+
−
⇧
i
D
T
electro (high-res multi-view) - Tolerance 2cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (87.18%)
3Dnovator - completeness (81.84%)
3Dnovator+
3Dnovator+ - accuracy (94.26%)
3Dnovator+ - completeness (80.09%)
ACMH
ACMH - accuracy (91.47%)
ACMH - completeness (67.65%)
ACMH+
ACMH+ - accuracy (92.18%)
ACMH+ - completeness (68.45%)
ACMM
ACMM - accuracy (96.34%)
ACMM - completeness (77.70%)
ACMMP
ACMMP - accuracy (96.49%)
ACMMP - completeness (81.42%)
ACMMPR
ACMMPR - accuracy (96.60%)
ACMMPR - completeness (83.02%)
ACMMP_NAP
ACMMP_NAP - accuracy (96.00%)
ACMMP_NAP - completeness (85.27%)
ACMP
ACMP - accuracy (94.96%)
ACMP - completeness (77.93%)
AdaColmap
AdaColmap - accuracy (90.56%)
AdaColmap - completeness (79.99%)
ADS-MVSNet
ADS-MVSNet - accuracy (58.02%)
ADS-MVSNet - completeness (60.26%)
ambc
ambc - accuracy (84.48%)
ambc - completeness (35.47%)
Anonymous20231206
Anonymous20231206 - accuracy (74.21%)
Anonymous20231206 - completeness (51.01%)
Anonymous202405211
Anonymous202405211 - accuracy (79.03%)
Anonymous202405211 - completeness (74.85%)
anonymousdsp
anonymousdsp - accuracy (96.28%)
anonymousdsp - completeness (51.49%)
APD-MVS
APD-MVS - accuracy (95.50%)
APD-MVS - completeness (86.51%)
APDe-MVS
APDe-MVS - accuracy (96.04%)
APDe-MVS - completeness (88.34%)
baseline1
baseline1 - accuracy (71.38%)
baseline1 - completeness (76.61%)
baseline2
baseline2 - accuracy (76.60%)
baseline2 - completeness (71.23%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (87.81%)
Baseline_NR-MVSNet - completeness (61.63%)
CANet
CANet - accuracy (90.23%)
CANet - completeness (81.19%)
CANet_DTU
CANet_DTU - accuracy (83.88%)
CANet_DTU - completeness (75.54%)
canonicalmvs
canonicalmvs - accuracy (80.29%)
canonicalmvs - completeness (81.32%)
casdiffmvs
casdiffmvs - accuracy (82.95%)
casdiffmvs - completeness (78.47%)
CDPH-MVS
CDPH-MVS - accuracy (92.86%)
CDPH-MVS - completeness (84.20%)
CDS-MVSNet
CDS-MVSNet - accuracy (79.56%)
CDS-MVSNet - completeness (69.91%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (78.98%)
CHOSEN 1792x2688 - completeness (75.63%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (69.12%)
CHOSEN 280x420 - completeness (61.20%)
CLD-MVS
CLD-MVS - accuracy (90.23%)
CLD-MVS - completeness (81.92%)
CMPMVS
CMPMVS - accuracy (63.17%)
CMPMVS - completeness (62.77%)
CNLPA
CNLPA - accuracy (90.89%)
CNLPA - completeness (71.07%)
CNVR-MVS
CNVR-MVS - accuracy (93.23%)
CNVR-MVS - completeness (87.62%)
COLMAP_ROB
COLMAP_ROB - accuracy (95.51%)
COLMAP_ROB - completeness (62.13%)
CostFormer
CostFormer - accuracy (79.55%)
CostFormer - completeness (76.94%)
CP-MVS
CP-MVS - accuracy (96.46%)
CP-MVS - completeness (82.00%)
CP-MVSNet
CP-MVSNet - accuracy (90.47%)
CP-MVSNet - completeness (48.17%)
CPTT-MVS
CPTT-MVS - accuracy (95.71%)
CPTT-MVS - completeness (80.96%)
CR-MVSNet
CR-MVSNet - accuracy (64.47%)
CR-MVSNet - completeness (67.53%)
CS-MVS
CS-MVS - accuracy (88.78%)
CS-MVS - completeness (73.93%)
