+
−
⇧
i
D
T
terrains (high-res multi-view) - Tolerance 5cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (95.40%)
3Dnovator - completeness (96.03%)
3Dnovator+
3Dnovator+ - accuracy (96.40%)
3Dnovator+ - completeness (97.30%)
ACMH
ACMH - accuracy (96.00%)
ACMH - completeness (89.33%)
ACMH+
ACMH+ - accuracy (95.79%)
ACMH+ - completeness (86.90%)
ACMM
ACMM - accuracy (96.86%)
ACMM - completeness (89.39%)
ACMMP
ACMMP - accuracy (96.99%)
ACMMP - completeness (95.86%)
ACMMPR
ACMMPR - accuracy (97.17%)
ACMMPR - completeness (96.30%)
ACMMP_NAP
ACMMP_NAP - accuracy (97.52%)
ACMMP_NAP - completeness (97.43%)
ACMP
ACMP - accuracy (96.17%)
ACMP - completeness (94.70%)
AdaColmap
AdaColmap - accuracy (92.67%)
AdaColmap - completeness (94.53%)
ADS-MVSNet
ADS-MVSNet - accuracy (74.07%)
ADS-MVSNet - completeness (85.86%)
ambc
ambc - accuracy (93.67%)
ambc - completeness (77.61%)
Anonymous20231206
Anonymous20231206 - accuracy (83.81%)
Anonymous20231206 - completeness (83.49%)
Anonymous202405211
Anonymous202405211 - accuracy (92.85%)
Anonymous202405211 - completeness (95.75%)
anonymousdsp
anonymousdsp - accuracy (97.69%)
anonymousdsp - completeness (93.75%)
APD-MVS
APD-MVS - accuracy (95.96%)
APD-MVS - completeness (98.60%)
APDe-MVS
APDe-MVS - accuracy (97.08%)
APDe-MVS - completeness (99.29%)
baseline1
baseline1 - accuracy (87.35%)
baseline1 - completeness (89.85%)
baseline2
baseline2 - accuracy (85.39%)
baseline2 - completeness (96.81%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (93.67%)
Baseline_NR-MVSNet - completeness (92.62%)
CANet
CANet - accuracy (93.58%)
CANet - completeness (98.58%)
CANet_DTU
CANet_DTU - accuracy (89.83%)
CANet_DTU - completeness (94.46%)
canonicalmvs
canonicalmvs - accuracy (97.13%)
canonicalmvs - completeness (96.95%)
casdiffmvs
casdiffmvs - accuracy (91.76%)
casdiffmvs - completeness (97.14%)
CDPH-MVS
CDPH-MVS - accuracy (94.72%)
CDPH-MVS - completeness (96.99%)
CDS-MVSNet
CDS-MVSNet - accuracy (87.63%)
CDS-MVSNet - completeness (93.97%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (86.68%)
CHOSEN 1792x2688 - completeness (98.86%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (80.03%)
CHOSEN 280x420 - completeness (95.71%)
CLD-MVS
CLD-MVS - accuracy (92.34%)
CLD-MVS - completeness (97.83%)
CMPMVS
CMPMVS - accuracy (92.56%)
CMPMVS - completeness (72.45%)
CNLPA
CNLPA - accuracy (93.37%)
CNLPA - completeness (94.26%)
CNVR-MVS
CNVR-MVS - accuracy (95.88%)
CNVR-MVS - completeness (99.01%)
COLMAP_ROB
COLMAP_ROB - accuracy (96.67%)
COLMAP_ROB - completeness (75.57%)
CostFormer
CostFormer - accuracy (82.02%)
CostFormer - completeness (96.90%)
CP-MVS
CP-MVS - accuracy (97.05%)
CP-MVS - completeness (97.13%)
CP-MVSNet
CP-MVSNet - accuracy (96.91%)
CP-MVSNet - completeness (89.75%)
CPTT-MVS
CPTT-MVS - accuracy (96.18%)
CPTT-MVS - completeness (96.72%)
CR-MVSNet
CR-MVSNet - accuracy (83.14%)
CR-MVSNet - completeness (93.92%)
CS-MVS
CS-MVS - accuracy (92.05%)
CS-MVS - completeness (98.03%)
CSCG
CSCG - accuracy (97.78%)
CSCG - completeness (98.01%)
CVMVSNet
CVMVSNet - accuracy (91.78%)
CVMVSNet - completeness (84.44%)
DCV-MVSNet
DCV-MVSNet - accuracy (95.95%)
DCV-MVSNet - completeness (94.30%)
DeepC-MVS
DeepC-MVS - accuracy (96.27%)
DeepC-MVS - completeness (98.10%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (95.13%)
DeepC-MVS_fast - completeness (97.88%)
DeepMVS_CX
DeepMVS_CX - accuracy (72.72%)
DeepMVS_CX - completeness (53.31%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (95.75%)
DeepPCF-MVS - completeness (99.48%)
DELS-MVS
DELS-MVS - accuracy (92.97%)
DELS-MVS - completeness (99.27%)
diffmvs
diffmvs - accuracy (91.00%)
