+
−
⇧
i
D
T
relief_2 (high-res multi-view) - Tolerance 5cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (94.85%)
3Dnovator - completeness (92.65%)
3Dnovator+
3Dnovator+ - accuracy (96.51%)
3Dnovator+ - completeness (91.89%)
ACMH
ACMH - accuracy (97.16%)
ACMH - completeness (81.18%)
ACMH+
ACMH+ - accuracy (97.90%)
ACMH+ - completeness (78.69%)
ACMM
ACMM - accuracy (97.45%)
ACMM - completeness (83.59%)
ACMMP
ACMMP - accuracy (97.57%)
ACMMP - completeness (86.37%)
ACMMPR
ACMMPR - accuracy (97.50%)
ACMMPR - completeness (89.82%)
ACMMP_NAP
ACMMP_NAP - accuracy (97.44%)
ACMMP_NAP - completeness (91.56%)
ACMP
ACMP - accuracy (97.14%)
ACMP - completeness (83.44%)
AdaColmap
AdaColmap - accuracy (95.07%)
AdaColmap - completeness (85.82%)
ADS-MVSNet
ADS-MVSNet - accuracy (75.56%)
ADS-MVSNet - completeness (78.14%)
ambc
ambc - accuracy (92.00%)
ambc - completeness (63.35%)
Anonymous20231206
Anonymous20231206 - accuracy (88.06%)
Anonymous20231206 - completeness (77.31%)
Anonymous202405211
Anonymous202405211 - accuracy (95.84%)
Anonymous202405211 - completeness (84.69%)
anonymousdsp
anonymousdsp - accuracy (97.41%)
anonymousdsp - completeness (81.34%)
APD-MVS
APD-MVS - accuracy (97.17%)
APD-MVS - completeness (90.70%)
APDe-MVS
APDe-MVS - accuracy (97.63%)
APDe-MVS - completeness (91.02%)
baseline1
baseline1 - accuracy (91.81%)
baseline1 - completeness (89.56%)
baseline2
baseline2 - accuracy (87.21%)
baseline2 - completeness (86.68%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (96.16%)
Baseline_NR-MVSNet - completeness (79.64%)
CANet
CANet - accuracy (93.94%)
CANet - completeness (93.78%)
CANet_DTU
CANet_DTU - accuracy (91.17%)
CANet_DTU - completeness (90.88%)
canonicalmvs
canonicalmvs - accuracy (95.75%)
canonicalmvs - completeness (91.51%)
casdiffmvs
casdiffmvs - accuracy (91.20%)
casdiffmvs - completeness (90.51%)
CDPH-MVS
CDPH-MVS - accuracy (94.81%)
CDPH-MVS - completeness (91.85%)
CDS-MVSNet
CDS-MVSNet - accuracy (92.71%)
CDS-MVSNet - completeness (87.20%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (84.95%)
CHOSEN 1792x2688 - completeness (91.64%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (81.39%)
CHOSEN 280x420 - completeness (85.01%)
CLD-MVS
CLD-MVS - accuracy (94.59%)
CLD-MVS - completeness (86.96%)
CMPMVS
CMPMVS - accuracy (89.63%)
CMPMVS - completeness (71.52%)
CNLPA
CNLPA - accuracy (93.70%)
CNLPA - completeness (84.00%)
CNVR-MVS
CNVR-MVS - accuracy (95.50%)
CNVR-MVS - completeness (94.16%)
COLMAP_ROB
COLMAP_ROB - accuracy (98.23%)
COLMAP_ROB - completeness (74.45%)
CostFormer
CostFormer - accuracy (75.28%)
CostFormer - completeness (84.50%)
CP-MVS
CP-MVS - accuracy (97.60%)
CP-MVS - completeness (88.43%)
CP-MVSNet
CP-MVSNet - accuracy (98.37%)
CP-MVSNet - completeness (76.93%)
CPTT-MVS
CPTT-MVS - accuracy (96.07%)
CPTT-MVS - completeness (84.07%)
CR-MVSNet
CR-MVSNet - accuracy (85.74%)
CR-MVSNet - completeness (84.03%)
CS-MVS
CS-MVS - accuracy (95.57%)
CS-MVS - completeness (90.05%)
CSCG
CSCG - accuracy (95.36%)
CSCG - completeness (90.59%)
CVMVSNet
CVMVSNet - accuracy (89.69%)
CVMVSNet - completeness (78.65%)
DCV-MVSNet
DCV-MVSNet - accuracy (96.87%)
DCV-MVSNet - completeness (84.56%)
DeepC-MVS
DeepC-MVS - accuracy (96.50%)
DeepC-MVS - completeness (92.79%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (95.30%)
DeepC-MVS_fast - completeness (94.83%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (94.92%)
DeepPCF-MVS - completeness (94.69%)
DELS-MVS
DELS-MVS - accuracy (93.91%)
DELS-MVS - completeness (95.93%)
diffmvs
diffmvs - accuracy (88.96%)
diffmvs - completeness (89.16%)
DPE-MVS
DPE-MVS - accuracy (97.61%)
