+
−
⇧
i
D
T
electro (high-res multi-view) - Tolerance 1cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (75.85%)
3Dnovator - completeness (67.73%)
3Dnovator+
3Dnovator+ - accuracy (88.33%)
3Dnovator+ - completeness (62.94%)
ACMH
ACMH - accuracy (80.77%)
ACMH - completeness (56.83%)
ACMH+
ACMH+ - accuracy (83.59%)
ACMH+ - completeness (56.62%)
ACMM
ACMM - accuracy (91.77%)
ACMM - completeness (65.65%)
ACMMP
ACMMP - accuracy (92.29%)
ACMMP - completeness (68.23%)
ACMMPR
ACMMPR - accuracy (92.57%)
ACMMPR - completeness (69.39%)
ACMMP_NAP
ACMMP_NAP - accuracy (91.62%)
ACMMP_NAP - completeness (73.53%)
ACMP
ACMP - accuracy (89.27%)
ACMP - completeness (65.98%)
AdaColmap
AdaColmap - accuracy (84.54%)
AdaColmap - completeness (67.84%)
ADS-MVSNet
ADS-MVSNet - accuracy (40.42%)
ADS-MVSNet - completeness (43.91%)
ambc
ambc - accuracy (73.75%)
ambc - completeness (28.38%)
Anonymous20231206
Anonymous20231206 - accuracy (58.06%)
Anonymous20231206 - completeness (34.99%)
Anonymous202405211
Anonymous202405211 - accuracy (62.23%)
Anonymous202405211 - completeness (59.82%)
anonymousdsp
anonymousdsp - accuracy (89.06%)
anonymousdsp - completeness (38.44%)
APD-MVS
APD-MVS - accuracy (90.49%)
APD-MVS - completeness (74.02%)
APDe-MVS
APDe-MVS - accuracy (90.38%)
APDe-MVS - completeness (77.39%)
baseline1
baseline1 - accuracy (54.17%)
baseline1 - completeness (57.33%)
baseline2
baseline2 - accuracy (60.89%)
baseline2 - completeness (58.65%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (75.88%)
Baseline_NR-MVSNet - completeness (44.50%)
CANet
CANet - accuracy (82.38%)
CANet - completeness (66.72%)
CANet_DTU
CANet_DTU - accuracy (70.98%)
CANet_DTU - completeness (58.14%)
canonicalmvs
canonicalmvs - accuracy (62.58%)
canonicalmvs - completeness (66.52%)
casdiffmvs
casdiffmvs - accuracy (69.06%)
casdiffmvs - completeness (67.91%)
CDPH-MVS
CDPH-MVS - accuracy (86.36%)
CDPH-MVS - completeness (71.35%)
CDS-MVSNet
CDS-MVSNet - accuracy (64.70%)
CDS-MVSNet - completeness (48.59%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (64.18%)
CHOSEN 1792x2688 - completeness (62.43%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (50.30%)
CHOSEN 280x420 - completeness (40.67%)
CLD-MVS
CLD-MVS - accuracy (82.82%)
CLD-MVS - completeness (63.09%)
CMPMVS
CMPMVS - accuracy (48.16%)
CMPMVS - completeness (46.73%)
CNLPA
CNLPA - accuracy (86.14%)
CNLPA - completeness (53.47%)
CNVR-MVS
CNVR-MVS - accuracy (87.97%)
CNVR-MVS - completeness (76.19%)
COLMAP_ROB
COLMAP_ROB - accuracy (90.39%)
COLMAP_ROB - completeness (45.51%)
CostFormer
CostFormer - accuracy (66.28%)
CostFormer - completeness (67.62%)
CP-MVS
CP-MVS - accuracy (92.67%)
CP-MVS - completeness (67.27%)
CP-MVSNet
CP-MVSNet - accuracy (80.54%)
CP-MVSNet - completeness (32.75%)
CPTT-MVS
CPTT-MVS - accuracy (91.68%)
CPTT-MVS - completeness (65.48%)
CR-MVSNet
CR-MVSNet - accuracy (45.00%)
CR-MVSNet - completeness (52.06%)
CS-MVS
CS-MVS - accuracy (75.90%)
CS-MVS - completeness (62.36%)
CSCG
CSCG - accuracy (81.08%)