diffmvs - completeness (97.82%)
DPE-MVS
DPE-MVS - accuracy (97.16%)
DPE-MVS - completeness (99.37%)
DPM-MVS
DPM-MVS - accuracy (93.77%)
DPM-MVS - completeness (93.94%)
dps
dps - accuracy (77.98%)
dps - completeness (89.63%)
DTE-MVSNet
DTE-MVSNet - accuracy (96.28%)
DTE-MVSNet - completeness (85.42%)
DU-MVS
DU-MVS - accuracy (94.22%)
DU-MVS - completeness (94.37%)
DVP-MVS
DVP-MVS - accuracy (97.34%)
DVP-MVS - completeness (99.61%)
E-PMN
E-PMN - accuracy (59.85%)
E-PMN - completeness (33.77%)
Effi-MVS+
Effi-MVS+ - accuracy (92.79%)
Effi-MVS+ - completeness (95.80%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (93.23%)
Effi-MVS+-dtu - completeness (91.95%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (93.56%)
EG-PatchMatch MVS - completeness (82.67%)
EIA-MVS
EIA-MVS - accuracy (90.79%)
EIA-MVS - completeness (98.23%)
EMVS
EMVS - accuracy (58.84%)
EMVS - completeness (29.77%)
EPMVS
EPMVS - accuracy (74.37%)
EPMVS - completeness (88.17%)
EPNet
EPNet - accuracy (94.20%)
EPNet - completeness (97.01%)
EPNet_dtu
EPNet_dtu - accuracy (89.38%)
EPNet_dtu - completeness (86.22%)
EPP-MVSNet
EPP-MVSNet - accuracy (95.18%)
EPP-MVSNet - completeness (95.79%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (89.36%)
ET-MVSNet_ETH3D - completeness (94.42%)
ETV-MVS
ETV-MVS - accuracy (92.04%)
ETV-MVS - completeness (98.83%)
EU-MVSNet
EU-MVSNet - accuracy (92.24%)
EU-MVSNet - completeness (80.23%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (92.77%)
Fast-Effi-MVS+ - completeness (92.98%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (88.77%)
Fast-Effi-MVS+-dtu - completeness (94.18%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (91.05%)
FC-MVSNet-test - completeness (82.70%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (94.09%)
FC-MVSNet-train - completeness (95.31%)
FMVSNet1
FMVSNet1 - accuracy (93.93%)
FMVSNet1 - completeness (89.42%)
FMVSNet2
FMVSNet2 - accuracy (92.67%)
FMVSNet2 - completeness (90.77%)
FMVSNet3
FMVSNet3 - accuracy (92.04%)
FMVSNet3 - completeness (91.13%)
FMVSNet5
FMVSNet5 - accuracy (83.45%)
FMVSNet5 - completeness (75.20%)
FPMVS
FPMVS - accuracy (90.65%)
FPMVS - completeness (56.31%)
GA-MVS
GA-MVS - accuracy (87.90%)
GA-MVS - completeness (92.12%)
GBi-Net
GBi-Net - accuracy (92.67%)
GBi-Net - completeness (90.77%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (72.68%)
GG-mvs-BLEND - completeness (99.02%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (83.10%)
gg-mvs-nofinetune - completeness (97.05%)
Gipuma
Gipuma - accuracy (94.48%)
Gipuma - completeness (38.79%)
gm-plane-assit
gm-plane-assit - accuracy (76.69%)
gm-plane-assit - completeness (94.66%)
HFP-MVS
HFP-MVS - accuracy (97.25%)
HFP-MVS - completeness (96.94%)
HPM-MVS++
HPM-MVS++ - accuracy (96.61%)
HPM-MVS++ - completeness (98.37%)
HQP-MVS
HQP-MVS - accuracy (95.40%)
HQP-MVS - completeness (97.31%)
HyFIR lowres test
HyFIR lowres test - accuracy (81.87%)
HyFIR lowres test - completeness (97.86%)
IB-MVS
IB-MVS - accuracy (92.15%)
IB-MVS - completeness (97.47%)
IS_MVSNet
IS_MVSNet - accuracy (93.38%)
IS_MVSNet - completeness (96.62%)
IterMVS
IterMVS - accuracy (86.06%)
IterMVS - completeness (91.65%)
IterMVS-LS
IterMVS-LS - accuracy (93.16%)
IterMVS-LS - completeness (92.16%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (88.90%)
IterMVS-SCA-FT - completeness (91.49%)
LGP-MVS_train
LGP-MVS_train - accuracy (96.50%)
LGP-MVS_train - completeness (95.02%)
LS3D
LS3D - accuracy (95.49%)
LS3D - completeness (84.39%)
LTVRE_ROB
LTVRE_ROB - accuracy (98.70%)
LTVRE_ROB - completeness (87.24%)
MAR-MVS
MAR-MVS - accuracy (94.53%)
MAR-MVS - completeness (93.88%)
