+
−
⇧
i
D
T
courtyard (high-res multi-view) - Tolerance 2cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (79.31%)
3Dnovator - completeness (91.43%)
3Dnovator+
3Dnovator+ - accuracy (86.82%)
3Dnovator+ - completeness (89.25%)
ACMH
ACMH - accuracy (86.45%)
ACMH - completeness (78.92%)
ACMH+
ACMH+ - accuracy (88.58%)
ACMH+ - completeness (77.37%)
ACMM
ACMM - accuracy (91.35%)
ACMM - completeness (82.85%)
ACMMP
ACMMP - accuracy (91.24%)
ACMMP - completeness (85.87%)
ACMMPR
ACMMPR - accuracy (91.92%)
ACMMPR - completeness (88.41%)
ACMMP_NAP
ACMMP_NAP - accuracy (91.00%)
ACMMP_NAP - completeness (89.57%)
ACMP
ACMP - accuracy (90.83%)
ACMP - completeness (80.96%)
AdaColmap
AdaColmap - accuracy (89.08%)
AdaColmap - completeness (89.38%)
ADS-MVSNet
ADS-MVSNet - accuracy (59.48%)
ADS-MVSNet - completeness (65.80%)
ambc
ambc - accuracy (91.62%)
ambc - completeness (50.36%)
Anonymous20231206
Anonymous20231206 - accuracy (76.45%)
Anonymous20231206 - completeness (64.70%)
Anonymous202405211
Anonymous202405211 - accuracy (83.92%)
Anonymous202405211 - completeness (78.00%)
anonymousdsp
anonymousdsp - accuracy (64.64%)
anonymousdsp - completeness (53.82%)
APD-MVS
APD-MVS - accuracy (91.73%)
APD-MVS - completeness (89.61%)
APDe-MVS
APDe-MVS - accuracy (90.47%)
APDe-MVS - completeness (91.43%)
baseline1
baseline1 - accuracy (78.95%)
baseline1 - completeness (80.56%)
baseline2
baseline2 - accuracy (75.69%)
baseline2 - completeness (75.76%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (88.30%)
Baseline_NR-MVSNet - completeness (66.69%)
CANet
CANet - accuracy (87.30%)
CANet - completeness (86.83%)
CANet_DTU
CANet_DTU - accuracy (77.27%)
CANet_DTU - completeness (76.81%)
canonicalmvs
canonicalmvs - accuracy (83.17%)
canonicalmvs - completeness (81.52%)
casdiffmvs
casdiffmvs - accuracy (81.41%)
casdiffmvs - completeness (79.26%)
CDPH-MVS
CDPH-MVS - accuracy (89.61%)
CDPH-MVS - completeness (89.22%)
CDS-MVSNet
CDS-MVSNet - accuracy (81.62%)
CDS-MVSNet - completeness (70.05%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (69.11%)
CHOSEN 1792x2688 - completeness (86.57%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (51.63%)
CHOSEN 280x420 - completeness (59.88%)
CLD-MVS
CLD-MVS - accuracy (88.01%)
CLD-MVS - completeness (82.21%)
CMPMVS
CMPMVS - accuracy (68.11%)
CMPMVS - completeness (72.01%)
CNLPA
CNLPA - accuracy (84.55%)
CNLPA - completeness (80.79%)
CNVR-MVS
CNVR-MVS - accuracy (90.11%)
CNVR-MVS - completeness (92.58%)
COLMAP_ROB
COLMAP_ROB - accuracy (88.98%)
COLMAP_ROB - completeness (73.47%)
CostFormer
CostFormer - accuracy (72.79%)
CostFormer - completeness (79.47%)
CP-MVS
CP-MVS - accuracy (92.16%)
CP-MVS - completeness (86.95%)
CP-MVSNet
CP-MVSNet - accuracy (92.39%)
CP-MVSNet - completeness (58.77%)
CPTT-MVS
CPTT-MVS - accuracy (90.95%)
CPTT-MVS - completeness (81.43%)
CR-MVSNet
CR-MVSNet - accuracy (72.78%)
CR-MVSNet - completeness (68.63%)
CS-MVS
CS-MVS - accuracy (85.59%)
CS-MVS - completeness (77.74%)
CSCG