CSCG
CSCG - accuracy (90.57%)
CSCG - completeness (87.14%)
CVMVSNet
CVMVSNet - accuracy (83.04%)
CVMVSNet - completeness (55.45%)
DCV-MVSNet
DCV-MVSNet - accuracy (80.44%)
DCV-MVSNet - completeness (74.68%)
DeepC-MVS
DeepC-MVS - accuracy (94.72%)
DeepC-MVS - completeness (83.23%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (92.74%)
DeepC-MVS_fast - completeness (83.42%)
DeepMVS_CX
DeepMVS_CX - accuracy (20.40%)
DeepMVS_CX - completeness (17.01%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (93.79%)
DeepPCF-MVS - completeness (78.48%)
DELS-MVS
DELS-MVS - accuracy (84.79%)
DELS-MVS - completeness (84.12%)
diffmvs
diffmvs - accuracy (80.68%)
diffmvs - completeness (78.20%)
DPE-MVS
DPE-MVS - accuracy (95.53%)
DPE-MVS - completeness (88.69%)
DPM-MVS
DPM-MVS - accuracy (90.18%)
DPM-MVS - completeness (90.49%)
dps
dps - accuracy (71.44%)
dps - completeness (66.68%)
DTE-MVSNet
DTE-MVSNet - accuracy (90.96%)
DTE-MVSNet - completeness (45.89%)
DU-MVS
DU-MVS - accuracy (87.06%)
DU-MVS - completeness (64.07%)
DVP-MVS
DVP-MVS - accuracy (93.72%)
DVP-MVS - completeness (87.86%)
E-PMN
E-PMN - accuracy (60.44%)
E-PMN - completeness (6.95%)
Effi-MVS+
Effi-MVS+ - accuracy (87.53%)
Effi-MVS+ - completeness (75.57%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (88.40%)
Effi-MVS+-dtu - completeness (70.68%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (86.75%)
EG-PatchMatch MVS - completeness (63.44%)
EIA-MVS
EIA-MVS - accuracy (86.16%)
EIA-MVS - completeness (71.78%)
EMVS
EMVS - accuracy (61.74%)
EMVS - completeness (7.06%)
EPMVS
EPMVS - accuracy (60.66%)
EPMVS - completeness (68.94%)
EPNet
EPNet - accuracy (88.35%)
EPNet - completeness (79.43%)
EPNet_dtu
EPNet_dtu - accuracy (82.44%)
EPNet_dtu - completeness (68.87%)
EPP-MVSNet
EPP-MVSNet - accuracy (85.39%)
EPP-MVSNet - completeness (66.85%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (82.70%)
ET-MVSNet_ETH3D - completeness (77.29%)
ETV-MVS
ETV-MVS - accuracy (88.80%)
ETV-MVS - completeness (72.75%)
EU-MVSNet
EU-MVSNet - accuracy (81.74%)
EU-MVSNet - completeness (43.07%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (87.72%)
Fast-Effi-MVS+ - completeness (71.12%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (84.80%)
Fast-Effi-MVS+-dtu - completeness (70.72%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (85.33%)
FC-MVSNet-test - completeness (34.48%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (85.68%)
FC-MVSNet-train - completeness (64.72%)
FMVSNet1
FMVSNet1 - accuracy (77.90%)
FMVSNet1 - completeness (71.77%)
FMVSNet2
FMVSNet2 - accuracy (75.77%)
FMVSNet2 - completeness (74.54%)
FMVSNet3
FMVSNet3 - accuracy (74.29%)
FMVSNet3 - completeness (75.63%)
FMVSNet5
FMVSNet5 - accuracy (66.85%)
FMVSNet5 - completeness (63.77%)
FPMVS
FPMVS - accuracy (86.48%)
FPMVS - completeness (46.23%)
GA-MVS
GA-MVS - accuracy (80.03%)
GA-MVS - completeness (69.59%)
GBi-Net
GBi-Net - accuracy (75.77%)
