+
−
⇧
i
D
T
facade (high-res multi-view) - Tolerance 5cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (87.79%)
3Dnovator - completeness (83.06%)
3Dnovator+
3Dnovator+ - accuracy (94.02%)
3Dnovator+ - completeness (82.41%)
ACMH
ACMH - accuracy (92.05%)
ACMH - completeness (77.63%)
ACMH+
ACMH+ - accuracy (92.52%)
ACMH+ - completeness (76.04%)
ACMM
ACMM - accuracy (93.79%)
ACMM - completeness (80.67%)
ACMMP
ACMMP - accuracy (93.74%)
ACMMP - completeness (85.60%)
ACMMPR
ACMMPR - accuracy (94.54%)
ACMMPR - completeness (87.08%)
ACMMP_NAP
ACMMP_NAP - accuracy (93.48%)
ACMMP_NAP - completeness (89.23%)
ACMP
ACMP - accuracy (93.22%)
ACMP - completeness (78.52%)
AdaColmap
AdaColmap - accuracy (91.73%)
AdaColmap - completeness (91.08%)
ADS-MVSNet
ADS-MVSNet - accuracy (83.69%)
ADS-MVSNet - completeness (50.56%)
Anonymous20231206
Anonymous20231206 - accuracy (86.41%)
Anonymous20231206 - completeness (67.62%)
Anonymous202405211
Anonymous202405211 - accuracy (91.35%)
Anonymous202405211 - completeness (77.96%)
anonymousdsp
anonymousdsp - accuracy (85.42%)
anonymousdsp - completeness (63.53%)
APD-MVS
APD-MVS - accuracy (93.92%)
APD-MVS - completeness (91.47%)
APDe-MVS
APDe-MVS - accuracy (93.69%)
APDe-MVS - completeness (91.98%)
baseline1
baseline1 - accuracy (86.85%)
baseline1 - completeness (80.86%)
baseline2
baseline2 - accuracy (84.25%)
baseline2 - completeness (74.25%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (94.54%)
Baseline_NR-MVSNet - completeness (74.75%)
CANet
CANet - accuracy (91.94%)
CANet - completeness (83.27%)
CANet_DTU
CANet_DTU - accuracy (83.47%)
CANet_DTU - completeness (68.85%)
canonicalmvs
canonicalmvs - accuracy (90.47%)
canonicalmvs - completeness (76.01%)
casdiffmvs
casdiffmvs - accuracy (88.73%)
casdiffmvs - completeness (79.62%)
CDPH-MVS
CDPH-MVS - accuracy (91.85%)
CDPH-MVS - completeness (85.95%)
CDS-MVSNet
CDS-MVSNet - accuracy (89.85%)
CDS-MVSNet - completeness (72.64%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (83.30%)
CHOSEN 1792x2688 - completeness (75.40%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (75.38%)
CHOSEN 280x420 - completeness (59.96%)
CLD-MVS
CLD-MVS - accuracy (81.44%)
CLD-MVS - completeness (82.72%)
CMPMVS
CMPMVS - accuracy (75.93%)
CMPMVS - completeness (70.72%)
CNLPA
CNLPA - accuracy (86.57%)
CNLPA - completeness (85.07%)
CNVR-MVS
CNVR-MVS - accuracy (91.95%)
CNVR-MVS - completeness (92.91%)
COLMAP_ROB
COLMAP_ROB - accuracy (91.72%)
COLMAP_ROB - completeness (76.46%)
CostFormer
CostFormer - accuracy (86.26%)
CostFormer - completeness (59.84%)
CP-MVS
CP-MVS - accuracy (94.70%)
CP-MVS - completeness (86.86%)
CP-MVSNet
CP-MVSNet - accuracy (96.98%)
CP-MVSNet - completeness (67.53%)
CPTT-MVS
CPTT-MVS - accuracy (93.67%)
CPTT-MVS - completeness (84.75%)
CR-MVSNet
CR-MVSNet - accuracy (92.22%)
CR-MVSNet - completeness (54.14%)
CS-MVS
CS-MVS - accuracy (91.36%)
CS-MVS - completeness (75.09%)
CSCG
CSCG - accuracy (90.98%)
