+
−
⇧
i
D
T
delivery_area (high-res multi-view) - Tolerance 2cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (84.61%)
3Dnovator - completeness (90.27%)
3Dnovator+
3Dnovator+ - accuracy (91.06%)
3Dnovator+ - completeness (88.32%)
ACMH
ACMH - accuracy (87.16%)
ACMH - completeness (78.26%)
ACMH+
ACMH+ - accuracy (89.26%)
ACMH+ - completeness (74.35%)
ACMM
ACMM - accuracy (89.93%)
ACMM - completeness (77.76%)
ACMMP
ACMMP - accuracy (91.60%)
ACMMP - completeness (85.58%)
ACMMPR
ACMMPR - accuracy (91.61%)
ACMMPR - completeness (87.05%)
ACMMP_NAP
ACMMP_NAP - accuracy (90.08%)
ACMMP_NAP - completeness (90.10%)
ACMP
ACMP - accuracy (91.10%)
ACMP - completeness (80.87%)
AdaColmap
AdaColmap - accuracy (87.14%)
AdaColmap - completeness (85.00%)
ADS-MVSNet
ADS-MVSNet - accuracy (48.10%)
ADS-MVSNet - completeness (74.57%)
ambc
ambc - accuracy (87.97%)
ambc - completeness (49.51%)
Anonymous20231206
Anonymous20231206 - accuracy (63.61%)
Anonymous20231206 - completeness (69.41%)
Anonymous202405211
Anonymous202405211 - accuracy (79.45%)
Anonymous202405211 - completeness (84.41%)
anonymousdsp
anonymousdsp - accuracy (76.35%)
anonymousdsp - completeness (71.75%)
APD-MVS
APD-MVS - accuracy (91.02%)
APD-MVS - completeness (89.21%)
APDe-MVS
APDe-MVS - accuracy (91.34%)
APDe-MVS - completeness (91.83%)
baseline1
baseline1 - accuracy (70.39%)
baseline1 - completeness (84.51%)
baseline2
baseline2 - accuracy (69.70%)
baseline2 - completeness (86.34%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (75.62%)
Baseline_NR-MVSNet - completeness (73.90%)
CANet
CANet - accuracy (85.20%)
CANet - completeness (92.26%)
CANet_DTU
CANet_DTU - accuracy (77.96%)
CANet_DTU - completeness (86.62%)
canonicalmvs
canonicalmvs - accuracy (83.18%)
canonicalmvs - completeness (89.83%)
casdiffmvs
casdiffmvs - accuracy (78.99%)
casdiffmvs - completeness (89.07%)
CDPH-MVS
CDPH-MVS - accuracy (88.27%)
CDPH-MVS - completeness (88.34%)
CDS-MVSNet
CDS-MVSNet - accuracy (72.89%)
CDS-MVSNet - completeness (80.59%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (68.89%)
CHOSEN 1792x2688 - completeness (92.41%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (39.91%)
CHOSEN 280x420 - completeness (68.92%)
CLD-MVS
CLD-MVS - accuracy (85.76%)
CLD-MVS - completeness (88.11%)
CMPMVS
CMPMVS - accuracy (63.91%)
CMPMVS - completeness (79.00%)
CNLPA
CNLPA - accuracy (87.52%)
CNLPA - completeness (81.33%)
CNVR-MVS
CNVR-MVS - accuracy (87.41%)
CNVR-MVS - completeness (92.40%)
COLMAP_ROB
COLMAP_ROB - accuracy (92.86%)
COLMAP_ROB - completeness (67.21%)
CostFormer
CostFormer - accuracy (68.25%)
CostFormer - completeness (86.19%)
CP-MVS
CP-MVS - accuracy (90.41%)
CP-MVS - completeness (85.96%)
CP-MVSNet
CP-MVSNet - accuracy (88.09%)
CP-MVSNet - completeness (65.82%)
CPTT-MVS
CPTT-MVS - accuracy (90.74%)
CPTT-MVS - completeness (82.55%)
CR-MVSNet
CR-MVSNet - accuracy (67.63%)
CR-MVSNet - completeness (71.29%)
CS-MVS
CS-MVS - accuracy (79.85%)
CS-MVS - completeness (87.69%)
