+
−
⇧
i
D
T
pipes (high-res multi-view) - Tolerance 5cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (93.37%)
3Dnovator - completeness (82.15%)
3Dnovator+
3Dnovator+ - accuracy (93.71%)
3Dnovator+ - completeness (85.37%)
9.14
9.14 - accuracy (93.19%)
9.14 - completeness (91.16%)
ACMH
ACMH - accuracy (99.25%)
ACMH - completeness (47.28%)
ACMH+
ACMH+ - accuracy (99.11%)
ACMH+ - completeness (48.69%)
ACMM
ACMM - accuracy (98.23%)
ACMM - completeness (60.84%)
ACMMP
ACMMP - accuracy (98.06%)
ACMMP - completeness (74.20%)
ACMMPR
ACMMPR - accuracy (97.35%)
ACMMPR - completeness (82.10%)
ACMMP_NAP
ACMMP_NAP - accuracy (94.11%)
ACMMP_NAP - completeness (86.84%)
ACMP
ACMP - accuracy (98.73%)
ACMP - completeness (60.63%)
AdaColmap
AdaColmap - accuracy (91.04%)
AdaColmap - completeness (73.67%)
ADS-MVSNet
ADS-MVSNet - accuracy (76.90%)
ADS-MVSNet - completeness (61.46%)
ambc
ambc - accuracy (96.30%)
ambc - completeness (10.64%)
Anonymous20231206
Anonymous20231206 - accuracy (96.82%)
Anonymous20231206 - completeness (37.05%)
Anonymous202405211
Anonymous202405211 - accuracy (95.85%)
Anonymous202405211 - completeness (63.84%)
anonymousdsp
anonymousdsp - accuracy (99.08%)
anonymousdsp - completeness (45.63%)
APD-MVS
APD-MVS - accuracy (97.69%)
APD-MVS - completeness (86.28%)
APDe-MVS
APDe-MVS - accuracy (98.13%)
APDe-MVS - completeness (87.97%)
baseline1
baseline1 - accuracy (76.09%)
baseline1 - completeness (72.20%)
baseline2
baseline2 - accuracy (71.15%)
baseline2 - completeness (68.44%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (97.89%)
Baseline_NR-MVSNet - completeness (44.28%)
CANet
CANet - accuracy (95.25%)
CANet - completeness (84.82%)
CANet_DTU
CANet_DTU - accuracy (93.68%)
CANet_DTU - completeness (69.94%)
canonicalmvs
canonicalmvs - accuracy (93.78%)
canonicalmvs - completeness (68.66%)
casdiffmvs
casdiffmvs - accuracy (98.64%)
casdiffmvs - completeness (64.34%)
CDPH-MVS
CDPH-MVS - accuracy (96.06%)
CDPH-MVS - completeness (80.69%)
CDS-MVSNet
CDS-MVSNet - accuracy (89.93%)
CDS-MVSNet - completeness (62.67%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (89.34%)
CHOSEN 1792x2688 - completeness (61.08%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (76.17%)
CHOSEN 280x420 - completeness (83.95%)
CLD-MVS
CLD-MVS - accuracy (97.36%)
CLD-MVS - completeness (65.81%)
CMPMVS
CMPMVS - accuracy (91.07%)
CMPMVS - completeness (44.40%)
CNLPA
CNLPA - accuracy (94.67%)
CNLPA - completeness (71.53%)
CNVR-MVS
CNVR-MVS - accuracy (95.35%)
CNVR-MVS - completeness (90.83%)
COLMAP_ROB
COLMAP_ROB - accuracy (98.76%)
COLMAP_ROB - completeness (49.13%)
CostFormer
CostFormer - accuracy (69.20%)
CostFormer - completeness (73.74%)
CP-MVS
CP-MVS - accuracy (98.03%)
CP-MVS - completeness (82.37%)
CP-MVSNet
CP-MVSNet - accuracy (98.44%)
CP-MVSNet - completeness (38.37%)
CPTT-MVS
CPTT-MVS - accuracy (97.56%)
CPTT-MVS - completeness (81.12%)
CR-MVSNet
CR-MVSNet - accuracy (67.88%)
CR-MVSNet - completeness (71.38%)
CS-MVS
CS-MVS - accuracy (90.28%)
CS-MVS - completeness (78.24%)
CSCG
