+
−
⇧
i
D
T
electro (high-res multi-view) - Tolerance 5cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (95.76%)
3Dnovator - completeness (91.97%)
3Dnovator+
3Dnovator+ - accuracy (97.64%)
3Dnovator+ - completeness (91.94%)
ACMH
ACMH - accuracy (98.43%)
ACMH - completeness (75.76%)
ACMH+
ACMH+ - accuracy (97.97%)
ACMH+ - completeness (76.96%)
ACMM
ACMM - accuracy (98.71%)
ACMM - completeness (85.16%)
ACMMP
ACMMP - accuracy (98.64%)
ACMMP - completeness (90.64%)
ACMMPR
ACMMPR - accuracy (98.62%)
ACMMPR - completeness (93.09%)
ACMMP_NAP
ACMMP_NAP - accuracy (98.37%)
ACMMP_NAP - completeness (93.66%)
ACMP
ACMP - accuracy (98.26%)
ACMP - completeness (85.23%)
AdaColmap
AdaColmap - accuracy (95.37%)
AdaColmap - completeness (90.71%)
ADS-MVSNet
ADS-MVSNet - accuracy (84.36%)
ADS-MVSNet - completeness (74.75%)
ambc
ambc - accuracy (91.71%)
ambc - completeness (48.73%)
Anonymous20231206
Anonymous20231206 - accuracy (91.36%)
Anonymous20231206 - completeness (63.10%)
Anonymous202405211
Anonymous202405211 - accuracy (93.94%)
Anonymous202405211 - completeness (84.62%)
anonymousdsp
anonymousdsp - accuracy (99.18%)
anonymousdsp - completeness (66.45%)
APD-MVS
APD-MVS - accuracy (97.83%)
APD-MVS - completeness (95.27%)
APDe-MVS
APDe-MVS - accuracy (98.63%)
APDe-MVS - completeness (95.79%)
baseline1
baseline1 - accuracy (89.24%)
baseline1 - completeness (88.03%)
baseline2
baseline2 - accuracy (90.09%)
baseline2 - completeness (80.32%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (96.70%)
Baseline_NR-MVSNet - completeness (75.92%)
CANet
CANet - accuracy (95.88%)
CANet - completeness (91.76%)
CANet_DTU
CANet_DTU - accuracy (93.61%)
CANet_DTU - completeness (86.63%)
canonicalmvs
canonicalmvs - accuracy (94.18%)
canonicalmvs - completeness (89.56%)
casdiffmvs
casdiffmvs - accuracy (94.28%)
casdiffmvs - completeness (86.01%)
CDPH-MVS
CDPH-MVS - accuracy (96.92%)
CDPH-MVS - completeness (92.95%)
CDS-MVSNet
CDS-MVSNet - accuracy (92.50%)
CDS-MVSNet - completeness (82.94%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (93.19%)
CHOSEN 1792x2688 - completeness (86.18%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (89.32%)
CHOSEN 280x420 - completeness (81.74%)
CLD-MVS
CLD-MVS - accuracy (95.82%)
CLD-MVS - completeness (90.01%)
CMPMVS
CMPMVS - accuracy (79.19%)
CMPMVS - completeness (72.69%)
CNLPA
CNLPA - accuracy (95.00%)
CNLPA - completeness (84.70%)
CNVR-MVS
CNVR-MVS - accuracy (96.43%)
CNVR-MVS - completeness (95.56%)
COLMAP_ROB
COLMAP_ROB - accuracy (98.56%)
COLMAP_ROB - completeness (76.59%)
CostFormer
CostFormer - accuracy (90.87%)
CostFormer - completeness (84.31%)
CP-MVS
CP-MVS - accuracy (98.43%)
CP-MVS - completeness (92.77%)
CP-MVSNet
CP-MVSNet - accuracy (98.12%)
CP-MVSNet - completeness (66.66%)
CPTT-MVS
CPTT-MVS - accuracy (97.88%)
CPTT-MVS - completeness (92.33%)
CR-MVSNet
CR-MVSNet - accuracy (86.72%)
CR-MVSNet - completeness (78.32%)
CS-MVS
CS-MVS - accuracy (96.72%)
CS-MVS - completeness (84.21%)
CSCG
CSCG - accuracy (96.52%)