CSCG
CSCG - accuracy (90.59%)
CSCG - completeness (93.43%)
CVMVSNet
CVMVSNet - accuracy (69.89%)
CVMVSNet - completeness (68.44%)
DCV-MVSNet
DCV-MVSNet - accuracy (81.11%)
DCV-MVSNet - completeness (77.52%)
DeepC-MVS
DeepC-MVS - accuracy (92.33%)
DeepC-MVS - completeness (88.50%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (90.70%)
DeepC-MVS_fast - completeness (87.81%)
DeepMVS_CX
DeepMVS_CX - accuracy (17.78%)
DeepMVS_CX - completeness (19.81%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (90.01%)
DeepPCF-MVS - completeness (90.96%)
DELS-MVS
DELS-MVS - accuracy (82.68%)
DELS-MVS - completeness (92.49%)
diffmvs
diffmvs - accuracy (74.45%)
diffmvs - completeness (87.27%)
DPE-MVS
DPE-MVS - accuracy (91.00%)
DPE-MVS - completeness (93.44%)
DPM-MVS
DPM-MVS - accuracy (85.30%)
DPM-MVS - completeness (91.92%)
dps
dps - accuracy (65.81%)
dps - completeness (79.65%)
DTE-MVSNet
DTE-MVSNet - accuracy (88.10%)
DTE-MVSNet - completeness (64.38%)
DU-MVS
DU-MVS - accuracy (83.59%)
DU-MVS - completeness (75.87%)
DVP-MVS
DVP-MVS - accuracy (89.85%)
DVP-MVS - completeness (95.01%)
E-PMN
E-PMN - accuracy (47.81%)
E-PMN - completeness (12.31%)
Effi-MVS+
Effi-MVS+ - accuracy (81.32%)
Effi-MVS+ - completeness (85.24%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (86.57%)
Effi-MVS+-dtu - completeness (75.17%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (82.24%)
EG-PatchMatch MVS - completeness (80.49%)
EIA-MVS
EIA-MVS - accuracy (80.71%)
EIA-MVS - completeness (87.21%)
EMVS
EMVS - accuracy (48.71%)
EMVS - completeness (12.09%)
EPMVS
EPMVS - accuracy (50.55%)
EPMVS - completeness (84.20%)
EPNet
EPNet - accuracy (77.20%)
EPNet - completeness (90.14%)
EPNet_dtu
EPNet_dtu - accuracy (61.64%)
EPNet_dtu - completeness (77.39%)
EPP-MVSNet
EPP-MVSNet - accuracy (84.47%)
EPP-MVSNet - completeness (83.35%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (75.29%)
ET-MVSNet_ETH3D - completeness (88.06%)
ETV-MVS
ETV-MVS - accuracy (79.73%)
ETV-MVS - completeness (87.95%)
EU-MVSNet
EU-MVSNet - accuracy (70.30%)
EU-MVSNet - completeness (56.59%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (80.62%)
Fast-Effi-MVS+ - completeness (81.14%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (79.17%)
Fast-Effi-MVS+-dtu - completeness (76.81%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (69.07%)
FC-MVSNet-test - completeness (58.25%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (77.67%)
FC-MVSNet-train - completeness (79.94%)
FMVSNet1
FMVSNet1 - accuracy (79.03%)
FMVSNet1 - completeness (76.37%)
FMVSNet2
FMVSNet2 - accuracy (77.36%)
FMVSNet2 - completeness (78.65%)
FMVSNet3
FMVSNet3 - accuracy (76.59%)
FMVSNet3 - completeness (79.42%)
FMVSNet5
FMVSNet5 - accuracy (59.58%)
FMVSNet5 - completeness (66.25%)
FPMVS
FPMVS - accuracy (75.96%)
FPMVS - completeness (45.94%)
GA-MVS
GA-MVS - accuracy (75.66%)
GA-MVS - completeness (81.56%)
GBi-Net
GBi-Net - accuracy (77.36%)