CSCG - accuracy (98.55%)
CSCG - completeness (86.53%)
CVMVSNet
CVMVSNet - accuracy (85.71%)
CVMVSNet - completeness (59.22%)
DCV-MVSNet
DCV-MVSNet - accuracy (97.16%)
DCV-MVSNet - completeness (66.56%)
DeepC-MVS
DeepC-MVS - accuracy (96.92%)
DeepC-MVS - completeness (77.05%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (95.45%)
DeepC-MVS_fast - completeness (84.23%)
DeepMVS_CX
DeepMVS_CX - accuracy (69.82%)
DeepMVS_CX - completeness (20.18%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (94.15%)
DeepPCF-MVS - completeness (88.90%)
DELS-MVS
DELS-MVS - accuracy (95.28%)
DELS-MVS - completeness (75.49%)
diffmvs
diffmvs - accuracy (97.71%)
diffmvs - completeness (63.90%)
DPE-MVS
DPE-MVS - accuracy (97.97%)
DPE-MVS - completeness (92.26%)
DPM-MVS
DPM-MVS - accuracy (88.64%)
DPM-MVS - completeness (92.95%)
dps
dps - accuracy (62.18%)
dps - completeness (57.85%)
DTE-MVSNet
DTE-MVSNet - accuracy (98.80%)
DTE-MVSNet - completeness (37.79%)
DU-MVS
DU-MVS - accuracy (98.07%)
DU-MVS - completeness (42.81%)
DVP-MVS
DVP-MVS - accuracy (97.72%)
DVP-MVS - completeness (93.02%)
E-PMN
E-PMN - accuracy (81.74%)
E-PMN - completeness (4.53%)
Effi-MVS+
Effi-MVS+ - accuracy (95.34%)
Effi-MVS+ - completeness (60.51%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (95.91%)
Effi-MVS+-dtu - completeness (57.50%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (98.61%)
EG-PatchMatch MVS - completeness (45.43%)
EIA-MVS
EIA-MVS - accuracy (91.95%)
EIA-MVS - completeness (71.12%)
EMVS
EMVS - accuracy (80.19%)
EMVS - completeness (4.68%)
EPMVS
EPMVS - accuracy (68.67%)
EPMVS - completeness (70.73%)
EPNet
EPNet - accuracy (85.88%)
EPNet - completeness (80.40%)
EPNet_dtu
EPNet_dtu - accuracy (89.74%)
EPNet_dtu - completeness (67.73%)
EPP-MVSNet
EPP-MVSNet - accuracy (84.27%)
EPP-MVSNet - completeness (80.63%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (66.79%)
ET-MVSNet_ETH3D - completeness (76.01%)
ETV-MVS
ETV-MVS - accuracy (89.85%)
ETV-MVS - completeness (76.42%)
EU-MVSNet
EU-MVSNet - accuracy (97.05%)
EU-MVSNet - completeness (40.06%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (96.22%)
Fast-Effi-MVS+ - completeness (53.20%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (93.14%)
Fast-Effi-MVS+-dtu - completeness (54.07%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (93.86%)
FC-MVSNet-test - completeness (60.40%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (96.43%)
FC-MVSNet-train - completeness (56.45%)
FMVSNet1
FMVSNet1 - accuracy (97.48%)
FMVSNet1 - completeness (57.41%)
FMVSNet2
FMVSNet2 - accuracy (92.73%)
FMVSNet2 - completeness (66.56%)
FMVSNet3
FMVSNet3 - accuracy (87.05%)
FMVSNet3 - completeness (73.48%)
FMVSNet5
FMVSNet5 - accuracy (65.44%)
FMVSNet5 - completeness (71.48%)
FPMVS
FPMVS - accuracy (89.73%)
FPMVS - completeness (27.51%)
GA-MVS
GA-MVS - accuracy (81.94%)
GA-MVS - completeness (49.07%)
GBi-Net
GBi-Net - accuracy (87.05%)
GBi-Net - completeness (73.48%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (83.06%)