CSCG - completeness (92.89%)
CVMVSNet
CVMVSNet - accuracy (94.68%)
CVMVSNet - completeness (72.05%)
DCV-MVSNet
DCV-MVSNet - accuracy (95.15%)
DCV-MVSNet - completeness (84.20%)
DeepC-MVS
DeepC-MVS - accuracy (97.96%)
DeepC-MVS - completeness (92.57%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (96.69%)
DeepC-MVS_fast - completeness (94.05%)
DeepMVS_CX
DeepMVS_CX - accuracy (53.20%)
DeepMVS_CX - completeness (43.77%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (97.03%)
DeepPCF-MVS - completeness (86.22%)
DELS-MVS
DELS-MVS - accuracy (94.76%)
DELS-MVS - completeness (92.78%)
diffmvs
diffmvs - accuracy (92.45%)
diffmvs - completeness (86.89%)
DPE-MVS
DPE-MVS - accuracy (98.25%)
DPE-MVS - completeness (96.60%)
DPM-MVS
DPM-MVS - accuracy (94.52%)
DPM-MVS - completeness (97.39%)
dps
dps - accuracy (88.37%)
dps - completeness (77.51%)
DTE-MVSNet
DTE-MVSNet - accuracy (98.20%)
DTE-MVSNet - completeness (65.03%)
DU-MVS
DU-MVS - accuracy (96.61%)
DU-MVS - completeness (77.01%)
DVP-MVS
DVP-MVS - accuracy (97.90%)
DVP-MVS - completeness (95.37%)
E-PMN
E-PMN - accuracy (80.19%)
E-PMN - completeness (11.56%)
Effi-MVS+
Effi-MVS+ - accuracy (95.04%)
Effi-MVS+ - completeness (85.28%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (94.57%)
Effi-MVS+-dtu - completeness (80.39%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (95.55%)
EG-PatchMatch MVS - completeness (72.51%)
EIA-MVS
EIA-MVS - accuracy (95.38%)
EIA-MVS - completeness (82.84%)
EMVS
EMVS - accuracy (81.13%)
EMVS - completeness (11.51%)
EPMVS
EPMVS - accuracy (86.08%)
EPMVS - completeness (78.62%)
EPNet
EPNet - accuracy (94.84%)
EPNet - completeness (91.13%)
EPNet_dtu
EPNet_dtu - accuracy (92.09%)
EPNet_dtu - completeness (82.98%)
EPP-MVSNet
EPP-MVSNet - accuracy (96.18%)
EPP-MVSNet - completeness (79.83%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (93.77%)
ET-MVSNet_ETH3D - completeness (87.06%)
ETV-MVS
ETV-MVS - accuracy (96.27%)
ETV-MVS - completeness (83.58%)
EU-MVSNet
EU-MVSNet - accuracy (96.53%)
EU-MVSNet - completeness (58.85%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (95.90%)
Fast-Effi-MVS+ - completeness (81.47%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (93.01%)
Fast-Effi-MVS+-dtu - completeness (79.72%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (95.42%)
FC-MVSNet-test - completeness (61.52%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (97.00%)
FC-MVSNet-train - completeness (79.96%)
FMVSNet1
FMVSNet1 - accuracy (94.37%)
FMVSNet1 - completeness (83.61%)
FMVSNet2
FMVSNet2 - accuracy (92.88%)
FMVSNet2 - completeness (86.73%)
FMVSNet3
FMVSNet3 - accuracy (91.62%)
FMVSNet3 - completeness (88.15%)
FMVSNet5
FMVSNet5 - accuracy (87.64%)
FMVSNet5 - completeness (75.88%)
FPMVS
FPMVS - accuracy (93.31%)
FPMVS - completeness (59.78%)
GA-MVS
GA-MVS - accuracy (92.28%)
GA-MVS - completeness (78.02%)
GBi-Net
GBi-Net - accuracy (92.88%)
GBi-Net - completeness (86.73%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (70.04%)