MCST-MVS
MCST-MVS - accuracy (95.13%)
MCST-MVS - completeness (99.20%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (85.72%)
MDA-MVSNet-bldmvs - completeness (73.88%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (75.83%)
MDTV_nov1_ep13 - completeness (89.05%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (79.46%)
MDTV_nov1_ep13_2view - completeness (82.82%)
MIMVSNet
MIMVSNet - accuracy (81.24%)
MIMVSNet - completeness (81.10%)
MIMVSNet1
MIMVSNet1 - accuracy (90.22%)
MIMVSNet1 - completeness (68.51%)
MP-MVS
MP-MVS - accuracy (96.88%)
MP-MVS - completeness (97.44%)
MS-PatchMatch
MS-PatchMatch - accuracy (88.34%)
MS-PatchMatch - completeness (84.23%)
MSDG
MSDG - accuracy (89.15%)
MSDG - completeness (82.91%)
MSLP-MVS++
MSLP-MVS++ - accuracy (96.29%)
MSLP-MVS++ - completeness (97.24%)
MSP-MVS
MSP-MVS - accuracy (96.40%)
MSP-MVS - completeness (99.64%)
MVE
MVE - accuracy (80.38%)
MVE - completeness (40.74%)
MVS-HIRNet
MVS-HIRNet - accuracy (66.73%)
MVS-HIRNet - completeness (79.52%)
MVSTER
MVSTER - accuracy (90.19%)
MVSTER - completeness (95.55%)
MVS_0304
MVS_0304 - accuracy (94.71%)
MVS_0304 - completeness (97.64%)
MVS_111021_LR
MVS_111021_LR - accuracy (92.74%)
MVS_111021_LR - completeness (96.74%)
MVS_Test
MVS_Test - accuracy (91.85%)
MVS_Test - completeness (95.27%)
NCCC
NCCC - accuracy (95.63%)
NCCC - completeness (98.22%)
new-patchmatchnet
new-patchmatchnet - accuracy (81.05%)
new-patchmatchnet - completeness (72.14%)
new_pmnet
new_pmnet - accuracy (75.02%)
new_pmnet - completeness (65.03%)
NR-MVSNet
NR-MVSNet - accuracy (93.98%)
NR-MVSNet - completeness (93.75%)
N_pmnet
N_pmnet - accuracy (73.25%)
N_pmnet - completeness (76.10%)
OMC-MVS
OMC-MVS - accuracy (94.80%)
OMC-MVS - completeness (93.11%)
OpenMVS
OpenMVS - accuracy (94.02%)
OpenMVS - completeness (95.48%)
OPM-MVS
OPM-MVS - accuracy (95.78%)
OPM-MVS - completeness (91.75%)
PatchMatch-RL
PatchMatch-RL - accuracy (85.60%)
PatchMatch-RL - completeness (87.97%)
PatchmatchNet
PatchmatchNet - accuracy (74.69%)
PatchmatchNet - completeness (90.29%)
PatchT
PatchT - accuracy (83.14%)
PatchT - completeness (93.92%)
PCF-MVS
PCF-MVS - accuracy (93.86%)
PCF-MVS - completeness (97.43%)
PEN-MVS
PEN-MVS - accuracy (96.83%)
PEN-MVS - completeness (87.68%)
PGM-MVS
PGM-MVS - accuracy (96.97%)
PGM-MVS - completeness (95.86%)
PHI-MVS
PHI-MVS - accuracy (94.84%)
PHI-MVS - completeness (97.51%)
PLC
PLC - accuracy (92.80%)
PLC - completeness (88.21%)
PM-MVS
PM-MVS - accuracy (91.85%)
PM-MVS - completeness (84.55%)
pm-mvs1
pm-mvs1 - accuracy (93.21%)
pm-mvs1 - completeness (89.42%)
PMMVS
PMMVS - accuracy (80.41%)
PMMVS - completeness (93.98%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (88.89%)
pmmvs-eth3d - completeness (83.39%)
PMMVS2
PMMVS2 - accuracy (67.17%)
PMMVS2 - completeness (53.54%)
pmmvs3
pmmvs3 - accuracy (79.18%)
pmmvs3 - completeness (75.20%)
pmmvs5
pmmvs5 - accuracy (86.76%)
pmmvs5 - completeness (90.42%)
pmmvs6
pmmvs6 - accuracy (94.79%)
pmmvs6 - completeness (86.70%)
pmnet_mix02
pmnet_mix02 - accuracy (79.51%)
pmnet_mix02 - completeness (82.29%)
PMVS
PMVS - accuracy (94.71%)
PMVS - completeness (52.53%)
PS-CasMVS
PS-CasMVS - accuracy (97.24%)
PS-CasMVS - completeness (89.29%)
PVSNet_Blended
PVSNet_Blended - accuracy (90.61%)
PVSNet_Blended - completeness (99.53%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (90.61%)
PVSNet_BlendedMVS - completeness (99.53%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (94.54%)
PVSNet_Blended_VisFu - completeness (98.85%)
QAPM
QAPM - accuracy (95.37%)
QAPM - completeness (97.44%)
RPMNet
RPMNet - accuracy (82.87%)