CSCG - completeness (87.06%)
CVMVSNet
CVMVSNet - accuracy (78.68%)
CVMVSNet - completeness (70.90%)
DCV-MVSNet
DCV-MVSNet - accuracy (91.21%)
DCV-MVSNet - completeness (72.36%)
DeepC-MVS
DeepC-MVS - accuracy (94.28%)
DeepC-MVS - completeness (89.38%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (92.17%)
DeepC-MVS_fast - completeness (90.23%)
DeepMVS_CX
DeepMVS_CX - accuracy (19.21%)
DeepMVS_CX - completeness (40.58%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (90.65%)
DeepPCF-MVS - completeness (88.59%)
DELS-MVS
DELS-MVS - accuracy (87.22%)
DELS-MVS - completeness (84.50%)
diffmvs
diffmvs - accuracy (84.84%)
diffmvs - completeness (78.62%)
DPE-MVS
DPE-MVS - accuracy (93.73%)
DPE-MVS - completeness (92.45%)
DPM-MVS
DPM-MVS - accuracy (89.63%)
DPM-MVS - completeness (92.56%)
dps
dps - accuracy (87.46%)
dps - completeness (58.33%)
DTE-MVSNet
DTE-MVSNet - accuracy (96.89%)
DTE-MVSNet - completeness (68.28%)
DU-MVS
DU-MVS - accuracy (95.32%)
DU-MVS - completeness (74.42%)
DVP-MVS
DVP-MVS - accuracy (93.60%)
DVP-MVS - completeness (92.04%)
E-PMN
E-PMN - accuracy (71.20%)
E-PMN - completeness (43.72%)
Effi-MVS+
Effi-MVS+ - accuracy (92.98%)
Effi-MVS+ - completeness (70.68%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (92.14%)
Effi-MVS+-dtu - completeness (67.70%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (88.18%)
EG-PatchMatch MVS - completeness (63.68%)
EIA-MVS
EIA-MVS - accuracy (90.40%)
EIA-MVS - completeness (76.39%)
EMVS
EMVS - accuracy (70.54%)
EMVS - completeness (43.75%)
EPMVS
EPMVS - accuracy (83.51%)
EPMVS - completeness (55.44%)
EPNet
EPNet - accuracy (93.54%)
EPNet - completeness (83.12%)
EPNet_dtu
EPNet_dtu - accuracy (90.08%)
EPNet_dtu - completeness (78.83%)
EPP-MVSNet
EPP-MVSNet - accuracy (91.97%)
EPP-MVSNet - completeness (74.51%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (88.59%)
ET-MVSNet_ETH3D - completeness (73.57%)
ETV-MVS
ETV-MVS - accuracy (92.00%)
ETV-MVS - completeness (76.37%)
EU-MVSNet
EU-MVSNet - accuracy (81.51%)
EU-MVSNet - completeness (61.24%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (90.61%)
Fast-Effi-MVS+ - completeness (68.01%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (95.71%)
Fast-Effi-MVS+-dtu - completeness (58.07%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (91.18%)
FC-MVSNet-test - completeness (69.45%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (89.40%)
FC-MVSNet-train - completeness (78.53%)
FMVSNet1
FMVSNet1 - accuracy (92.22%)
FMVSNet1 - completeness (69.99%)
FMVSNet2
FMVSNet2 - accuracy (90.69%)
FMVSNet2 - completeness (71.91%)
FMVSNet3
FMVSNet3 - accuracy (90.05%)
FMVSNet3 - completeness (72.57%)
FMVSNet5
FMVSNet5 - accuracy (78.15%)
FMVSNet5 - completeness (63.74%)
FPMVS
FPMVS - accuracy (83.62%)
FPMVS - completeness (59.33%)
GA-MVS
GA-MVS - accuracy (86.62%)
GA-MVS - completeness (71.67%)
GBi-Net
GBi-Net - accuracy (90.05%)