CSCG - completeness (77.26%)
CVMVSNet
CVMVSNet - accuracy (68.41%)
CVMVSNet - completeness (34.81%)
DCV-MVSNet
DCV-MVSNet - accuracy (62.50%)
DCV-MVSNet - completeness (60.37%)
DeepC-MVS
DeepC-MVS - accuracy (90.30%)
DeepC-MVS - completeness (68.89%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (87.59%)
DeepC-MVS_fast - completeness (67.96%)
DeepMVS_CX
DeepMVS_CX - accuracy (9.75%)
DeepMVS_CX - completeness (4.32%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (89.33%)
DeepPCF-MVS - completeness (65.54%)
DELS-MVS
DELS-MVS - accuracy (70.99%)
DELS-MVS - completeness (70.82%)
diffmvs
diffmvs - accuracy (67.36%)
diffmvs - completeness (66.90%)
DPE-MVS
DPE-MVS - accuracy (89.77%)
DPE-MVS - completeness (77.05%)
DPM-MVS
DPM-MVS - accuracy (84.07%)
DPM-MVS - completeness (79.30%)
dps
dps - accuracy (53.02%)
dps - completeness (54.47%)
DTE-MVSNet
DTE-MVSNet - accuracy (81.60%)
DTE-MVSNet - completeness (30.71%)
DU-MVS
DU-MVS - accuracy (73.93%)
DU-MVS - completeness (46.97%)
DVP-MVS
DVP-MVS - accuracy (86.62%)
DVP-MVS - completeness (77.20%)
E-PMN
E-PMN - accuracy (42.77%)
E-PMN - completeness (4.30%)
Effi-MVS+
Effi-MVS+ - accuracy (74.87%)
Effi-MVS+ - completeness (63.61%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (79.47%)
Effi-MVS+-dtu - completeness (56.42%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (74.23%)
EG-PatchMatch MVS - completeness (52.46%)
EIA-MVS
EIA-MVS - accuracy (72.40%)
EIA-MVS - completeness (59.55%)
EMVS
EMVS - accuracy (44.09%)
EMVS - completeness (4.48%)
EPMVS
EPMVS - accuracy (41.74%)
EPMVS - completeness (55.32%)
EPNet
EPNet - accuracy (78.46%)
EPNet - completeness (59.28%)
EPNet_dtu
EPNet_dtu - accuracy (69.83%)
EPNet_dtu - completeness (41.44%)
EPP-MVSNet
EPP-MVSNet - accuracy (71.77%)
EPP-MVSNet - completeness (49.27%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (68.06%)
ET-MVSNet_ETH3D - completeness (63.51%)
ETV-MVS
ETV-MVS - accuracy (77.02%)
ETV-MVS - completeness (60.26%)
EU-MVSNet
EU-MVSNet - accuracy (62.98%)
EU-MVSNet - completeness (29.32%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (75.74%)
Fast-Effi-MVS+ - completeness (57.05%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (74.15%)
Fast-Effi-MVS+-dtu - completeness (58.75%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (68.06%)
FC-MVSNet-test - completeness (19.43%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (69.69%)
FC-MVSNet-train - completeness (46.77%)
FMVSNet1
FMVSNet1 - accuracy (59.48%)
FMVSNet1 - completeness (54.22%)
FMVSNet2
FMVSNet2 - accuracy (57.26%)
FMVSNet2 - completeness (56.80%)
FMVSNet3
FMVSNet3 - accuracy (55.89%)
FMVSNet3 - completeness (57.57%)
FMVSNet5
FMVSNet5 - accuracy (48.77%)
FMVSNet5 - completeness (45.87%)
FPMVS
FPMVS - accuracy (77.07%)
FPMVS - completeness (32.28%)
GA-MVS
GA-MVS - accuracy (65.07%)
GA-MVS - completeness (57.55%)
GBi-Net
GBi-Net - accuracy (57.26%)
GBi-Net - completeness (56.80%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (42.97%)
