+
−
⇧
i
D
T
relief (high-res multi-view) - Tolerance 5cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (95.26%)
3Dnovator - completeness (90.99%)
3Dnovator+
3Dnovator+ - accuracy (96.68%)
3Dnovator+ - completeness (91.51%)
ACMH
ACMH - accuracy (98.35%)
ACMH - completeness (78.91%)
ACMH+
ACMH+ - accuracy (98.67%)
ACMH+ - completeness (76.06%)
ACMM
ACMM - accuracy (98.07%)
ACMM - completeness (84.33%)
ACMMP
ACMMP - accuracy (97.99%)
ACMMP - completeness (88.16%)
ACMMPR
ACMMPR - accuracy (97.85%)
ACMMPR - completeness (90.24%)
ACMMP_NAP
ACMMP_NAP - accuracy (97.87%)
ACMMP_NAP - completeness (93.30%)
ACMP
ACMP - accuracy (98.04%)
ACMP - completeness (82.88%)
AdaColmap
AdaColmap - accuracy (95.82%)
AdaColmap - completeness (86.31%)
ADS-MVSNet
ADS-MVSNet - accuracy (78.70%)
ADS-MVSNet - completeness (76.01%)
ambc
ambc - accuracy (94.70%)
ambc - completeness (72.83%)
Anonymous20231206
Anonymous20231206 - accuracy (89.72%)
Anonymous20231206 - completeness (77.33%)
Anonymous202405211
Anonymous202405211 - accuracy (96.47%)
Anonymous202405211 - completeness (83.55%)
anonymousdsp
anonymousdsp - accuracy (97.77%)
anonymousdsp - completeness (77.99%)
APD-MVS
APD-MVS - accuracy (97.24%)
APD-MVS - completeness (92.06%)
APDe-MVS
APDe-MVS - accuracy (97.79%)
APDe-MVS - completeness (93.01%)
baseline1
baseline1 - accuracy (91.80%)
baseline1 - completeness (91.32%)
baseline2
baseline2 - accuracy (88.21%)
baseline2 - completeness (89.61%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (97.03%)
Baseline_NR-MVSNet - completeness (78.67%)
CANet
CANet - accuracy (94.33%)
CANet - completeness (94.52%)
CANet_DTU
CANet_DTU - accuracy (91.44%)
CANet_DTU - completeness (92.63%)
canonicalmvs
canonicalmvs - accuracy (95.74%)
canonicalmvs - completeness (87.02%)
casdiffmvs
casdiffmvs - accuracy (93.21%)
casdiffmvs - completeness (90.55%)
CDPH-MVS
CDPH-MVS - accuracy (95.57%)
CDPH-MVS - completeness (90.81%)
CDS-MVSNet
CDS-MVSNet - accuracy (93.17%)
CDS-MVSNet - completeness (86.26%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (85.64%)
CHOSEN 1792x2688 - completeness (92.35%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (88.61%)
CHOSEN 280x420 - completeness (89.53%)
CLD-MVS
CLD-MVS - accuracy (95.35%)
CLD-MVS - completeness (87.33%)
CMPMVS
CMPMVS - accuracy (92.56%)
CMPMVS - completeness (70.84%)
CNLPA
CNLPA - accuracy (95.41%)
CNLPA - completeness (84.19%)
CNVR-MVS
CNVR-MVS - accuracy (96.34%)
CNVR-MVS - completeness (95.20%)
COLMAP_ROB
COLMAP_ROB - accuracy (98.76%)
COLMAP_ROB - completeness (74.96%)
CostFormer
CostFormer - accuracy (77.50%)
CostFormer - completeness (82.58%)
CP-MVS
CP-MVS - accuracy (98.00%)
CP-MVS - completeness (89.65%)
CP-MVSNet
CP-MVSNet - accuracy (98.93%)
CP-MVSNet - completeness (72.26%)
CPTT-MVS
CPTT-MVS - accuracy (96.96%)
CPTT-MVS - completeness (85.42%)
CR-MVSNet
CR-MVSNet - accuracy (83.76%)
CR-MVSNet - completeness (86.48%)
CS-MVS