GBi-Net - completeness (72.57%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (0.39%)
GG-mvs-BLEND - completeness (0.09%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (95.94%)
gg-mvs-nofinetune - completeness (48.77%)
Gipuma
Gipuma - accuracy (92.50%)
Gipuma - completeness (48.31%)
gm-plane-assit
gm-plane-assit - accuracy (84.66%)
gm-plane-assit - completeness (53.37%)
HFP-MVS
HFP-MVS - accuracy (94.54%)
HFP-MVS - completeness (87.60%)
HPM-MVS++
HPM-MVS++ - accuracy (94.05%)
HPM-MVS++ - completeness (91.01%)
HQP-MVS
HQP-MVS - accuracy (91.06%)
HQP-MVS - completeness (84.35%)
HyFIR lowres test
HyFIR lowres test - accuracy (88.79%)
HyFIR lowres test - completeness (69.85%)
IB-MVS
IB-MVS - accuracy (85.58%)
IB-MVS - completeness (77.53%)
IS_MVSNet
IS_MVSNet - accuracy (92.12%)
IS_MVSNet - completeness (74.64%)
IterMVS
IterMVS - accuracy (81.69%)
IterMVS - completeness (61.00%)
IterMVS-LS
IterMVS-LS - accuracy (92.27%)
IterMVS-LS - completeness (68.52%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (87.48%)
IterMVS-SCA-FT - completeness (61.09%)
LGP-MVS_train
LGP-MVS_train - accuracy (93.83%)
LGP-MVS_train - completeness (78.05%)
LS3D
LS3D - accuracy (92.35%)
LS3D - completeness (85.88%)
LTVRE_ROB
LTVRE_ROB - accuracy (94.90%)
LTVRE_ROB - completeness (65.02%)
MAR-MVS
MAR-MVS - accuracy (91.82%)
MAR-MVS - completeness (76.71%)
MCST-MVS
MCST-MVS - accuracy (90.87%)
MCST-MVS - completeness (92.54%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (85.89%)
MDA-MVSNet-bldmvs - completeness (68.41%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (81.98%)
MDTV_nov1_ep13 - completeness (61.52%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (84.97%)
MDTV_nov1_ep13_2view - completeness (54.54%)
MIMVSNet
MIMVSNet - accuracy (89.49%)
MIMVSNet - completeness (54.10%)
MIMVSNet1
MIMVSNet1 - accuracy (89.68%)
MIMVSNet1 - completeness (63.03%)
MP-MVS
MP-MVS - accuracy (94.53%)
MP-MVS - completeness (87.19%)
MS-PatchMatch
MS-PatchMatch - accuracy (82.25%)
MS-PatchMatch - completeness (69.53%)
MSDG
MSDG - accuracy (85.43%)
MSDG - completeness (86.02%)
MSLP-MVS++
MSLP-MVS++ - accuracy (91.93%)
MSLP-MVS++ - completeness (86.26%)
MSP-MVS
MSP-MVS - accuracy (93.88%)
MSP-MVS - completeness (90.91%)
MVE
MVE - accuracy (72.76%)
MVE - completeness (34.60%)
MVS-HIRNet
MVS-HIRNet - accuracy (86.59%)
MVS-HIRNet - completeness (52.10%)
MVSTER
MVSTER - accuracy (82.99%)
MVSTER - completeness (77.05%)
MVS_0304
MVS_0304 - accuracy (92.76%)
MVS_0304 - completeness (81.10%)
MVS_111021_LR
MVS_111021_LR - accuracy (86.92%)
MVS_111021_LR - completeness (82.49%)
MVS_Test
MVS_Test - accuracy (88.54%)
MVS_Test - completeness (73.15%)
NCCC
NCCC - accuracy (92.62%)
NCCC - completeness (92.39%)
new-patchmatchnet
new-patchmatchnet - accuracy (83.48%)
new-patchmatchnet - completeness (61.75%)
new_pmnet
new_pmnet - accuracy (64.17%)
new_pmnet - completeness (47.99%)
NR-MVSNet
NR-MVSNet - accuracy (95.32%)
NR-MVSNet - completeness (74.42%)