GBi-Net - completeness (74.54%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (55.66%)
GG-mvs-BLEND - completeness (77.20%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (70.48%)
gg-mvs-nofinetune - completeness (71.18%)
Gipuma
Gipuma - accuracy (85.35%)
Gipuma - completeness (18.06%)
gm-plane-assit
gm-plane-assit - accuracy (90.42%)
gm-plane-assit - completeness (32.32%)
HFP-MVS
HFP-MVS - accuracy (95.69%)
HFP-MVS - completeness (84.28%)
HPM-MVS++
HPM-MVS++ - accuracy (95.10%)
HPM-MVS++ - completeness (85.83%)
HQP-MVS
HQP-MVS - accuracy (91.28%)
HQP-MVS - completeness (83.01%)
HyFIR lowres test
HyFIR lowres test - accuracy (83.12%)
HyFIR lowres test - completeness (71.08%)
IB-MVS
IB-MVS - accuracy (83.05%)
IB-MVS - completeness (64.50%)
IS_MVSNet
IS_MVSNet - accuracy (85.56%)
IS_MVSNet - completeness (65.90%)
IterMVS
IterMVS - accuracy (80.69%)
IterMVS - completeness (67.34%)
IterMVS-LS
IterMVS-LS - accuracy (79.90%)
IterMVS-LS - completeness (70.89%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (75.58%)
IterMVS-SCA-FT - completeness (67.53%)
LGP-MVS_train
LGP-MVS_train - accuracy (95.35%)
LGP-MVS_train - completeness (79.58%)
LS3D
LS3D - accuracy (92.56%)
LS3D - completeness (69.99%)
LTVRE_ROB
LTVRE_ROB - accuracy (93.60%)
LTVRE_ROB - completeness (49.05%)
MAR-MVS
MAR-MVS - accuracy (89.13%)
MAR-MVS - completeness (79.33%)
MCST-MVS
MCST-MVS - accuracy (90.46%)
MCST-MVS - completeness (88.15%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (84.05%)
MDA-MVSNet-bldmvs - completeness (46.28%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (75.80%)
MDTV_nov1_ep13 - completeness (69.28%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (82.31%)
MDTV_nov1_ep13_2view - completeness (57.92%)
MIMVSNet
MIMVSNet - accuracy (70.01%)
MIMVSNet - completeness (63.89%)
MIMVSNet1
MIMVSNet1 - accuracy (84.58%)
MIMVSNet1 - completeness (39.24%)
MP-MVS
MP-MVS - accuracy (96.56%)
MP-MVS - completeness (82.82%)
MS-PatchMatch
MS-PatchMatch - accuracy (77.18%)
MS-PatchMatch - completeness (77.84%)
MSDG
MSDG - accuracy (85.31%)
MSDG - completeness (74.46%)
MSLP-MVS++
MSLP-MVS++ - accuracy (87.04%)
MSLP-MVS++ - completeness (84.62%)
MSP-MVS
MSP-MVS - accuracy (95.29%)
MSP-MVS - completeness (88.24%)
MVE
MVE - accuracy (48.45%)
MVE - completeness (5.90%)
MVS-HIRNet
MVS-HIRNet - accuracy (56.02%)
MVS-HIRNet - completeness (44.63%)
MVSTER
MVSTER - accuracy (75.71%)
MVSTER - completeness (78.15%)
MVS_0304
MVS_0304 - accuracy (91.55%)
MVS_0304 - completeness (81.82%)
MVS_111021_LR
MVS_111021_LR - accuracy (89.61%)
MVS_111021_LR - completeness (72.71%)
MVS_Test
MVS_Test - accuracy (79.91%)
MVS_Test - completeness (80.06%)
NCCC
NCCC - accuracy (93.27%)
NCCC - completeness (86.57%)
new-patchmatchnet
new-patchmatchnet - accuracy (53.46%)
new-patchmatchnet - completeness (39.38%)
new_pmnet
new_pmnet - accuracy (48.78%)
new_pmnet - completeness (29.29%)
NR-MVSNet
NR-MVSNet - accuracy (87.10%)
NR-MVSNet - completeness (63.60%)
N_pmnet
N_pmnet - accuracy (57.92%)