CS-MVS - accuracy (95.84%)
CS-MVS - completeness (92.72%)
CSCG
CSCG - accuracy (97.17%)
CSCG - completeness (87.82%)
CVMVSNet
CVMVSNet - accuracy (91.19%)
CVMVSNet - completeness (78.33%)
DCV-MVSNet
DCV-MVSNet - accuracy (97.65%)
DCV-MVSNet - completeness (82.89%)
DeepC-MVS
DeepC-MVS - accuracy (96.81%)
DeepC-MVS - completeness (92.44%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (95.73%)
DeepC-MVS_fast - completeness (94.62%)
DeepMVS_CX
DeepMVS_CX - accuracy (64.27%)
DeepMVS_CX - completeness (38.92%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (95.22%)
DeepPCF-MVS - completeness (95.02%)
DELS-MVS
DELS-MVS - accuracy (94.44%)
DELS-MVS - completeness (95.38%)
diffmvs
diffmvs - accuracy (90.01%)
diffmvs - completeness (87.90%)
DPE-MVS
DPE-MVS - accuracy (97.49%)
DPE-MVS - completeness (93.68%)
DPM-MVS
DPM-MVS - accuracy (90.46%)
DPM-MVS - completeness (96.54%)
dps
dps - accuracy (81.13%)
dps - completeness (77.89%)
DTE-MVSNet
DTE-MVSNet - accuracy (98.97%)
DTE-MVSNet - completeness (70.83%)
DU-MVS
DU-MVS - accuracy (97.03%)
DU-MVS - completeness (78.67%)
DVP-MVS
DVP-MVS - accuracy (97.74%)
DVP-MVS - completeness (94.22%)
E-PMN
E-PMN - accuracy (90.02%)
E-PMN - completeness (16.13%)
Effi-MVS+
Effi-MVS+ - accuracy (93.72%)
Effi-MVS+ - completeness (88.41%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (94.23%)
Effi-MVS+-dtu - completeness (80.19%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (96.89%)
EG-PatchMatch MVS - completeness (81.00%)
EIA-MVS
EIA-MVS - accuracy (95.67%)
EIA-MVS - completeness (89.69%)
EMVS
EMVS - accuracy (89.48%)
EMVS - completeness (14.56%)
EPMVS
EPMVS - accuracy (78.17%)
EPMVS - completeness (80.59%)
EPNet
EPNet - accuracy (92.30%)
EPNet - completeness (92.13%)
EPNet_dtu
EPNet_dtu - accuracy (89.07%)
EPNet_dtu - completeness (85.44%)
EPP-MVSNet
EPP-MVSNet - accuracy (97.61%)
EPP-MVSNet - completeness (85.63%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (91.72%)
ET-MVSNet_ETH3D - completeness (84.14%)
ETV-MVS
ETV-MVS - accuracy (97.07%)
ETV-MVS - completeness (92.20%)
EU-MVSNet
EU-MVSNet - accuracy (94.10%)
EU-MVSNet - completeness (68.27%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (94.90%)
Fast-Effi-MVS+ - completeness (86.47%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (90.84%)
Fast-Effi-MVS+-dtu - completeness (81.90%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (97.82%)
FC-MVSNet-test - completeness (77.60%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (96.89%)
FC-MVSNet-train - completeness (86.20%)
FMVSNet1
FMVSNet1 - accuracy (95.32%)
FMVSNet1 - completeness (86.57%)
FMVSNet2
FMVSNet2 - accuracy (91.64%)
FMVSNet2 - completeness (90.10%)
FMVSNet3
FMVSNet3 - accuracy (88.03%)
FMVSNet3 - completeness (91.49%)
FMVSNet5
FMVSNet5 - accuracy (90.17%)
FMVSNet5 - completeness (81.95%)
FPMVS
FPMVS - accuracy (96.42%)
FPMVS - completeness (50.98%)
GA-MVS
GA-MVS - accuracy (89.41%)