N_pmnet
N_pmnet - accuracy (76.36%)
N_pmnet - completeness (66.47%)
OMC-MVS
OMC-MVS - accuracy (89.36%)
OMC-MVS - completeness (83.51%)
OpenMVS
OpenMVS - accuracy (85.47%)
OpenMVS - completeness (81.59%)
OPM-MVS
OPM-MVS - accuracy (93.28%)
OPM-MVS - completeness (83.62%)
PatchMatch-RL
PatchMatch-RL - accuracy (86.64%)
PatchMatch-RL - completeness (77.51%)
PatchmatchNet
PatchmatchNet - accuracy (87.27%)
PatchmatchNet - completeness (55.85%)
Patchmtry
Patchmtry - accuracy (92.22%)
Patchmtry - completeness (54.14%)
PatchT
PatchT - accuracy (87.39%)
PatchT - completeness (51.78%)
PCF-MVS
PCF-MVS - accuracy (90.19%)
PCF-MVS - completeness (89.81%)
PEN-MVS
PEN-MVS - accuracy (96.86%)
PEN-MVS - completeness (68.24%)
PGM-MVS
PGM-MVS - accuracy (94.12%)
PGM-MVS - completeness (82.48%)
PHI-MVS
PHI-MVS - accuracy (91.10%)
PHI-MVS - completeness (84.56%)
PLC
PLC - accuracy (90.10%)
PLC - completeness (84.47%)
PM-MVS
PM-MVS - accuracy (84.81%)
PM-MVS - completeness (62.08%)
pm-mvs1
pm-mvs1 - accuracy (89.91%)
pm-mvs1 - completeness (71.05%)
PMMVS
PMMVS - accuracy (64.01%)
PMMVS - completeness (70.77%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (89.06%)
pmmvs-eth3d - completeness (66.31%)
PMMVS2
PMMVS2 - accuracy (60.97%)
PMMVS2 - completeness (39.69%)
pmmvs3
pmmvs3 - accuracy (58.71%)
pmmvs3 - completeness (46.89%)
pmmvs5
pmmvs5 - accuracy (82.13%)
pmmvs5 - completeness (67.91%)
pmmvs6
pmmvs6 - accuracy (92.43%)
pmmvs6 - completeness (65.95%)
pmnet_mix02
pmnet_mix02 - accuracy (78.58%)
pmnet_mix02 - completeness (67.91%)
PMVS
PMVS - accuracy (91.57%)
PMVS - completeness (56.02%)
PS-CasMVS
PS-CasMVS - accuracy (97.02%)
PS-CasMVS - completeness (67.43%)
PVSNet_Blended
PVSNet_Blended - accuracy (85.89%)
PVSNet_Blended - completeness (81.82%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (85.89%)
PVSNet_BlendedMVS - completeness (81.82%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (90.58%)
PVSNet_Blended_VisFu - completeness (77.36%)
QAPM
QAPM - accuracy (87.51%)
QAPM - completeness (82.62%)
RPMNet
RPMNet - accuracy (92.11%)
RPMNet - completeness (50.54%)
RPSCF
RPSCF - accuracy (88.08%)
RPSCF - completeness (72.37%)
SCA
SCA - accuracy (92.09%)
SCA - completeness (54.56%)
SD-MVS
SD-MVS - accuracy (93.04%)
SD-MVS - completeness (90.89%)
SED-MVS
SED-MVS - accuracy (93.80%)
SED-MVS - completeness (92.05%)
SF-MVS
SF-MVS - accuracy (91.76%)
SF-MVS - completeness (93.46%)
SMA-MVS
SMA-MVS - accuracy (93.70%)
SMA-MVS - completeness (90.19%)
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 (94.77%)
SR-MVS - completeness (87.51%)
SteuartSystems-ACMMP
SteuartSystems-ACMMP - accuracy (94.24%)
SteuartSystems-ACMMP - completeness (89.44%)
TAMVS
TAMVS - accuracy (75.12%)
TAMVS - completeness (68.09%)
TAPA-MVS
TAPA-MVS - accuracy (86.98%)
TAPA-MVS - completeness (82.80%)
TDRefinement
TDRefinement - accuracy (93.92%)
TDRefinement - completeness (73.79%)
test-mter
test-mter - accuracy (59.06%)