GG-mvs-BLEND - completeness (55.99%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (53.71%)
gg-mvs-nofinetune - completeness (53.40%)
Gipuma
Gipuma - accuracy (70.28%)
Gipuma - completeness (11.97%)
gm-plane-assit
gm-plane-assit - accuracy (74.96%)
gm-plane-assit - completeness (24.54%)
HFP-MVS
HFP-MVS - accuracy (91.13%)
HFP-MVS - completeness (71.87%)
HPM-MVS++
HPM-MVS++ - accuracy (90.48%)
HPM-MVS++ - completeness (71.98%)
HQP-MVS
HQP-MVS - accuracy (84.75%)
HQP-MVS - completeness (71.41%)
HyFIR lowres test
HyFIR lowres test - accuracy (71.76%)
HyFIR lowres test - completeness (59.02%)
IB-MVS
IB-MVS - accuracy (70.70%)
IB-MVS - completeness (54.51%)
IS_MVSNet
IS_MVSNet - accuracy (71.47%)
IS_MVSNet - completeness (47.65%)
IterMVS
IterMVS - accuracy (66.51%)
IterMVS - completeness (53.10%)
IterMVS-LS
IterMVS-LS - accuracy (64.63%)
IterMVS-LS - completeness (55.00%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (57.51%)
IterMVS-SCA-FT - completeness (52.89%)
LGP-MVS_train
LGP-MVS_train - accuracy (89.78%)
LGP-MVS_train - completeness (66.90%)
LS3D
LS3D - accuracy (83.30%)
LS3D - completeness (56.31%)
LTVRE_ROB
LTVRE_ROB - accuracy (86.48%)
LTVRE_ROB - completeness (28.52%)
MAR-MVS
MAR-MVS - accuracy (80.09%)
MAR-MVS - completeness (69.87%)
MCST-MVS
MCST-MVS - accuracy (81.38%)
MCST-MVS - completeness (76.33%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (68.65%)
MDA-MVSNet-bldmvs - completeness (33.42%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (59.82%)
MDTV_nov1_ep13 - completeness (56.47%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (66.95%)
MDTV_nov1_ep13_2view - completeness (46.53%)
MIMVSNet
MIMVSNet - accuracy (52.20%)
MIMVSNet - completeness (49.48%)
MIMVSNet1
MIMVSNet1 - accuracy (69.13%)
MIMVSNet1 - completeness (26.29%)
MP-MVS
MP-MVS - accuracy (92.68%)
MP-MVS - completeness (69.22%)
MS-PatchMatch
MS-PatchMatch - accuracy (63.41%)
MS-PatchMatch - completeness (66.29%)
MSDG
MSDG - accuracy (75.41%)
MSDG - completeness (61.44%)
MSLP-MVS++
MSLP-MVS++ - accuracy (79.77%)
MSLP-MVS++ - completeness (70.75%)
MSP-MVS
MSP-MVS - accuracy (89.07%)
MSP-MVS - completeness (77.61%)
MVE
MVE - accuracy (30.85%)
MVE - completeness (3.36%)
MVS-HIRNet
MVS-HIRNet - accuracy (39.52%)
MVS-HIRNet - completeness (32.66%)
MVSTER
MVSTER - accuracy (60.14%)
MVSTER - completeness (63.02%)
MVS_0304
MVS_0304 - accuracy (84.70%)
MVS_0304 - completeness (67.13%)
MVS_111021_LR
MVS_111021_LR - accuracy (81.73%)
MVS_111021_LR - completeness (55.16%)
MVS_Test
MVS_Test - accuracy (64.94%)
MVS_Test - completeness (68.13%)
NCCC
NCCC - accuracy (88.06%)
NCCC - completeness (74.16%)
new-patchmatchnet
new-patchmatchnet - accuracy (36.84%)
new-patchmatchnet - completeness (24.85%)
new_pmnet
new_pmnet - accuracy (31.87%)
new_pmnet - completeness (14.22%)
NR-MVSNet
NR-MVSNet - accuracy (74.42%)
NR-MVSNet - completeness (47.39%)
N_pmnet
N_pmnet - accuracy (40.20%)
N_pmnet - completeness (32.26%)
OMC-MVS
OMC-MVS - accuracy (87.87%)