N_pmnet - completeness (46.95%)
OMC-MVS
OMC-MVS - accuracy (93.01%)
OMC-MVS - completeness (75.35%)
OpenMVS
OpenMVS - accuracy (79.99%)
OpenMVS - completeness (78.01%)
OPM-MVS
OPM-MVS - accuracy (95.07%)
OPM-MVS - completeness (82.82%)
our_test_3
our_test_3 - accuracy (83.26%)
our_test_3 - completeness (55.90%)
PatchMatch-RL
PatchMatch-RL - accuracy (81.09%)
PatchMatch-RL - completeness (59.27%)
Patchmatch-RL test
Patchmatch-RL test - accuracy (4.13%)
Patchmatch-RL test - completeness (2.17%)
PatchmatchNet
PatchmatchNet - accuracy (73.16%)
PatchmatchNet - completeness (66.42%)
Patchmtry
Patchmtry - accuracy (64.47%)
Patchmtry - completeness (67.53%)
PatchT
PatchT - accuracy (70.17%)
PatchT - completeness (47.34%)
PCF-MVS
PCF-MVS - accuracy (91.24%)
PCF-MVS - completeness (81.47%)
PEN-MVS
PEN-MVS - accuracy (90.83%)
PEN-MVS - completeness (48.68%)
PGM-MVS
PGM-MVS - accuracy (96.51%)
PGM-MVS - completeness (82.97%)
PHI-MVS
PHI-MVS - accuracy (90.76%)
PHI-MVS - completeness (80.85%)
PLC
PLC - accuracy (88.86%)
PLC - completeness (72.64%)
PM-MVS
PM-MVS - accuracy (87.14%)
PM-MVS - completeness (50.91%)
pm-mvs1
pm-mvs1 - accuracy (76.25%)
pm-mvs1 - completeness (64.12%)
PMMVS
PMMVS - accuracy (69.54%)
PMMVS - completeness (64.10%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (87.47%)
pmmvs-eth3d - completeness (57.54%)
PMMVS2
PMMVS2 - accuracy (51.95%)
PMMVS2 - completeness (14.85%)
pmmvs3
pmmvs3 - accuracy (70.05%)
pmmvs3 - completeness (38.93%)
pmmvs5
pmmvs5 - accuracy (71.70%)
pmmvs5 - completeness (63.17%)
pmmvs6
pmmvs6 - accuracy (77.54%)
pmmvs6 - completeness (60.17%)
pmnet_mix02
pmnet_mix02 - accuracy (62.81%)
pmnet_mix02 - completeness (54.54%)
PMVS
PMVS - accuracy (93.64%)
PMVS - completeness (26.97%)
PS-CasMVS
PS-CasMVS - accuracy (90.54%)
PS-CasMVS - completeness (48.04%)
PVSNet_Blended
PVSNet_Blended - accuracy (79.65%)
PVSNet_Blended - completeness (75.45%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (79.65%)
PVSNet_BlendedMVS - completeness (75.45%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (88.03%)
PVSNet_Blended_VisFu - completeness (72.05%)
QAPM
QAPM - accuracy (79.86%)
QAPM - completeness (81.41%)
RPMNet
RPMNet - accuracy (75.81%)
RPMNet - completeness (54.60%)
RPSCF
RPSCF - accuracy (90.04%)
RPSCF - completeness (53.68%)
SCA
SCA - accuracy (76.96%)
SCA - completeness (59.87%)
SD-MVS
SD-MVS - accuracy (94.31%)
SD-MVS - completeness (85.65%)
SED-MVS
SED-MVS - accuracy (95.11%)
SED-MVS - completeness (88.55%)
SF-MVS
SF-MVS - accuracy (90.80%)
SF-MVS - completeness (91.01%)
SMA-MVS
SMA-MVS - accuracy (95.22%)
SMA-MVS - completeness (86.71%)
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 (96.51%)
SteuartSystems-ACMMP - completeness (84.79%)
TAMVS
TAMVS - accuracy (69.63%)
TAMVS - completeness (58.97%)
TAPA-MVS
TAPA-MVS - accuracy (90.62%)
TAPA-MVS - completeness (73.81%)
TDRefinement
TDRefinement - accuracy (97.27%)
TDRefinement - completeness (61.47%)
test-mter