test-mter - completeness (65.31%)
test1
test1 - accuracy (90.05%)
test1 - completeness (72.57%)
test123
test123 - accuracy (0.82%)
test123 - completeness (0.04%)
testgi
testgi - accuracy (84.89%)
testgi - completeness (66.20%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (58.33%)
TESTMET0.1,1 - completeness (67.83%)
testmvs
testmvs - accuracy (0.83%)
testmvs - completeness (0.09%)
test_part1
test_part1 - accuracy (93.88%)
test_part1 - completeness (71.43%)
thisisatest0515
thisisatest0515 - accuracy (88.55%)
thisisatest0515 - completeness (68.02%)
thisisatest0530
thisisatest0530 - accuracy (87.53%)
thisisatest0530 - completeness (73.84%)
TinyColmap
TinyColmap - accuracy (88.90%)
TinyColmap - completeness (69.78%)
tmp_tt
tmp_tt - accuracy (6.40%)
tmp_tt - completeness (15.08%)
tpm
tpm - accuracy (83.75%)
tpm - completeness (55.91%)
tpm cat1
tpm cat1 - accuracy (86.55%)
tpm cat1 - completeness (59.33%)
tpmrst
tpmrst - accuracy (81.52%)
tpmrst - completeness (54.91%)
train_agg
train_agg - accuracy (92.19%)
train_agg - completeness (89.05%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (94.99%)
TranMVSNet+NR-MVSNet - completeness (75.65%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (89.53%)
TransMVSNet (Re) - completeness (74.34%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (94.21%)
TSAR-MVS + ACMM - completeness (86.97%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (89.46%)
TSAR-MVS + COLMAP - completeness (82.00%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (92.47%)
TSAR-MVS + GP. - completeness (83.83%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (91.58%)
TSAR-MVS + MP. - completeness (89.87%)
tttt0517
tttt0517 - accuracy (87.53%)
tttt0517 - completeness (73.84%)
UA-Net
UA-Net - accuracy (95.64%)
UA-Net - completeness (75.49%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (92.10%)
UGNet - completeness (76.53%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (94.99%)
UniMVSNet (Re) - completeness (73.51%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (96.91%)
UniMVSNet_ETH3D - completeness (70.52%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (94.79%)
UniMVSNet_NR-MVSNet - completeness (75.82%)
USDC
USDC - accuracy (87.41%)
USDC - completeness (71.83%)
Vis-MVSNet
Vis-MVSNet - accuracy (91.41%)
Vis-MVSNet - completeness (72.55%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (91.20%)
Vis-MVSNet (Re-imp) - completeness (74.48%)
WR-MVS_H
WR-MVS_H - accuracy (97.32%)
WR-MVS_H - completeness (66.99%)
X-MVS
X-MVS - accuracy (94.28%)
X-MVS - completeness (86.98%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (91.76%)
xxxxxxxxxxxxxcwj - completeness (93.46%)
zzz-MVS
zzz-MVS - accuracy (94.48%)
zzz-MVS - completeness (88.00%)
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
:
-10.36 to 91.04
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
:
70.3
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