OMC-MVS - completeness (56.80%)
OpenMVS
OpenMVS - accuracy (64.11%)
OpenMVS - completeness (64.42%)
OPM-MVS
OPM-MVS - accuracy (89.84%)
OPM-MVS - completeness (71.41%)
our_test_3
our_test_3 - accuracy (69.11%)
our_test_3 - completeness (45.84%)
PatchMatch-RL
PatchMatch-RL - accuracy (67.38%)
PatchMatch-RL - completeness (40.02%)
Patchmatch-RL test
Patchmatch-RL test - accuracy (2.05%)
Patchmatch-RL test - completeness (0.69%)
PatchmatchNet
PatchmatchNet - accuracy (55.54%)
PatchmatchNet - completeness (51.39%)
Patchmtry
Patchmtry - accuracy (45.00%)
Patchmtry - completeness (52.06%)
PatchT
PatchT - accuracy (50.55%)
PatchT - completeness (33.59%)
PCF-MVS
PCF-MVS - accuracy (83.76%)
PCF-MVS - completeness (67.53%)
PEN-MVS
PEN-MVS - accuracy (80.86%)
PEN-MVS - completeness (33.17%)
PGM-MVS
PGM-MVS - accuracy (92.40%)
PGM-MVS - completeness (69.41%)
PHI-MVS
PHI-MVS - accuracy (82.28%)
PHI-MVS - completeness (67.04%)
PLC
PLC - accuracy (82.01%)
PLC - completeness (53.11%)
PM-MVS
PM-MVS - accuracy (73.66%)
PM-MVS - completeness (33.56%)
pm-mvs1
pm-mvs1 - accuracy (58.67%)
pm-mvs1 - completeness (44.98%)
PMMVS
PMMVS - accuracy (50.88%)
PMMVS - completeness (47.22%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (74.29%)
pmmvs-eth3d - completeness (44.97%)
PMMVS2
PMMVS2 - accuracy (35.08%)
PMMVS2 - completeness (8.21%)
pmmvs3
pmmvs3 - accuracy (49.83%)
pmmvs3 - completeness (26.40%)
pmmvs5
pmmvs5 - accuracy (49.27%)
pmmvs5 - completeness (47.24%)
pmmvs6
pmmvs6 - accuracy (60.24%)
pmmvs6 - completeness (41.92%)
pmnet_mix02
pmnet_mix02 - accuracy (42.04%)
pmnet_mix02 - completeness (42.19%)
PMVS
PMVS - accuracy (87.77%)
PMVS - completeness (19.95%)
PS-CasMVS
PS-CasMVS - accuracy (80.63%)
PS-CasMVS - completeness (32.68%)
PVSNet_Blended
PVSNet_Blended - accuracy (65.81%)
PVSNet_Blended - completeness (61.30%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (65.81%)
PVSNet_BlendedMVS - completeness (61.30%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (77.97%)
PVSNet_Blended_VisFu - completeness (57.72%)
QAPM
QAPM - accuracy (64.05%)
QAPM - completeness (67.43%)
RPMNet
RPMNet - accuracy (59.16%)
RPMNet - completeness (37.66%)
RPSCF
RPSCF - accuracy (79.74%)
RPSCF - completeness (31.73%)
SCA
SCA - accuracy (60.18%)
SCA - completeness (43.14%)
SD-MVS
SD-MVS - accuracy (89.48%)
SD-MVS - completeness (70.81%)
SED-MVS
SED-MVS - accuracy (88.77%)
SED-MVS - completeness (77.82%)
SF-MVS
SF-MVS - accuracy (83.86%)
SF-MVS - completeness (82.08%)
SMA-MVS
SMA-MVS - accuracy (91.01%)
SMA-MVS - completeness (74.99%)
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 (92.65%)
SteuartSystems-ACMMP - completeness (73.13%)
TAMVS
TAMVS - accuracy (53.16%)
TAMVS - completeness (39.07%)
TAPA-MVS
TAPA-MVS - accuracy (83.17%)
TAPA-MVS - completeness (53.82%)
TDRefinement
TDRefinement - accuracy (93.79%)
TDRefinement - completeness (43.29%)
test-mter
test-mter - accuracy (55.28%)
test-mter - completeness (41.77%)
test1
test1 - accuracy (57.26%)