GA-MVS - completeness (89.39%)
GBi-Net
GBi-Net - accuracy (95.32%)
GBi-Net - completeness (86.57%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (83.73%)
GG-mvs-BLEND - completeness (88.98%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (91.04%)
gg-mvs-nofinetune - completeness (94.30%)
Gipuma
Gipuma - accuracy (98.02%)
Gipuma - completeness (53.60%)
gm-plane-assit
gm-plane-assit - accuracy (88.02%)
gm-plane-assit - completeness (95.12%)
HFP-MVS
HFP-MVS - accuracy (97.28%)
HFP-MVS - completeness (90.81%)
HPM-MVS++
HPM-MVS++ - accuracy (96.01%)
HPM-MVS++ - completeness (94.22%)
HQP-MVS
HQP-MVS - accuracy (92.26%)
HQP-MVS - completeness (89.12%)
HyFIR lowres test
HyFIR lowres test - accuracy (85.40%)
HyFIR lowres test - completeness (88.77%)
IB-MVS
IB-MVS - accuracy (93.48%)
IB-MVS - completeness (79.01%)
IS_MVSNet
IS_MVSNet - accuracy (97.29%)
IS_MVSNet - completeness (90.88%)
IterMVS
IterMVS - accuracy (87.38%)
IterMVS - completeness (83.15%)
IterMVS-LS
IterMVS-LS - accuracy (89.60%)
IterMVS-LS - completeness (83.48%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (89.02%)
IterMVS-SCA-FT - completeness (82.83%)
LGP-MVS_train
LGP-MVS_train - accuracy (98.11%)
LGP-MVS_train - completeness (85.20%)
LS3D
LS3D - accuracy (98.48%)
LS3D - completeness (82.07%)
LTVRE_ROB
LTVRE_ROB - accuracy (99.24%)
LTVRE_ROB - completeness (75.10%)
MAR-MVS
MAR-MVS - accuracy (95.16%)
MAR-MVS - completeness (89.40%)
MCST-MVS
MCST-MVS - accuracy (93.94%)
MCST-MVS - completeness (95.05%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (96.87%)
MDA-MVSNet-bldmvs - completeness (48.85%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (80.29%)
MDTV_nov1_ep13 - completeness (80.93%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (87.29%)
MDTV_nov1_ep13_2view - completeness (71.85%)
MIMVSNet
MIMVSNet - accuracy (88.26%)
MIMVSNet - completeness (84.86%)
MIMVSNet1
MIMVSNet1 - accuracy (96.08%)
MIMVSNet1 - completeness (70.49%)
MP-MVS
MP-MVS - accuracy (97.75%)
MP-MVS - completeness (90.58%)
MS-PatchMatch
MS-PatchMatch - accuracy (89.39%)
MS-PatchMatch - completeness (86.71%)
MSDG
MSDG - accuracy (94.91%)
MSDG - completeness (81.95%)
MSLP-MVS++
MSLP-MVS++ - accuracy (96.57%)
MSLP-MVS++ - completeness (89.45%)
MSP-MVS
MSP-MVS - accuracy (94.37%)
MSP-MVS - completeness (95.24%)
MVE
MVE - accuracy (86.17%)
MVE - completeness (27.45%)
MVS-HIRNet
MVS-HIRNet - accuracy (77.81%)
MVS-HIRNet - completeness (78.28%)
MVSTER
MVSTER - accuracy (90.77%)
MVSTER - completeness (93.53%)
MVS_0304
MVS_0304 - accuracy (94.65%)
MVS_0304 - completeness (94.64%)
MVS_111021_LR
MVS_111021_LR - accuracy (95.11%)
MVS_111021_LR - completeness (90.03%)
MVS_Test
MVS_Test - accuracy (88.69%)
MVS_Test - completeness (91.71%)
NCCC
NCCC - accuracy (95.89%)
NCCC - completeness (93.90%)
new-patchmatchnet
new-patchmatchnet - accuracy (90.35%)
new-patchmatchnet - completeness (61.52%)
new_pmnet