RPMNet - completeness (94.71%)
RPSCF
RPSCF - accuracy (97.13%)
RPSCF - completeness (77.37%)
SCA
SCA - accuracy (76.80%)
SCA - completeness (90.20%)
SD-MVS
SD-MVS - accuracy (97.09%)
SD-MVS - completeness (99.07%)
SED-MVS
SED-MVS - accuracy (97.34%)
SED-MVS - completeness (99.58%)
SF-MVS
SF-MVS - accuracy (96.13%)
SF-MVS - completeness (98.44%)
SMA-MVS
SMA-MVS - accuracy (97.67%)
SMA-MVS - completeness (98.53%)
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 (97.25%)
SteuartSystems-ACMMP - completeness (98.30%)
TAMVS
TAMVS - accuracy (79.38%)
TAMVS - completeness (86.99%)
TAPA-MVS
TAPA-MVS - accuracy (95.40%)
TAPA-MVS - completeness (89.90%)
TDRefinement
TDRefinement - accuracy (97.77%)
TDRefinement - completeness (79.20%)
test-mter
test-mter - accuracy (81.24%)
test-mter - completeness (96.71%)
test1
test1 - accuracy (92.67%)
test1 - completeness (90.77%)
test123
test123 - accuracy (4.00%)
test123 - completeness (3.76%)
testgi
testgi - accuracy (83.84%)
testgi - completeness (74.86%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (78.87%)
TESTMET0.1,1 - completeness (97.02%)
testmvs
testmvs - accuracy (3.92%)
testmvs - completeness (3.62%)
test_part1
test_part1 - accuracy (97.60%)
test_part1 - completeness (92.55%)
thisisatest0515
thisisatest0515 - accuracy (94.58%)
thisisatest0515 - completeness (90.99%)
thisisatest0530
thisisatest0530 - accuracy (93.71%)
thisisatest0530 - completeness (93.80%)
TinyColmap
TinyColmap - accuracy (89.10%)
TinyColmap - completeness (76.41%)
tpm
tpm - accuracy (80.15%)
tpm - completeness (94.35%)
tpm cat1
tpm cat1 - accuracy (76.87%)
tpm cat1 - completeness (95.35%)
tpmrst
tpmrst - accuracy (73.95%)
tpmrst - completeness (95.32%)
train_agg
train_agg - accuracy (94.70%)
train_agg - completeness (98.84%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (94.31%)
TranMVSNet+NR-MVSNet - completeness (92.29%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (93.46%)
TransMVSNet (Re) - completeness (83.06%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (96.69%)
TSAR-MVS + ACMM - completeness (98.59%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (92.55%)
TSAR-MVS + COLMAP - completeness (91.09%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (95.28%)
TSAR-MVS + GP. - completeness (99.10%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (96.81%)
TSAR-MVS + MP. - completeness (99.16%)
tttt0517
tttt0517 - accuracy (94.04%)
tttt0517 - completeness (93.49%)
UA-Net
UA-Net - accuracy (98.58%)
UA-Net - completeness (83.97%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (95.19%)
UGNet - completeness (96.94%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (94.63%)
UniMVSNet (Re) - completeness (95.13%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (94.95%)
UniMVSNet_ETH3D - completeness (92.29%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (94.22%)
UniMVSNet_NR-MVSNet - completeness (94.37%)
USDC
USDC - accuracy (87.47%)
USDC - completeness (82.24%)
Vis-MVSNet
Vis-MVSNet - accuracy (96.71%)
Vis-MVSNet - completeness (92.54%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (89.08%)
Vis-MVSNet (Re-imp) - completeness (94.00%)
WR-MVS_H
WR-MVS_H - accuracy (97.19%)
WR-MVS_H - completeness (88.86%)
X-MVS
X-MVS - accuracy (96.95%)
X-MVS - completeness (96.72%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (96.13%)
xxxxxxxxxxxxxcwj - completeness (98.44%)
zzz-MVS
zzz-MVS - accuracy (96.73%)
zzz-MVS - completeness (96.97%)
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
:
-28.80 to 75.15
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
:
72.0
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