DPE-MVS - completeness (91.73%)
DPM-MVS
DPM-MVS - accuracy (90.43%)
DPM-MVS - completeness (97.33%)
dps
dps - accuracy (77.52%)
dps - completeness (78.40%)
DTE-MVSNet
DTE-MVSNet - accuracy (98.27%)
DTE-MVSNet - completeness (76.73%)
DU-MVS
DU-MVS - accuracy (96.53%)
DU-MVS - completeness (83.10%)
DVP-MVS
DVP-MVS - accuracy (97.53%)
DVP-MVS - completeness (92.15%)
E-PMN
E-PMN - accuracy (68.30%)
E-PMN - completeness (26.16%)
Effi-MVS+
Effi-MVS+ - accuracy (94.23%)
Effi-MVS+ - completeness (86.09%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (93.65%)
Effi-MVS+-dtu - completeness (78.62%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (95.19%)
EG-PatchMatch MVS - completeness (80.95%)
EIA-MVS
EIA-MVS - accuracy (94.72%)
EIA-MVS - completeness (88.70%)
EMVS
EMVS - accuracy (67.13%)
EMVS - completeness (23.10%)
EPMVS
EPMVS - accuracy (75.08%)
EPMVS - completeness (81.43%)
EPNet
EPNet - accuracy (92.58%)
EPNet - completeness (91.12%)
EPNet_dtu
EPNet_dtu - accuracy (87.89%)
EPNet_dtu - completeness (84.91%)
EPP-MVSNet
EPP-MVSNet - accuracy (97.38%)
EPP-MVSNet - completeness (84.35%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (91.34%)
ET-MVSNet_ETH3D - completeness (89.03%)
ETV-MVS
ETV-MVS - accuracy (96.29%)
ETV-MVS - completeness (90.45%)
EU-MVSNet
EU-MVSNet - accuracy (88.94%)
EU-MVSNet - completeness (70.34%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (93.92%)
Fast-Effi-MVS+ - completeness (86.12%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (91.01%)
Fast-Effi-MVS+-dtu - completeness (82.30%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (96.13%)
FC-MVSNet-test - completeness (77.78%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (96.72%)
FC-MVSNet-train - completeness (84.08%)
FMVSNet1
FMVSNet1 - accuracy (94.98%)
FMVSNet1 - completeness (86.83%)
FMVSNet2
FMVSNet2 - accuracy (92.26%)
FMVSNet2 - completeness (89.77%)
FMVSNet3
FMVSNet3 - accuracy (89.86%)
FMVSNet3 - completeness (91.20%)
FMVSNet5
FMVSNet5 - accuracy (90.46%)
FMVSNet5 - completeness (81.69%)
FPMVS
FPMVS - accuracy (95.69%)
FPMVS - completeness (47.90%)
GA-MVS
GA-MVS - accuracy (89.27%)
GA-MVS - completeness (86.55%)
GBi-Net
GBi-Net - accuracy (94.98%)
GBi-Net - completeness (86.83%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (78.99%)
GG-mvs-BLEND - completeness (89.39%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (89.10%)
gg-mvs-nofinetune - completeness (93.03%)
Gipuma
Gipuma - accuracy (94.81%)
Gipuma - completeness (58.43%)
gm-plane-assit
gm-plane-assit - accuracy (85.95%)
gm-plane-assit - completeness (93.97%)
HFP-MVS
HFP-MVS - accuracy (97.46%)
HFP-MVS - completeness (89.83%)
HPM-MVS++
HPM-MVS++ - accuracy (95.88%)
HPM-MVS++ - completeness (92.34%)
HQP-MVS
HQP-MVS - accuracy (91.81%)
HQP-MVS - completeness (88.16%)
HyFIR lowres test
HyFIR lowres test - accuracy (87.28%)
HyFIR lowres test - completeness (88.38%)
IB-MVS
IB-MVS - accuracy (92.33%)
IB-MVS - completeness (87.89%)
IS_MVSNet
IS_MVSNet - accuracy (96.95%)
IS_MVSNet - completeness (90.05%)
IterMVS
IterMVS - accuracy (83.77%)
IterMVS - completeness (83.83%)
IterMVS-LS
IterMVS-LS - accuracy (90.94%)
IterMVS-LS - completeness (86.21%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (85.53%)
IterMVS-SCA-FT - completeness (83.70%)
LGP-MVS_train
LGP-MVS_train - accuracy (97.37%)
LGP-MVS_train - completeness (84.68%)
LS3D
LS3D - accuracy (98.05%)
LS3D - completeness (81.63%)
LTVRE_ROB
LTVRE_ROB - accuracy (98.70%)
LTVRE_ROB - completeness (78.45%)
MAR-MVS
MAR-MVS - accuracy (94.44%)
MAR-MVS - completeness (90.30%)
MCST-MVS
MCST-MVS - accuracy (92.99%)