new_pmnet - accuracy (86.59%)
new_pmnet - completeness (61.12%)
NR-MVSNet
NR-MVSNet - accuracy (96.87%)
NR-MVSNet - completeness (81.40%)
N_pmnet
N_pmnet - accuracy (84.23%)
N_pmnet - completeness (67.07%)
OMC-MVS
OMC-MVS - accuracy (96.15%)
OMC-MVS - completeness (87.62%)
OpenMVS
OpenMVS - accuracy (94.07%)
OpenMVS - completeness (88.47%)
OPM-MVS
OPM-MVS - accuracy (97.09%)
OPM-MVS - completeness (87.77%)
PatchMatch-RL
PatchMatch-RL - accuracy (93.23%)
PatchMatch-RL - completeness (84.06%)
PatchmatchNet
PatchmatchNet - accuracy (78.58%)
PatchmatchNet - completeness (79.92%)
PatchT
PatchT - accuracy (83.76%)
PatchT - completeness (86.48%)
PCF-MVS
PCF-MVS - accuracy (91.32%)
PCF-MVS - completeness (85.92%)
PEN-MVS
PEN-MVS - accuracy (98.98%)
PEN-MVS - completeness (71.06%)
PGM-MVS
PGM-MVS - accuracy (97.68%)
PGM-MVS - completeness (89.88%)
PHI-MVS
PHI-MVS - accuracy (96.97%)
PHI-MVS - completeness (91.82%)
PLC
PLC - accuracy (95.05%)
PLC - completeness (85.48%)
PM-MVS
PM-MVS - accuracy (93.65%)
PM-MVS - completeness (72.58%)
pm-mvs1
pm-mvs1 - accuracy (96.44%)
pm-mvs1 - completeness (84.00%)
PMMVS
PMMVS - accuracy (86.59%)
PMMVS - completeness (88.05%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (90.20%)
pmmvs-eth3d - completeness (75.78%)
PMMVS2
PMMVS2 - accuracy (88.70%)
PMMVS2 - completeness (40.11%)
pmmvs3
pmmvs3 - accuracy (87.48%)
pmmvs3 - completeness (67.28%)
pmmvs5
pmmvs5 - accuracy (87.33%)
pmmvs5 - completeness (83.93%)
pmmvs6
pmmvs6 - accuracy (97.88%)
pmmvs6 - completeness (77.88%)
pmnet_mix02
pmnet_mix02 - accuracy (85.17%)
pmnet_mix02 - completeness (69.92%)
PMVS
PMVS - accuracy (98.89%)
PMVS - completeness (48.49%)
PS-CasMVS
PS-CasMVS - accuracy (99.04%)
PS-CasMVS - completeness (71.98%)
PVSNet_Blended
PVSNet_Blended - accuracy (92.64%)
PVSNet_Blended - completeness (93.46%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (92.64%)
PVSNet_BlendedMVS - completeness (93.46%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (94.69%)
PVSNet_Blended_VisFu - completeness (91.31%)
QAPM
QAPM - accuracy (94.54%)
QAPM - completeness (89.93%)
RPMNet
RPMNet - accuracy (81.88%)
RPMNet - completeness (83.55%)
RPSCF
RPSCF - accuracy (98.28%)
RPSCF - completeness (71.05%)
SCA
SCA - accuracy (80.50%)
SCA - completeness (80.48%)
SD-MVS
SD-MVS - accuracy (96.79%)
SD-MVS - completeness (92.74%)
SED-MVS
SED-MVS - accuracy (97.74%)
SED-MVS - completeness (94.32%)
SF-MVS
SF-MVS - accuracy (96.62%)
SF-MVS - completeness (92.29%)
SMA-MVS
SMA-MVS - accuracy (97.53%)
SMA-MVS - completeness (94.31%)
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 (98.01%)
SteuartSystems-ACMMP - completeness (93.07%)
TAMVS
TAMVS - accuracy (88.72%)
TAMVS - completeness (81.37%)
TAPA-MVS
TAPA-MVS - accuracy (94.33%)
TAPA-MVS - completeness (86.26%)
TDRefinement
TDRefinement - accuracy (99.24%)
TDRefinement - completeness (74.69%)
test-mter
test-mter - accuracy (83.41%)