test-mter - accuracy (73.12%)
test-mter - completeness (59.13%)
test1
test1 - accuracy (75.77%)
test1 - completeness (74.54%)
test123
test123 - accuracy (0.52%)
test123 - completeness (0.01%)
testgi
testgi - accuracy (81.16%)
testgi - completeness (41.54%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (69.46%)
TESTMET0.1,1 - completeness (63.98%)
testmvs
testmvs - accuracy (0.62%)
testmvs - completeness (0.03%)
test_part1
test_part1 - accuracy (90.91%)
test_part1 - completeness (77.85%)
thisisatest0515
thisisatest0515 - accuracy (85.06%)
thisisatest0515 - completeness (58.56%)
thisisatest0530
thisisatest0530 - accuracy (82.15%)
thisisatest0530 - completeness (68.21%)
TinyColmap
TinyColmap - accuracy (85.42%)
TinyColmap - completeness (57.15%)
tmp_tt
tmp_tt - accuracy (8.49%)
tmp_tt - completeness (13.61%)
tpm
tpm - accuracy (71.65%)
tpm - completeness (70.98%)
tpm cat1
tpm cat1 - accuracy (76.18%)
tpm cat1 - completeness (74.49%)
tpmrst
tpmrst - accuracy (66.99%)
tpmrst - completeness (71.27%)
train_agg
train_agg - accuracy (94.47%)
train_agg - completeness (85.60%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (87.40%)
TranMVSNet+NR-MVSNet - completeness (63.38%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (77.54%)
TransMVSNet (Re) - completeness (63.57%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (90.98%)
TSAR-MVS + ACMM - completeness (86.32%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (90.50%)
TSAR-MVS + COLMAP - completeness (74.51%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (89.07%)
TSAR-MVS + GP. - completeness (81.12%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (96.15%)
TSAR-MVS + MP. - completeness (85.63%)
tttt0517
tttt0517 - accuracy (82.73%)
tttt0517 - completeness (67.62%)
UA-Net
UA-Net - accuracy (94.76%)
UA-Net - completeness (60.08%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (86.64%)
UGNet - completeness (66.43%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (88.03%)
UniMVSNet (Re) - completeness (61.75%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (81.76%)
UniMVSNet_ETH3D - completeness (67.70%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (87.06%)
UniMVSNet_NR-MVSNet - completeness (64.07%)
USDC
USDC - accuracy (82.62%)
USDC - completeness (63.15%)
Vis-MVSNet
Vis-MVSNet - accuracy (90.58%)
Vis-MVSNet - completeness (66.37%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (81.66%)
Vis-MVSNet (Re-imp) - completeness (56.51%)
WR-MVS_H
WR-MVS_H - accuracy (91.95%)
WR-MVS_H - completeness (46.14%)
X-MVS
X-MVS - accuracy (96.76%)
X-MVS - completeness (81.05%)
X-MVStestdata
X-MVStestdata - accuracy (96.89%)
X-MVStestdata - completeness (75.70%)
XVS
XVS - accuracy (96.89%)
XVS - completeness (75.70%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (90.80%)
xxxxxxxxxxxxxcwj - completeness (91.01%)
zzz-MVS
zzz-MVS - accuracy (96.45%)
zzz-MVS - completeness (83.96%)
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