MCST-MVS - completeness (94.02%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (86.37%)
MDA-MVSNet-bldmvs - completeness (67.34%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (76.08%)
MDTV_nov1_ep13 - completeness (83.20%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (80.29%)
MDTV_nov1_ep13_2view - completeness (74.77%)
MIMVSNet
MIMVSNet - accuracy (87.74%)
MIMVSNet - completeness (85.57%)
MIMVSNet1
MIMVSNet1 - accuracy (95.10%)
MIMVSNet1 - completeness (72.69%)
MP-MVS
MP-MVS - accuracy (97.44%)
MP-MVS - completeness (89.30%)
MS-PatchMatch
MS-PatchMatch - accuracy (89.12%)
MS-PatchMatch - completeness (82.54%)
MSDG
MSDG - accuracy (93.31%)
MSDG - completeness (82.27%)
MSLP-MVS++
MSLP-MVS++ - accuracy (96.40%)
MSLP-MVS++ - completeness (92.17%)
MSP-MVS
MSP-MVS - accuracy (97.53%)
MSP-MVS - completeness (92.15%)
MVE
MVE - accuracy (83.36%)
MVE - completeness (42.42%)
MVS-HIRNet
MVS-HIRNet - accuracy (71.65%)
MVS-HIRNet - completeness (78.81%)
MVSTER
MVSTER - accuracy (88.83%)
MVSTER - completeness (91.41%)
MVS_0304
MVS_0304 - accuracy (94.20%)
MVS_0304 - completeness (93.67%)
MVS_111021_LR
MVS_111021_LR - accuracy (93.45%)
MVS_111021_LR - completeness (88.52%)
MVS_Test
MVS_Test - accuracy (89.32%)
MVS_Test - completeness (91.90%)
NCCC
NCCC - accuracy (95.23%)
NCCC - completeness (92.98%)
new-patchmatchnet
new-patchmatchnet - accuracy (77.33%)
new-patchmatchnet - completeness (65.08%)
new_pmnet
new_pmnet - accuracy (83.26%)
new_pmnet - completeness (62.74%)
NR-MVSNet
NR-MVSNet - accuracy (96.48%)
NR-MVSNet - completeness (82.24%)
N_pmnet
N_pmnet - accuracy (74.84%)
N_pmnet - completeness (70.08%)
OMC-MVS
OMC-MVS - accuracy (95.04%)
OMC-MVS - completeness (85.95%)
OpenMVS
OpenMVS - accuracy (93.34%)
OpenMVS - completeness (89.35%)
OPM-MVS
OPM-MVS - accuracy (96.37%)
OPM-MVS - completeness (85.88%)
PatchMatch-RL
PatchMatch-RL - accuracy (92.28%)
PatchMatch-RL - completeness (82.35%)
PatchmatchNet
PatchmatchNet - accuracy (74.33%)
PatchmatchNet - completeness (81.41%)
PatchT
PatchT - accuracy (85.74%)
PatchT - completeness (84.03%)
PCF-MVS
PCF-MVS - accuracy (90.82%)
PCF-MVS - completeness (86.38%)
PEN-MVS
PEN-MVS - accuracy (98.39%)
PEN-MVS - completeness (77.65%)
PGM-MVS
PGM-MVS - accuracy (97.34%)
PGM-MVS - completeness (89.08%)
PHI-MVS
PHI-MVS - accuracy (96.69%)
PHI-MVS - completeness (92.37%)
PLC
PLC - accuracy (94.73%)
PLC - completeness (84.28%)
PM-MVS
PM-MVS - accuracy (92.91%)
PM-MVS - completeness (69.93%)
pm-mvs1
pm-mvs1 - accuracy (95.76%)
pm-mvs1 - completeness (81.14%)
PMMVS
PMMVS - accuracy (86.64%)
PMMVS - completeness (84.78%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (91.42%)
pmmvs-eth3d - completeness (75.48%)
PMMVS2
PMMVS2 - accuracy (79.34%)
PMMVS2 - completeness (47.00%)
pmmvs3
pmmvs3 - accuracy (82.42%)
pmmvs3 - completeness (70.54%)
pmmvs5
pmmvs5 - accuracy (89.07%)
pmmvs5 - completeness (81.93%)
pmmvs6
pmmvs6 - accuracy (97.03%)
pmmvs6 - completeness (76.36%)
pmnet_mix02
pmnet_mix02 - accuracy (76.44%)
pmnet_mix02 - completeness (71.67%)
PMVS
PMVS - accuracy (98.72%)
PMVS - completeness (43.82%)
PS-CasMVS
PS-CasMVS - accuracy (98.47%)
PS-CasMVS - completeness (76.69%)
PVSNet_Blended
PVSNet_Blended - accuracy (90.25%)
PVSNet_Blended - completeness (91.97%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (90.25%)
PVSNet_BlendedMVS - completeness (91.97%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (93.41%)
PVSNet_Blended_VisFu - completeness (89.72%)
QAPM
QAPM - accuracy (94.39%)
QAPM - completeness (89.91%)
RPMNet
RPMNet - accuracy (82.07%)
RPMNet - completeness (82.18%)
RPSCF
RPSCF - accuracy (97.67%)
RPSCF - completeness (69.38%)