GG-mvs-BLEND - completeness (83.74%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (76.38%)
gg-mvs-nofinetune - completeness (77.73%)
Gipuma
Gipuma - accuracy (97.88%)
Gipuma - completeness (7.41%)
gm-plane-assit
gm-plane-assit - accuracy (44.65%)
gm-plane-assit - completeness (57.09%)
HFP-MVS
HFP-MVS - accuracy (96.95%)
HFP-MVS - completeness (83.94%)
HPM-MVS++
HPM-MVS++ - accuracy (95.07%)
HPM-MVS++ - completeness (92.63%)
HQP-MVS
HQP-MVS - accuracy (96.25%)
HQP-MVS - completeness (68.91%)
HyFIR lowres test
HyFIR lowres test - accuracy (85.64%)
HyFIR lowres test - completeness (64.66%)
IB-MVS
IB-MVS - accuracy (93.45%)
IB-MVS - completeness (55.92%)
IS_MVSNet
IS_MVSNet - accuracy (88.30%)
IS_MVSNet - completeness (76.89%)
IterMVS
IterMVS - accuracy (86.91%)
IterMVS - completeness (59.09%)
IterMVS-LS
IterMVS-LS - accuracy (90.97%)
IterMVS-LS - completeness (64.31%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (87.25%)
IterMVS-SCA-FT - completeness (59.15%)
LGP-MVS_train
LGP-MVS_train - accuracy (98.86%)
LGP-MVS_train - completeness (62.11%)
LS3D
LS3D - accuracy (95.11%)
LS3D - completeness (58.53%)
LTVRE_ROB
LTVRE_ROB - accuracy (98.57%)
LTVRE_ROB - completeness (35.58%)
MAR-MVS
MAR-MVS - accuracy (93.42%)
MAR-MVS - completeness (74.49%)
MCST-MVS
MCST-MVS - accuracy (95.99%)
MCST-MVS - completeness (90.97%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (94.35%)
MDA-MVSNet-bldmvs - completeness (22.11%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (73.77%)
MDTV_nov1_ep13 - completeness (72.80%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (96.21%)
MDTV_nov1_ep13_2view - completeness (43.27%)
MIMVSNet
MIMVSNet - accuracy (90.88%)
MIMVSNet - completeness (49.48%)
MIMVSNet1
MIMVSNet1 - accuracy (98.21%)
MIMVSNet1 - completeness (33.07%)
MP-MVS
MP-MVS - accuracy (96.43%)
MP-MVS - completeness (84.88%)
mPP-MVS
mPP-MVS - accuracy (97.65%)
mPP-MVS - completeness (80.22%)
MS-PatchMatch
MS-PatchMatch - accuracy (89.29%)
MS-PatchMatch - completeness (70.62%)
MSDG
MSDG - accuracy (94.59%)
MSDG - completeness (54.00%)
MSLP-MVS++
MSLP-MVS++ - accuracy (96.12%)
MSLP-MVS++ - completeness (82.60%)
MSP-MVS
MSP-MVS - accuracy (98.37%)
MSP-MVS - completeness (89.47%)
MTAPA
MTAPA - accuracy (96.88%)
MTAPA - completeness (85.84%)
MTMP
MTMP - accuracy (97.25%)
MTMP - completeness (84.13%)
MVE
MVE - accuracy (85.30%)
MVE - completeness (3.82%)
MVS-HIRNet
MVS-HIRNet - accuracy (81.04%)
MVS-HIRNet - completeness (43.48%)
MVSTER
MVSTER - accuracy (66.81%)
MVSTER - completeness (85.25%)
MVS_0304
MVS_0304 - accuracy (97.08%)
MVS_0304 - completeness (83.36%)
MVS_111021_LR
MVS_111021_LR - accuracy (96.22%)
MVS_111021_LR - completeness (74.22%)
MVS_Test
MVS_Test - accuracy (95.02%)
MVS_Test - completeness (68.78%)
NCCC
NCCC - accuracy (95.55%)
NCCC - completeness (89.32%)
new-patchmatchnet
new-patchmatchnet - accuracy (97.88%)
new-patchmatchnet - completeness (28.22%)
new_pmnet
new_pmnet - accuracy (91.53%)
new_pmnet - completeness (28.66%)
NR-MVSNet
NR-MVSNet - accuracy (98.39%)
NR-MVSNet - completeness (39.87%)