CSCG - accuracy (88.12%)
CSCG - completeness (91.85%)
CVMVSNet
CVMVSNet - accuracy (71.95%)
CVMVSNet - completeness (62.61%)
DCV-MVSNet
DCV-MVSNet - accuracy (82.91%)
DCV-MVSNet - completeness (77.65%)
DeepC-MVS
DeepC-MVS - accuracy (91.26%)
DeepC-MVS - completeness (87.42%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (89.89%)
DeepC-MVS_fast - completeness (91.04%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (87.48%)
DeepPCF-MVS - completeness (90.11%)
DELS-MVS
DELS-MVS - accuracy (79.31%)
DELS-MVS - completeness (88.26%)
diffmvs
diffmvs - accuracy (75.64%)
diffmvs - completeness (75.60%)
DPE-MVS
DPE-MVS - accuracy (89.69%)
DPE-MVS - completeness (92.09%)
DPM-MVS
DPM-MVS - accuracy (87.54%)
DPM-MVS - completeness (91.66%)
dps
dps - accuracy (71.41%)
dps - completeness (75.27%)
DTE-MVSNet
DTE-MVSNet - accuracy (93.31%)
DTE-MVSNet - completeness (61.75%)
DU-MVS
DU-MVS - accuracy (88.30%)
DU-MVS - completeness (66.69%)
DVP-MVS
DVP-MVS - accuracy (89.01%)
DVP-MVS - completeness (91.98%)
E-PMN
E-PMN - accuracy (67.01%)
E-PMN - completeness (28.73%)
Effi-MVS+
Effi-MVS+ - accuracy (84.51%)
Effi-MVS+ - completeness (78.04%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (85.48%)
Effi-MVS+-dtu - completeness (73.04%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (86.38%)
EG-PatchMatch MVS - completeness (72.32%)
EIA-MVS
EIA-MVS - accuracy (87.24%)
EIA-MVS - completeness (78.12%)
EMVS
EMVS - accuracy (66.26%)
EMVS - completeness (28.15%)
EPMVS
EPMVS - accuracy (62.41%)
EPMVS - completeness (75.81%)
EPNet
EPNet - accuracy (89.51%)
EPNet - completeness (88.31%)
EPNet_dtu
EPNet_dtu - accuracy (78.28%)
EPNet_dtu - completeness (81.04%)
EPP-MVSNet
EPP-MVSNet - accuracy (86.00%)
EPP-MVSNet - completeness (75.71%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (79.22%)
ET-MVSNet_ETH3D - completeness (51.61%)
ETV-MVS
ETV-MVS - accuracy (86.69%)
ETV-MVS - completeness (78.23%)
EU-MVSNet
EU-MVSNet - accuracy (67.62%)
EU-MVSNet - completeness (49.26%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (82.24%)
Fast-Effi-MVS+ - completeness (73.67%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (79.55%)
Fast-Effi-MVS+-dtu - completeness (71.21%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (76.63%)
FC-MVSNet-test - completeness (59.49%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (84.06%)
FC-MVSNet-train - completeness (78.35%)
FMVSNet1
FMVSNet1 - accuracy (78.62%)
FMVSNet1 - completeness (65.31%)
FMVSNet2
FMVSNet2 - accuracy (76.76%)
FMVSNet2 - completeness (69.49%)
FMVSNet3
FMVSNet3 - accuracy (75.00%)
FMVSNet3 - completeness (70.89%)
FMVSNet5
FMVSNet5 - accuracy (60.83%)
FMVSNet5 - completeness (52.66%)
FPMVS
FPMVS - accuracy (82.92%)
FPMVS - completeness (55.97%)
GA-MVS
GA-MVS - accuracy (78.37%)
GA-MVS - completeness (69.68%)
GBi-Net
GBi-Net - accuracy (76.76%)
GBi-Net - completeness (69.49%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (0.14%)