SCA
SCA - accuracy (77.51%)
SCA - completeness (81.37%)
SD-MVS
SD-MVS - accuracy (95.89%)
SD-MVS - completeness (92.17%)
SED-MVS
SED-MVS - accuracy (97.41%)
SED-MVS - completeness (92.59%)
SF-MVS
SF-MVS - accuracy (96.44%)
SF-MVS - completeness (90.84%)
SMA-MVS
SMA-MVS - accuracy (97.19%)
SMA-MVS - completeness (93.33%)
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 (97.44%)
SteuartSystems-ACMMP - completeness (91.90%)
TAMVS
TAMVS - accuracy (87.26%)
TAMVS - completeness (82.44%)
TAPA-MVS
TAPA-MVS - accuracy (93.95%)
TAPA-MVS - completeness (84.54%)
TDRefinement
TDRefinement - accuracy (98.93%)
TDRefinement - completeness (74.64%)
test-mter
test-mter - accuracy (80.61%)
test-mter - completeness (86.26%)
test1
test1 - accuracy (94.98%)
test1 - completeness (86.83%)
test123
test123 - accuracy (3.01%)
test123 - completeness (0.72%)
testgi
testgi - accuracy (89.90%)
testgi - completeness (77.22%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (79.20%)
TESTMET0.1,1 - completeness (87.16%)
testmvs
testmvs - accuracy (2.51%)
testmvs - completeness (0.77%)
test_part1
test_part1 - accuracy (98.61%)
test_part1 - completeness (81.53%)
thisisatest0515
thisisatest0515 - accuracy (95.07%)
thisisatest0515 - completeness (81.63%)
thisisatest0530
thisisatest0530 - accuracy (93.79%)
thisisatest0530 - completeness (85.73%)
TinyColmap
TinyColmap - accuracy (91.58%)
TinyColmap - completeness (77.06%)
tmp_tt
tmp_tt - accuracy (59.66%)
tmp_tt - completeness (44.24%)
tpm
tpm - accuracy (76.67%)
tpm - completeness (80.61%)
tpm cat1
tpm cat1 - accuracy (70.88%)
tpm cat1 - completeness (80.10%)
tpmrst
tpmrst - accuracy (71.02%)
tpmrst - completeness (80.21%)
train_agg
train_agg - accuracy (93.46%)
train_agg - completeness (91.41%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (96.83%)
TranMVSNet+NR-MVSNet - completeness (82.83%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (96.14%)
TransMVSNet (Re) - completeness (79.15%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (95.61%)
TSAR-MVS + ACMM - completeness (92.02%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (92.50%)
TSAR-MVS + COLMAP - completeness (87.09%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (95.62%)
TSAR-MVS + GP. - completeness (90.31%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (97.91%)
TSAR-MVS + MP. - completeness (89.65%)
tttt0517
tttt0517 - accuracy (93.79%)
tttt0517 - completeness (85.73%)
UA-Net
UA-Net - accuracy (98.12%)
UA-Net - completeness (88.45%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (94.79%)
UGNet - completeness (86.97%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (96.74%)
UniMVSNet (Re) - completeness (82.47%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (97.81%)
UniMVSNet_ETH3D - completeness (81.49%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (96.31%)
UniMVSNet_NR-MVSNet - completeness (83.03%)
USDC
USDC - accuracy (89.18%)
USDC - completeness (81.22%)
Vis-MVSNet
Vis-MVSNet - accuracy (95.91%)
Vis-MVSNet - completeness (88.21%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (95.30%)
Vis-MVSNet (Re-imp) - completeness (88.29%)
WR-MVS_H
WR-MVS_H - accuracy (98.45%)
WR-MVS_H - completeness (75.99%)
X-MVS
X-MVS - accuracy (97.59%)
X-MVS - completeness (89.60%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (96.44%)
xxxxxxxxxxxxxcwj - completeness (90.84%)
zzz-MVS
zzz-MVS - accuracy (97.83%)
zzz-MVS - completeness (89.65%)
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
:
0.00 to 1.00
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
:
0.4
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