GBi-Net - completeness (78.65%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (66.04%)
GG-mvs-BLEND - completeness (90.09%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (69.04%)
gg-mvs-nofinetune - completeness (88.61%)
Gipuma
Gipuma - accuracy (78.78%)
Gipuma - completeness (21.59%)
gm-plane-assit
gm-plane-assit - accuracy (73.21%)
gm-plane-assit - completeness (54.42%)
HFP-MVS
HFP-MVS - accuracy (90.91%)
HFP-MVS - completeness (87.55%)
HPM-MVS++
HPM-MVS++ - accuracy (85.69%)
HPM-MVS++ - completeness (90.24%)
HQP-MVS
HQP-MVS - accuracy (86.59%)
HQP-MVS - completeness (84.33%)
HyFIR lowres test
HyFIR lowres test - accuracy (78.33%)
HyFIR lowres test - completeness (88.11%)
IB-MVS
IB-MVS - accuracy (77.45%)
IB-MVS - completeness (89.01%)
IS_MVSNet
IS_MVSNet - accuracy (82.64%)
IS_MVSNet - completeness (84.32%)
IterMVS
IterMVS - accuracy (77.18%)
IterMVS - completeness (72.20%)
IterMVS-LS
IterMVS-LS - accuracy (77.85%)
IterMVS-LS - completeness (74.88%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (79.85%)
IterMVS-SCA-FT - completeness (71.84%)
LGP-MVS_train
LGP-MVS_train - accuracy (91.15%)
LGP-MVS_train - completeness (80.26%)
LS3D
LS3D - accuracy (90.81%)
LS3D - completeness (75.79%)
LTVRE_ROB
LTVRE_ROB - accuracy (86.35%)
LTVRE_ROB - completeness (69.79%)
MAR-MVS
MAR-MVS - accuracy (85.85%)
MAR-MVS - completeness (90.58%)
MCST-MVS
MCST-MVS - accuracy (87.03%)
MCST-MVS - completeness (92.80%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (74.72%)
MDA-MVSNet-bldmvs - completeness (62.31%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (62.46%)
MDTV_nov1_ep13 - completeness (81.72%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (64.86%)
MDTV_nov1_ep13_2view - completeness (73.82%)
MIMVSNet
MIMVSNet - accuracy (59.26%)
MIMVSNet - completeness (77.10%)
MIMVSNet1
MIMVSNet1 - accuracy (64.37%)
MIMVSNet1 - completeness (58.92%)
MP-MVS
MP-MVS - accuracy (90.90%)
MP-MVS - completeness (88.16%)
MS-PatchMatch
MS-PatchMatch - accuracy (71.76%)
MS-PatchMatch - completeness (85.35%)
MSDG
MSDG - accuracy (82.47%)
MSDG - completeness (76.47%)
MSLP-MVS++
MSLP-MVS++ - accuracy (89.79%)
MSLP-MVS++ - completeness (84.79%)
MSP-MVS
MSP-MVS - accuracy (92.01%)
MSP-MVS - completeness (91.60%)
MVE
MVE - accuracy (34.14%)
MVE - completeness (20.24%)
MVS-HIRNet
MVS-HIRNet - accuracy (45.81%)
MVS-HIRNet - completeness (72.36%)
MVSTER
MVSTER - accuracy (70.06%)
MVSTER - completeness (82.97%)
MVS_0304
MVS_0304 - accuracy (86.71%)
MVS_0304 - completeness (91.79%)
MVS_111021_LR
MVS_111021_LR - accuracy (78.23%)
MVS_111021_LR - completeness (85.04%)
MVS_Test
MVS_Test - accuracy (74.99%)
MVS_Test - completeness (88.82%)
NCCC
NCCC - accuracy (87.25%)
NCCC - completeness (90.57%)
new-patchmatchnet
new-patchmatchnet - accuracy (53.57%)
new-patchmatchnet - completeness (59.89%)
new_pmnet
new_pmnet - accuracy (44.70%)
new_pmnet - completeness (45.31%)
NR-MVSNet
NR-MVSNet - accuracy (83.59%)
NR-MVSNet - completeness (75.87%)
N_pmnet
N_pmnet - accuracy (43.86%)