GG-mvs-BLEND - completeness (0.03%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (81.48%)
gg-mvs-nofinetune - completeness (76.15%)
Gipuma
Gipuma - accuracy (83.88%)
Gipuma - completeness (31.47%)
gm-plane-assit
gm-plane-assit - accuracy (84.43%)
gm-plane-assit - completeness (69.27%)
HFP-MVS
HFP-MVS - accuracy (91.46%)
HFP-MVS - completeness (90.15%)
HPM-MVS++
HPM-MVS++ - accuracy (92.58%)
HPM-MVS++ - completeness (92.65%)
HQP-MVS
HQP-MVS - accuracy (89.19%)
HQP-MVS - completeness (85.67%)
HyFIR lowres test
HyFIR lowres test - accuracy (73.08%)
HyFIR lowres test - completeness (80.85%)
IB-MVS
IB-MVS - accuracy (76.76%)
IB-MVS - completeness (81.75%)
IS_MVSNet
IS_MVSNet - accuracy (86.19%)
IS_MVSNet - completeness (76.92%)
IterMVS
IterMVS - accuracy (71.83%)
IterMVS - completeness (67.29%)
IterMVS-LS
IterMVS-LS - accuracy (81.83%)
IterMVS-LS - completeness (73.67%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (76.67%)
IterMVS-SCA-FT - completeness (66.64%)
LGP-MVS_train
LGP-MVS_train - accuracy (90.88%)
LGP-MVS_train - completeness (82.13%)
LS3D
LS3D - accuracy (89.72%)
LS3D - completeness (80.85%)
LTVRE_ROB
LTVRE_ROB - accuracy (83.19%)
LTVRE_ROB - completeness (64.76%)
MAR-MVS
MAR-MVS - accuracy (85.18%)
MAR-MVS - completeness (89.87%)
MCST-MVS
MCST-MVS - accuracy (87.30%)
MCST-MVS - completeness (94.07%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (50.71%)
MDA-MVSNet-bldmvs - completeness (38.34%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (67.08%)
MDTV_nov1_ep13 - completeness (70.91%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (71.15%)
MDTV_nov1_ep13_2view - completeness (60.50%)
MIMVSNet
MIMVSNet - accuracy (68.20%)
MIMVSNet - completeness (54.79%)
MIMVSNet1
MIMVSNet1 - accuracy (72.90%)
MIMVSNet1 - completeness (32.14%)
MP-MVS
MP-MVS - accuracy (92.92%)
MP-MVS - completeness (88.48%)
mPP-MVS
mPP-MVS - accuracy (93.05%)
mPP-MVS - completeness (86.96%)
MS-PatchMatch
MS-PatchMatch - accuracy (77.16%)
MS-PatchMatch - completeness (85.20%)
MSDG
MSDG - accuracy (82.40%)
MSDG - completeness (82.02%)
MSLP-MVS++
MSLP-MVS++ - accuracy (85.71%)
MSLP-MVS++ - completeness (88.39%)
MSP-MVS
MSP-MVS - accuracy (90.63%)
MSP-MVS - completeness (89.38%)
MVE
MVE - accuracy (35.21%)
MVE - completeness (7.72%)
MVS-HIRNet
MVS-HIRNet - accuracy (57.74%)
MVS-HIRNet - completeness (60.30%)
MVSTER
MVSTER - accuracy (66.33%)
MVSTER - completeness (74.98%)
MVS_0304
MVS_0304 - accuracy (88.32%)
MVS_0304 - completeness (84.22%)
MVS_111021_LR
MVS_111021_LR - accuracy (82.88%)
MVS_111021_LR - completeness (79.43%)
MVS_Test
MVS_Test - accuracy (78.85%)
MVS_Test - completeness (79.30%)
NCCC
NCCC - accuracy (90.64%)
NCCC - completeness (92.34%)
new-patchmatchnet
new-patchmatchnet - accuracy (76.98%)
new-patchmatchnet - completeness (53.05%)
new_pmnet
new_pmnet - accuracy (58.89%)
new_pmnet - completeness (27.55%)
NR-MVSNet
NR-MVSNet - accuracy (83.91%)
NR-MVSNet - completeness (71.96%)
N_pmnet
N_pmnet - accuracy (66.37%)
N_pmnet - completeness (54.72%)