GG-mvs-BLEND - completeness (91.57%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (89.06%)
gg-mvs-nofinetune - completeness (85.66%)
Gipuma
Gipuma - accuracy (94.77%)
Gipuma - completeness (26.96%)
gm-plane-assit
gm-plane-assit - accuracy (97.99%)
gm-plane-assit - completeness (41.60%)
HFP-MVS
HFP-MVS - accuracy (98.16%)
HFP-MVS - completeness (93.57%)
HPM-MVS++
HPM-MVS++ - accuracy (97.68%)
HPM-MVS++ - completeness (94.65%)
HQP-MVS
HQP-MVS - accuracy (95.64%)
HQP-MVS - completeness (91.05%)
HyFIR lowres test
HyFIR lowres test - accuracy (94.30%)
HyFIR lowres test - completeness (82.97%)
IB-MVS
IB-MVS - accuracy (92.40%)
IB-MVS - completeness (71.95%)
IS_MVSNet
IS_MVSNet - accuracy (95.86%)
IS_MVSNet - completeness (80.44%)
IterMVS
IterMVS - accuracy (93.07%)
IterMVS - completeness (77.44%)
IterMVS-LS
IterMVS-LS - accuracy (92.80%)
IterMVS-LS - completeness (81.54%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (91.69%)
IterMVS-SCA-FT - completeness (77.42%)
LGP-MVS_train
LGP-MVS_train - accuracy (98.43%)
LGP-MVS_train - completeness (88.76%)
LS3D
LS3D - accuracy (97.99%)
LS3D - completeness (83.66%)
LTVRE_ROB
LTVRE_ROB - accuracy (98.30%)
LTVRE_ROB - completeness (70.98%)
MAR-MVS
MAR-MVS - accuracy (94.91%)
MAR-MVS - completeness (86.50%)
MCST-MVS
MCST-MVS - accuracy (96.49%)
MCST-MVS - completeness (95.43%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (94.68%)
MDA-MVSNet-bldmvs - completeness (55.61%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (90.09%)
MDTV_nov1_ep13 - completeness (79.25%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (94.07%)
MDTV_nov1_ep13_2view - completeness (67.53%)
MIMVSNet
MIMVSNet - accuracy (89.74%)
MIMVSNet - completeness (74.16%)
MIMVSNet1
MIMVSNet1 - accuracy (96.92%)
MIMVSNet1 - completeness (53.56%)
MP-MVS
MP-MVS - accuracy (98.49%)
MP-MVS - completeness (92.46%)
MS-PatchMatch
MS-PatchMatch - accuracy (90.92%)
MS-PatchMatch - completeness (85.42%)
MSDG
MSDG - accuracy (93.42%)
MSDG - completeness (85.25%)
MSLP-MVS++
MSLP-MVS++ - accuracy (93.12%)
MSLP-MVS++ - completeness (94.35%)
MSP-MVS
MSP-MVS - accuracy (98.27%)
MSP-MVS - completeness (95.72%)
MVE
MVE - accuracy (75.28%)
MVE - completeness (10.67%)
MVS-HIRNet
MVS-HIRNet - accuracy (76.83%)
MVS-HIRNet - completeness (58.54%)
MVSTER
MVSTER - accuracy (89.39%)
MVSTER - completeness (89.28%)
MVS_0304
MVS_0304 - accuracy (96.43%)
MVS_0304 - completeness (92.62%)
MVS_111021_LR
MVS_111021_LR - accuracy (95.09%)
MVS_111021_LR - completeness (86.20%)
MVS_Test
MVS_Test - accuracy (92.51%)
MVS_Test - completeness (88.21%)
NCCC
NCCC - accuracy (96.47%)
NCCC - completeness (95.40%)
new-patchmatchnet
new-patchmatchnet - accuracy (81.68%)
new-patchmatchnet - completeness (52.24%)
new_pmnet
new_pmnet - accuracy (76.76%)
new_pmnet - completeness (48.66%)
NR-MVSNet
NR-MVSNet - accuracy (96.69%)
NR-MVSNet - completeness (76.88%)
N_pmnet
N_pmnet - accuracy (86.11%)
N_pmnet - completeness (59.72%)
OMC-MVS
OMC-MVS - accuracy (96.64%)