N_pmnet - completeness (62.78%)
OMC-MVS
OMC-MVS - accuracy (90.63%)
OMC-MVS - completeness (80.98%)
OpenMVS
OpenMVS - accuracy (79.85%)
OpenMVS - completeness (90.38%)
OPM-MVS
OPM-MVS - accuracy (89.35%)
OPM-MVS - completeness (84.34%)
our_test_3
our_test_3 - accuracy (70.91%)
our_test_3 - completeness (71.07%)
PatchMatch-RL
PatchMatch-RL - accuracy (69.87%)
PatchMatch-RL - completeness (75.75%)
PatchmatchNet
PatchmatchNet - accuracy (58.62%)
PatchmatchNet - completeness (82.83%)
Patchmtry
Patchmtry - accuracy (56.88%)
Patchmtry - completeness (78.06%)
PatchT
PatchT - accuracy (60.75%)
PatchT - completeness (75.68%)
PCF-MVS
PCF-MVS - accuracy (88.30%)
PCF-MVS - completeness (88.04%)
PEN-MVS
PEN-MVS - accuracy (88.05%)
PEN-MVS - completeness (66.00%)
PGM-MVS
PGM-MVS - accuracy (91.06%)
PGM-MVS - completeness (86.69%)
PHI-MVS
PHI-MVS - accuracy (87.56%)
PHI-MVS - completeness (91.57%)
PLC
PLC - accuracy (88.84%)
PLC - completeness (74.88%)
PM-MVS
PM-MVS - accuracy (72.37%)
PM-MVS - completeness (62.08%)
pm-mvs1
pm-mvs1 - accuracy (75.73%)
pm-mvs1 - completeness (77.07%)
PMMVS
PMMVS - accuracy (51.76%)
PMMVS - completeness (81.88%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (72.64%)
pmmvs-eth3d - completeness (67.77%)
PMMVS2
PMMVS2 - accuracy (36.69%)
PMMVS2 - completeness (26.73%)
pmmvs3
pmmvs3 - accuracy (57.10%)
pmmvs3 - completeness (52.66%)
pmmvs5
pmmvs5 - accuracy (66.78%)
pmmvs5 - completeness (77.33%)
pmmvs6
pmmvs6 - accuracy (77.51%)
pmmvs6 - completeness (72.98%)
pmnet_mix02
pmnet_mix02 - accuracy (50.44%)
pmnet_mix02 - completeness (71.33%)
PMVS
PMVS - accuracy (88.75%)
PMVS - completeness (24.79%)
PS-CasMVS
PS-CasMVS - accuracy (88.23%)
PS-CasMVS - completeness (65.54%)
PVSNet_Blended
PVSNet_Blended - accuracy (78.46%)
PVSNet_Blended - completeness (89.90%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (78.46%)
PVSNet_BlendedMVS - completeness (89.90%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (86.01%)
PVSNet_Blended_VisFu - completeness (87.16%)
QAPM
QAPM - accuracy (82.06%)
QAPM - completeness (92.00%)
RPMNet
RPMNet - accuracy (67.63%)
RPMNet - completeness (71.29%)
RPSCF
RPSCF - accuracy (88.40%)
RPSCF - completeness (58.95%)
SCA
SCA - accuracy (75.04%)
SCA - completeness (71.78%)
SD-MVS
SD-MVS - accuracy (89.79%)
SD-MVS - completeness (88.68%)
SED-MVS
SED-MVS - accuracy (89.65%)
SED-MVS - completeness (95.09%)
SF-MVS
SF-MVS - accuracy (87.90%)
SF-MVS - completeness (94.55%)
SMA-MVS
SMA-MVS - accuracy (90.44%)
SMA-MVS - completeness (90.71%)
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 (90.29%)
SteuartSystems-ACMMP - completeness (89.39%)
TAMVS
TAMVS - accuracy (56.89%)
TAMVS - completeness (77.57%)
TAPA-MVS
TAPA-MVS - accuracy (88.62%)
TAPA-MVS - completeness (80.78%)
TDRefinement
TDRefinement - accuracy (93.57%)
TDRefinement - completeness (65.06%)
test-mter
test-mter - accuracy (54.82%)
test-mter - completeness (77.40%)
test1
test1 - accuracy (77.36%)
test1 - completeness (78.65%)