N_pmnet
N_pmnet - accuracy (95.62%)
N_pmnet - completeness (35.63%)
OMC-MVS
OMC-MVS - accuracy (97.73%)
OMC-MVS - completeness (77.83%)
OpenMVS
OpenMVS - accuracy (93.07%)
OpenMVS - completeness (79.04%)
OPM-MVS
OPM-MVS - accuracy (98.85%)
OPM-MVS - completeness (64.33%)
PatchMatch-RL
PatchMatch-RL - accuracy (90.66%)
PatchMatch-RL - completeness (48.10%)
PatchmatchNet
PatchmatchNet - accuracy (70.96%)
PatchmatchNet - completeness (76.02%)
PatchT
PatchT - accuracy (66.71%)
PatchT - completeness (66.70%)
PCF-MVS
PCF-MVS - accuracy (93.97%)
PCF-MVS - completeness (77.86%)
PEN-MVS
PEN-MVS - accuracy (99.16%)
PEN-MVS - completeness (38.51%)
PGM-MVS
PGM-MVS - accuracy (97.18%)
PGM-MVS - completeness (80.96%)
PHI-MVS
PHI-MVS - accuracy (95.32%)
PHI-MVS - completeness (87.11%)
PLC
PLC - accuracy (93.91%)
PLC - completeness (71.01%)
PM-MVS
PM-MVS - accuracy (96.64%)
PM-MVS - completeness (31.31%)
pm-mvs1
pm-mvs1 - accuracy (98.29%)
pm-mvs1 - completeness (48.20%)
PMMVS
PMMVS - accuracy (91.12%)
PMMVS - completeness (70.88%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (97.02%)
pmmvs-eth3d - completeness (32.79%)
PMMVS2
PMMVS2 - accuracy (96.44%)
PMMVS2 - completeness (14.13%)
pmmvs3
pmmvs3 - accuracy (91.96%)
pmmvs3 - completeness (26.96%)
pmmvs5
pmmvs5 - accuracy (96.15%)
pmmvs5 - completeness (41.47%)
pmmvs6
pmmvs6 - accuracy (99.53%)
pmmvs6 - completeness (43.45%)
pmnet_mix02
pmnet_mix02 - accuracy (95.86%)
pmnet_mix02 - completeness (40.99%)
PMVS
PMVS - accuracy (95.37%)
PMVS - completeness (26.15%)
PS-CasMVS
PS-CasMVS - accuracy (98.97%)
PS-CasMVS - completeness (37.46%)
PVSNet_Blended
PVSNet_Blended - accuracy (95.51%)
PVSNet_Blended - completeness (66.07%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (95.51%)
PVSNet_BlendedMVS - completeness (66.07%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (92.20%)
PVSNet_Blended_VisFu - completeness (77.19%)
QAPM
QAPM - accuracy (91.70%)
QAPM - completeness (84.24%)
RPMNet
RPMNet - accuracy (61.99%)
RPMNet - completeness (71.91%)
RPSCF
RPSCF - accuracy (98.04%)
RPSCF - completeness (67.39%)
SCA
SCA - accuracy (73.08%)
SCA - completeness (77.84%)
SD-MVS
SD-MVS - accuracy (96.78%)
SD-MVS - completeness (90.14%)
SED-MVS
SED-MVS - accuracy (97.49%)
SED-MVS - completeness (93.25%)
SF-MVS
SF-MVS - accuracy (97.07%)
SF-MVS - completeness (88.42%)
SMA-MVS
SMA-MVS - accuracy (94.53%)
SMA-MVS - completeness (90.99%)
sosnet
sosnet - accuracy (0.00%)
sosnet - completeness (0.00%)
sosnet-low-res
sosnet-low-res - accuracy (0.00%)
sosnet-low-res - completeness (0.00%)
SR-MVS
SR-MVS - accuracy (97.77%)
SR-MVS - completeness (87.60%)
SteuartSystems-ACMMP
SteuartSystems-ACMMP - accuracy (96.89%)
SteuartSystems-ACMMP - completeness (85.55%)
TAMVS
TAMVS - accuracy (88.27%)
TAMVS - completeness (56.93%)
TAPA-MVS
TAPA-MVS - accuracy (96.88%)
TAPA-MVS - completeness (75.03%)
TDRefinement
TDRefinement - accuracy (97.86%)
TDRefinement - completeness (42.40%)
test-mter
test-mter - accuracy (71.83%)
test-mter - completeness (75.94%)