OMC-MVS
OMC-MVS - accuracy (86.85%)
OMC-MVS - completeness (79.56%)
OpenMVS
OpenMVS - accuracy (80.46%)
OpenMVS - completeness (90.10%)
OPM-MVS
OPM-MVS - accuracy (90.86%)
OPM-MVS - completeness (85.30%)
our_test_3
our_test_3 - accuracy (73.27%)
our_test_3 - completeness (63.32%)
PatchMatch-RL
PatchMatch-RL - accuracy (77.84%)
PatchMatch-RL - completeness (68.74%)
PatchmatchNet
PatchmatchNet - accuracy (69.21%)
PatchmatchNet - completeness (73.49%)
PatchT
PatchT - accuracy (55.87%)
PatchT - completeness (65.95%)
PCF-MVS
PCF-MVS - accuracy (86.12%)
PCF-MVS - completeness (83.67%)
PEN-MVS
PEN-MVS - accuracy (92.92%)
PEN-MVS - completeness (61.45%)
PGM-MVS
PGM-MVS - accuracy (91.77%)
PGM-MVS - completeness (88.38%)
PHI-MVS
PHI-MVS - accuracy (86.65%)
PHI-MVS - completeness (86.15%)
PLC
PLC - accuracy (85.79%)
PLC - completeness (80.28%)
PM-MVS
PM-MVS - accuracy (78.04%)
PM-MVS - completeness (47.23%)
pm-mvs1
pm-mvs1 - accuracy (80.38%)
pm-mvs1 - completeness (67.97%)
PMMVS
PMMVS - accuracy (45.03%)
PMMVS - completeness (71.46%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (80.05%)
pmmvs-eth3d - completeness (57.34%)
PMMVS2
PMMVS2 - accuracy (44.06%)
PMMVS2 - completeness (20.52%)
pmmvs3
pmmvs3 - accuracy (50.74%)
pmmvs3 - completeness (39.80%)
pmmvs5
pmmvs5 - accuracy (67.45%)
pmmvs5 - completeness (62.77%)
pmmvs6
pmmvs6 - accuracy (81.96%)
pmmvs6 - completeness (63.22%)
pmnet_mix02
pmnet_mix02 - accuracy (66.56%)
pmnet_mix02 - completeness (61.89%)
PMVS
PMVS - accuracy (90.16%)
PMVS - completeness (48.33%)
PS-CasMVS
PS-CasMVS - accuracy (92.44%)
PS-CasMVS - completeness (58.60%)
PVSNet_Blended
PVSNet_Blended - accuracy (76.76%)
PVSNet_Blended - completeness (82.37%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (76.76%)
PVSNet_BlendedMVS - completeness (82.37%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (82.17%)
PVSNet_Blended_VisFu - completeness (79.01%)
QAPM
QAPM - accuracy (79.40%)
QAPM - completeness (91.52%)
RPMNet
RPMNet - accuracy (71.55%)
RPMNet - completeness (67.59%)
RPSCF
RPSCF - accuracy (84.24%)
RPSCF - completeness (48.87%)
SCA
SCA - accuracy (67.79%)
SCA - completeness (73.75%)
SD-MVS
SD-MVS - accuracy (91.31%)
SD-MVS - completeness (88.98%)
SED-MVS
SED-MVS - accuracy (88.64%)
SED-MVS - completeness (92.53%)
SF-MVS
SF-MVS - accuracy (88.17%)
SF-MVS - completeness (94.57%)
SMA-MVS
SMA-MVS - accuracy (91.68%)
SMA-MVS - completeness (91.74%)
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 (91.82%)
SR-MVS - completeness (86.33%)
SteuartSystems-ACMMP
SteuartSystems-ACMMP - accuracy (91.21%)
SteuartSystems-ACMMP - completeness (90.25%)
TAMVS
TAMVS - accuracy (70.12%)
TAMVS - completeness (62.38%)
TAPA-MVS
TAPA-MVS - accuracy (84.69%)
TAPA-MVS - completeness (77.04%)
TDRefinement
TDRefinement - accuracy (88.79%)
TDRefinement - completeness (57.41%)
test-mter
test-mter - accuracy (53.21%)
test-mter - completeness (59.07%)
test1
test1 - accuracy (76.76%)
test1 - completeness (69.49%)
