStestdata - accuracy (96.86%)
X-MVStestdata - completeness (89.65%)
XVS
XVS - accuracy (96.86%)
XVS - completeness (89.65%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (95.30%)
xxxxxxxxxxxxxcwj - completeness (98.25%)
zzz-MVS
zzz-MVS - accuracy (98.30%)
zzz-MVS - completeness (96.76%)
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
:
0.00 to 1.00
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
:
0.4
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