test1
test1 - accuracy (87.05%)
test1 - completeness (73.48%)
test123
test123 - accuracy (1.98%)
test123 - completeness (0.02%)
testgi
testgi - accuracy (97.96%)
testgi - completeness (40.35%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (71.60%)
TESTMET0.1,1 - completeness (77.47%)
testmvs
testmvs - accuracy (2.93%)
testmvs - completeness (0.08%)
test_part1
test_part1 - accuracy (99.66%)
test_part1 - completeness (59.61%)
thisisatest0515
thisisatest0515 - accuracy (95.71%)
thisisatest0515 - completeness (50.36%)
thisisatest0530
thisisatest0530 - accuracy (70.32%)
thisisatest0530 - completeness (77.64%)
TinyColmap
TinyColmap - accuracy (95.29%)
TinyColmap - completeness (33.53%)
tmp_tt
tmp_tt - accuracy (38.68%)
tmp_tt - completeness (47.51%)
tpm
tpm - accuracy (64.78%)
tpm - completeness (61.09%)
tpm cat1
tpm cat1 - accuracy (63.62%)
tpm cat1 - completeness (64.41%)
tpmrst
tpmrst - accuracy (66.88%)
tpmrst - completeness (64.58%)
train_agg
train_agg - accuracy (95.78%)
train_agg - completeness (88.27%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (98.63%)
TranMVSNet+NR-MVSNet - completeness (43.07%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (97.89%)
TransMVSNet (Re) - completeness (42.37%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (95.24%)
TSAR-MVS + ACMM - completeness (86.64%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (95.27%)
TSAR-MVS + COLMAP - completeness (59.46%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (94.38%)
TSAR-MVS + GP. - completeness (89.62%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (96.57%)
TSAR-MVS + MP. - completeness (88.19%)
tttt0517
tttt0517 - accuracy (70.05%)
tttt0517 - completeness (77.46%)
UA-Net
UA-Net - accuracy (95.02%)
UA-Net - completeness (84.08%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (95.48%)
UGNet - completeness (73.71%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (98.13%)
UniMVSNet (Re) - completeness (46.49%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (99.60%)
UniMVSNet_ETH3D - completeness (40.56%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (97.25%)
UniMVSNet_NR-MVSNet - completeness (48.42%)
USDC
USDC - accuracy (96.68%)
USDC - completeness (42.58%)
Vis-MVSNet
Vis-MVSNet - accuracy (96.26%)
Vis-MVSNet - completeness (69.49%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (89.07%)
Vis-MVSNet (Re-imp) - completeness (76.52%)
WR-MVS_H
WR-MVS_H - accuracy (98.89%)
WR-MVS_H - completeness (42.77%)
X-MVS
X-MVS - accuracy (96.82%)
X-MVS - completeness (82.05%)
X-MVStestdata
X-MVStestdata - accuracy (96.82%)
X-MVStestdata - completeness (82.05%)
XVS
XVS - accuracy (96.82%)
XVS - completeness (82.05%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (98.96%)
xxxxxxxxxxxxxcwj - completeness (55.37%)
zzz-MVS
zzz-MVS - accuracy (96.96%)
zzz-MVS - completeness (85.33%)
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
:
-6.51 to 16.63
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
:
16.0
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