test123
test123 - accuracy (0.39%)
test123 - completeness (0.00%)
testgi
testgi - accuracy (79.99%)
testgi - completeness (64.78%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (50.95%)
TESTMET0.1,1 - completeness (66.05%)
testmvs
testmvs - accuracy (0.36%)
testmvs - completeness (0.00%)
test_part1
test_part1 - accuracy (87.23%)
test_part1 - completeness (77.40%)
thisisatest0515
thisisatest0515 - accuracy (76.73%)
thisisatest0515 - completeness (64.39%)
thisisatest0530
thisisatest0530 - accuracy (75.08%)
thisisatest0530 - completeness (72.61%)
TinyColmap
TinyColmap - accuracy (83.42%)
TinyColmap - completeness (59.72%)
tmp_tt
tmp_tt - accuracy (16.73%)
tmp_tt - completeness (13.07%)
tpm
tpm - accuracy (70.09%)
tpm - completeness (74.52%)
tpm cat1
tpm cat1 - accuracy (74.61%)
tpm cat1 - completeness (76.63%)
tpmrst
tpmrst - accuracy (67.56%)
tpmrst - completeness (76.21%)
train_agg
train_agg - accuracy (91.51%)
train_agg - completeness (89.70%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (88.78%)
TranMVSNet+NR-MVSNet - completeness (68.34%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (83.32%)
TransMVSNet (Re) - completeness (72.26%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (89.27%)
TSAR-MVS + ACMM - completeness (89.82%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (86.05%)
TSAR-MVS + COLMAP - completeness (74.97%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (90.07%)
TSAR-MVS + GP. - completeness (80.72%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (91.53%)
TSAR-MVS + MP. - completeness (88.09%)
tttt0517
tttt0517 - accuracy (75.55%)
tttt0517 - completeness (71.94%)
UA-Net
UA-Net - accuracy (94.88%)
UA-Net - completeness (77.53%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (73.52%)
UGNet - completeness (69.88%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (87.82%)
UniMVSNet (Re) - completeness (67.64%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (90.48%)
UniMVSNet_ETH3D - completeness (63.24%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (88.18%)
UniMVSNet_NR-MVSNet - completeness (69.48%)
USDC
USDC - accuracy (81.48%)
USDC - completeness (64.04%)
Vis-MVSNet
Vis-MVSNet - accuracy (77.91%)
Vis-MVSNet - completeness (70.80%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (83.66%)
Vis-MVSNet (Re-imp) - completeness (73.70%)
WR-MVS_H
WR-MVS_H - accuracy (91.92%)
WR-MVS_H - completeness (58.80%)
X-MVS
X-MVS - accuracy (91.50%)
X-MVS - completeness (87.99%)
X-MVStestdata
X-MVStestdata - accuracy (91.28%)
X-MVStestdata - completeness (82.43%)
XVS
XVS - accuracy (91.28%)
XVS - completeness (82.43%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (88.17%)
xxxxxxxxxxxxxcwj - completeness (94.57%)
zzz-MVS
zzz-MVS - accuracy (93.08%)
zzz-MVS - completeness (88.14%)
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
:
-5.75 to 52.47
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
:
40.3
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