OMC-MVS - completeness (87.60%)
OpenMVS
OpenMVS - accuracy (92.74%)
OpenMVS - completeness (89.36%)
OPM-MVS
OPM-MVS - accuracy (97.86%)
OPM-MVS - completeness (90.66%)
our_test_3
our_test_3 - accuracy (94.37%)
our_test_3 - completeness (64.47%)
PatchMatch-RL
PatchMatch-RL - accuracy (91.72%)
PatchMatch-RL - completeness (78.09%)
Patchmatch-RL test
Patchmatch-RL test - accuracy (8.96%)
Patchmatch-RL test - completeness (8.17%)
PatchmatchNet
PatchmatchNet - accuracy (90.78%)
PatchmatchNet - completeness (77.76%)
Patchmtry
Patchmtry - accuracy (86.72%)
Patchmtry - completeness (78.32%)
PatchT
PatchT - accuracy (89.87%)
PatchT - completeness (59.81%)
PCF-MVS
PCF-MVS - accuracy (96.37%)
PCF-MVS - completeness (90.27%)
PEN-MVS
PEN-MVS - accuracy (98.25%)
PEN-MVS - completeness (66.97%)
PGM-MVS
PGM-MVS - accuracy (98.55%)
PGM-MVS - completeness (93.06%)
PHI-MVS
PHI-MVS - accuracy (96.46%)
PHI-MVS - completeness (89.99%)
PLC
PLC - accuracy (94.38%)
PLC - completeness (88.80%)
PM-MVS
PM-MVS - accuracy (95.99%)
PM-MVS - completeness (65.07%)
pm-mvs1
pm-mvs1 - accuracy (92.61%)
pm-mvs1 - completeness (76.11%)
PMMVS
PMMVS - accuracy (88.54%)
PMMVS - completeness (78.30%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (96.37%)
pmmvs-eth3d - completeness (66.09%)
PMMVS2
PMMVS2 - accuracy (75.52%)
PMMVS2 - completeness (27.79%)
pmmvs3
pmmvs3 - accuracy (89.53%)
pmmvs3 - completeness (50.07%)
pmmvs5
pmmvs5 - accuracy (91.87%)
pmmvs5 - completeness (72.94%)
pmmvs6
pmmvs6 - accuracy (93.40%)
pmmvs6 - completeness (71.33%)
pmnet_mix02
pmnet_mix02 - accuracy (88.52%)
pmnet_mix02 - completeness (63.24%)
PMVS
PMVS - accuracy (96.70%)
PMVS - completeness (32.62%)
PS-CasMVS
PS-CasMVS - accuracy (98.17%)
PS-CasMVS - completeness (66.42%)
PVSNet_Blended
PVSNet_Blended - accuracy (91.74%)
PVSNet_Blended - completeness (86.57%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (91.74%)
PVSNet_BlendedMVS - completeness (86.57%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (95.71%)
PVSNet_Blended_VisFu - completeness (82.41%)
QAPM
QAPM - accuracy (93.01%)
QAPM - completeness (91.71%)
RPMNet
RPMNet - accuracy (90.64%)
RPMNet - completeness (73.83%)
RPSCF
RPSCF - accuracy (95.58%)
RPSCF - completeness (76.24%)
SCA
SCA - accuracy (92.21%)
SCA - completeness (75.57%)
SD-MVS
SD-MVS - accuracy (97.01%)
SD-MVS - completeness (94.56%)
SED-MVS
SED-MVS - accuracy (98.18%)
SED-MVS - completeness (95.99%)
SF-MVS
SF-MVS - accuracy (94.80%)
SF-MVS - completeness (96.86%)
SMA-MVS
SMA-MVS - accuracy (97.55%)
SMA-MVS - completeness (94.46%)
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 (98.40%)
SteuartSystems-ACMMP - completeness (93.95%)
TAMVS
TAMVS - accuracy (87.29%)
TAMVS - completeness (74.82%)
TAPA-MVS
TAPA-MVS - accuracy (95.74%)
TAPA-MVS - completeness (88.53%)
TDRefinement
TDRefinement - accuracy (99.08%)
TDRefinement - completeness (77.42%)
test-mter
test-mter - accuracy (88.51%)
test-mter - completeness (73.85%)
test1
test1 - accuracy (92.88%)
test1 - completeness (86.73%)