test-mter - completeness (85.98%)
test1
test1 - accuracy (95.32%)
test1 - completeness (86.57%)
test123
test123 - accuracy (2.58%)
test123 - completeness (0.23%)
testgi
testgi - accuracy (91.90%)
testgi - completeness (77.46%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (82.32%)
TESTMET0.1,1 - completeness (87.02%)
testmvs
testmvs - accuracy (3.49%)
testmvs - completeness (0.82%)
test_part1
test_part1 - accuracy (98.84%)
test_part1 - completeness (78.96%)
thisisatest0515
thisisatest0515 - accuracy (94.58%)
thisisatest0515 - completeness (83.15%)
thisisatest0530
thisisatest0530 - accuracy (93.37%)
thisisatest0530 - completeness (88.73%)
TinyColmap
TinyColmap - accuracy (95.31%)
TinyColmap - completeness (76.91%)
tmp_tt
tmp_tt - accuracy (61.75%)
tmp_tt - completeness (52.23%)
tpm
tpm - accuracy (80.50%)
tpm - completeness (79.10%)
tpm cat1
tpm cat1 - accuracy (73.43%)
tpm cat1 - completeness (77.90%)
tpmrst
tpmrst - accuracy (73.04%)
tpmrst - completeness (80.85%)
train_agg
train_agg - accuracy (94.78%)
train_agg - completeness (92.02%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (97.27%)
TranMVSNet+NR-MVSNet - completeness (78.28%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (96.75%)
TransMVSNet (Re) - completeness (80.85%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (96.60%)
TSAR-MVS + ACMM - completeness (92.97%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (93.24%)
TSAR-MVS + COLMAP - completeness (89.79%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (96.36%)
TSAR-MVS + GP. - completeness (90.40%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (98.09%)
TSAR-MVS + MP. - completeness (91.79%)
tttt0517
tttt0517 - accuracy (93.71%)
tttt0517 - completeness (88.47%)
UA-Net
UA-Net - accuracy (98.43%)
UA-Net - completeness (88.54%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (95.22%)
UGNet - completeness (87.39%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (96.90%)
UniMVSNet (Re) - completeness (80.10%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (98.51%)
UniMVSNet_ETH3D - completeness (75.05%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (96.68%)
UniMVSNet_NR-MVSNet - completeness (79.19%)
USDC
USDC - accuracy (92.04%)
USDC - completeness (82.66%)
Vis-MVSNet
Vis-MVSNet - accuracy (96.95%)
Vis-MVSNet - completeness (88.78%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (95.88%)
Vis-MVSNet (Re-imp) - completeness (88.96%)
WR-MVS_H
WR-MVS_H - accuracy (98.91%)
WR-MVS_H - completeness (72.41%)
X-MVS
X-MVS - accuracy (97.85%)
X-MVS - completeness (89.98%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (96.62%)
xxxxxxxxxxxxxcwj - completeness (92.29%)
zzz-MVS
zzz-MVS - accuracy (98.09%)
zzz-MVS - completeness (91.60%)
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
:
-29.67 to 44.52
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
:
51.4
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