test123
test123 - accuracy (0.48%)
test123 - completeness (0.01%)
testgi
testgi - accuracy (67.32%)
testgi - completeness (67.15%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (52.66%)
TESTMET0.1,1 - completeness (81.32%)
testmvs
testmvs - accuracy (0.36%)
testmvs - completeness (0.01%)
test_part1
test_part1 - accuracy (86.76%)
test_part1 - completeness (78.35%)
thisisatest0515
thisisatest0515 - accuracy (74.84%)
thisisatest0515 - completeness (75.65%)
thisisatest0530
thisisatest0530 - accuracy (73.56%)
thisisatest0530 - completeness (84.42%)
TinyColmap
TinyColmap - accuracy (81.44%)
TinyColmap - completeness (64.02%)
tmp_tt
tmp_tt - accuracy (6.42%)
tmp_tt - completeness (8.12%)
tpm
tpm - accuracy (53.78%)
tpm - completeness (78.38%)
tpm cat1
tpm cat1 - accuracy (65.91%)
tpm cat1 - completeness (81.51%)
tpmrst
tpmrst - accuracy (53.10%)
tpmrst - completeness (80.98%)
train_agg
train_agg - accuracy (82.72%)
train_agg - completeness (88.41%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (83.77%)
TranMVSNet+NR-MVSNet - completeness (75.57%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (75.99%)
TransMVSNet (Re) - completeness (74.69%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (90.61%)
TSAR-MVS + ACMM - completeness (86.53%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (87.69%)
TSAR-MVS + COLMAP - completeness (82.49%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (85.69%)
TSAR-MVS + GP. - completeness (88.25%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (90.98%)
TSAR-MVS + MP. - completeness (86.47%)
tttt0517
tttt0517 - accuracy (74.06%)
tttt0517 - completeness (83.96%)
UA-Net
UA-Net - accuracy (89.84%)
UA-Net - completeness (81.38%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (83.91%)
UGNet - completeness (82.58%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (84.21%)
UniMVSNet (Re) - completeness (77.90%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (83.72%)
UniMVSNet_ETH3D - completeness (73.22%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (83.83%)
UniMVSNet_NR-MVSNet - completeness (77.83%)
USDC
USDC - accuracy (78.95%)
USDC - completeness (71.84%)
Vis-MVSNet
Vis-MVSNet - accuracy (83.44%)
Vis-MVSNet - completeness (84.59%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (74.80%)
Vis-MVSNet (Re-imp) - completeness (78.74%)
WR-MVS_H
WR-MVS_H - accuracy (89.13%)
WR-MVS_H - completeness (67.58%)
X-MVS
X-MVS - accuracy (91.23%)
X-MVS - completeness (86.27%)
X-MVStestdata
X-MVStestdata - accuracy (91.23%)
X-MVStestdata - completeness (86.27%)
XVS
XVS - accuracy (91.23%)
XVS - completeness (86.27%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (87.90%)
xxxxxxxxxxxxxcwj - completeness (94.55%)
zzz-MVS
zzz-MVS - accuracy (86.59%)
zzz-MVS - completeness (87.62%)
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
:
-15.97 to 81.74
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
:
67.7
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