test1 - completeness (56.80%)
test123
test123 - accuracy (0.33%)
test123 - completeness (0.00%)
testgi
testgi - accuracy (65.88%)
testgi - completeness (24.38%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (51.28%)
TESTMET0.1,1 - completeness (47.88%)
testmvs
testmvs - accuracy (0.35%)
testmvs - completeness (0.00%)
test_part1
test_part1 - accuracy (78.24%)
test_part1 - completeness (66.45%)
thisisatest0515
thisisatest0515 - accuracy (71.08%)
thisisatest0515 - completeness (46.19%)
thisisatest0530
thisisatest0530 - accuracy (68.03%)
thisisatest0530 - completeness (52.72%)
TinyColmap
TinyColmap - accuracy (74.35%)
TinyColmap - completeness (39.71%)
tmp_tt
tmp_tt - accuracy (4.35%)
tmp_tt - completeness (2.61%)
tpm
tpm - accuracy (53.93%)
tpm - completeness (58.34%)
tpm cat1
tpm cat1 - accuracy (63.13%)
tpm cat1 - completeness (64.35%)
tpmrst
tpmrst - accuracy (48.01%)
tpmrst - completeness (60.71%)
train_agg
train_agg - accuracy (88.87%)
train_agg - completeness (72.33%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (74.77%)
TranMVSNet+NR-MVSNet - completeness (47.28%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (61.17%)
TransMVSNet (Re) - completeness (48.26%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (84.41%)
TSAR-MVS + ACMM - completeness (73.36%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (82.93%)
TSAR-MVS + COLMAP - completeness (54.11%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (81.59%)
TSAR-MVS + GP. - completeness (64.26%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (90.55%)
TSAR-MVS + MP. - completeness (72.60%)
tttt0517
tttt0517 - accuracy (68.80%)
tttt0517 - completeness (51.96%)
UA-Net
UA-Net - accuracy (89.06%)
UA-Net - completeness (38.41%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (70.97%)
UGNet - completeness (46.65%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (75.98%)
UniMVSNet (Re) - completeness (44.05%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (66.49%)
UniMVSNet_ETH3D - completeness (49.69%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (73.93%)
UniMVSNet_NR-MVSNet - completeness (46.97%)
USDC
USDC - accuracy (70.12%)
USDC - completeness (42.61%)
Vis-MVSNet
Vis-MVSNet - accuracy (77.94%)
Vis-MVSNet - completeness (49.10%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (67.40%)
Vis-MVSNet (Re-imp) - completeness (34.57%)
WR-MVS_H
WR-MVS_H - accuracy (83.23%)
WR-MVS_H - completeness (30.57%)
X-MVS
X-MVS - accuracy (93.53%)
X-MVS - completeness (65.82%)
X-MVStestdata
X-MVStestdata - accuracy (93.33%)
X-MVStestdata - completeness (61.80%)
XVS
XVS - accuracy (93.33%)
XVS - completeness (61.80%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (83.86%)
xxxxxxxxxxxxxcwj - completeness (82.08%)
zzz-MVS
zzz-MVS - accuracy (92.42%)
zzz-MVS - completeness (70.05%)
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
:
-35.24 to 110.56
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
:
101.0
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