test123
test123 - accuracy (1.53%)
test123 - completeness (0.20%)
testgi
testgi - accuracy (93.47%)
testgi - completeness (60.42%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (87.04%)
TESTMET0.1,1 - completeness (76.17%)
testmvs
testmvs - accuracy (1.53%)
testmvs - completeness (0.38%)
test_part1
test_part1 - accuracy (98.33%)
test_part1 - completeness (84.31%)
thisisatest0515
thisisatest0515 - accuracy (95.56%)
thisisatest0515 - completeness (68.03%)
thisisatest0530
thisisatest0530 - accuracy (93.45%)
thisisatest0530 - completeness (81.77%)
TinyColmap
TinyColmap - accuracy (94.75%)
TinyColmap - completeness (72.80%)
tmp_tt
tmp_tt - accuracy (21.29%)
tmp_tt - completeness (35.84%)
tpm
tpm - accuracy (89.79%)
tpm - completeness (78.61%)
tpm cat1
tpm cat1 - accuracy (88.86%)
tpm cat1 - completeness (82.96%)
tpmrst
tpmrst - accuracy (86.74%)
tpmrst - completeness (79.31%)
train_agg
train_agg - accuracy (97.63%)
train_agg - completeness (94.31%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (96.90%)
TranMVSNet+NR-MVSNet - completeness (76.55%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (93.30%)
TransMVSNet (Re) - completeness (73.88%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (95.67%)
TSAR-MVS + ACMM - completeness (94.52%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (95.36%)
TSAR-MVS + COLMAP - completeness (89.25%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (94.37%)
TSAR-MVS + GP. - completeness (92.51%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (98.71%)
TSAR-MVS + MP. - completeness (94.75%)
tttt0517
tttt0517 - accuracy (93.67%)
tttt0517 - completeness (81.42%)
UA-Net
UA-Net - accuracy (97.79%)
UA-Net - completeness (79.54%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (96.19%)
UGNet - completeness (80.28%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (96.68%)
UniMVSNet (Re) - completeness (75.73%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (95.06%)
UniMVSNet_ETH3D - completeness (78.65%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (96.61%)
UniMVSNet_NR-MVSNet - completeness (77.01%)
USDC
USDC - accuracy (93.66%)
USDC - completeness (80.42%)
Vis-MVSNet
Vis-MVSNet - accuracy (97.62%)
Vis-MVSNet - completeness (80.33%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (92.91%)
Vis-MVSNet (Re-imp) - completeness (78.07%)
WR-MVS_H
WR-MVS_H - accuracy (98.25%)
WR-MVS_H - completeness (65.13%)
X-MVS
X-MVS - accuracy (98.43%)
X-MVS - completeness (92.26%)
X-MVStestdata
X-MVStestdata - accuracy (98.73%)
X-MVStestdata - completeness (85.97%)
XVS
XVS - accuracy (98.73%)
XVS - completeness (85.97%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (94.80%)
xxxxxxxxxxxxxcwj - completeness (96.86%)
zzz-MVS
zzz-MVS - accuracy (98.51%)
zzz-MVS - completeness (93.39%)
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
:
-200546.64 to 139732.98
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
:
235752.6
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