+
−
⇧
i
D
T
kicker (high-res multi-view) - Tolerance 5cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (93.82%)
3Dnovator - completeness (85.16%)
3Dnovator+
3Dnovator+ - accuracy (94.16%)
3Dnovator+ - completeness (87.09%)
ACMH
ACMH - accuracy (98.04%)
ACMH - completeness (54.79%)
ACMH+
ACMH+ - accuracy (96.72%)
ACMH+ - completeness (59.76%)
ACMM
ACMM - accuracy (94.35%)
ACMM - completeness (79.04%)
ACMMP
ACMMP - accuracy (92.47%)
ACMMP - completeness (90.97%)
ACMMPR
ACMMPR - accuracy (94.45%)
ACMMPR - completeness (93.32%)
ACMMP_NAP
ACMMP_NAP - accuracy (93.49%)
ACMMP_NAP - completeness (93.33%)
ACMP
ACMP - accuracy (92.33%)
ACMP - completeness (81.70%)
AdaColmap
AdaColmap - accuracy (87.97%)
AdaColmap - completeness (90.22%)
ADS-MVSNet
ADS-MVSNet - accuracy (87.31%)
ADS-MVSNet - completeness (72.58%)
ambc
ambc - accuracy (94.18%)
ambc - completeness (44.08%)
Anonymous20231206
Anonymous20231206 - accuracy (88.89%)
Anonymous20231206 - completeness (50.20%)
Anonymous202405211
Anonymous202405211 - accuracy (90.82%)
Anonymous202405211 - completeness (69.47%)
anonymousdsp
anonymousdsp - accuracy (94.29%)
anonymousdsp - completeness (50.54%)
APD-MVS
APD-MVS - accuracy (89.40%)
APD-MVS - completeness (95.71%)
APDe-MVS
APDe-MVS - accuracy (94.62%)
APDe-MVS - completeness (95.50%)
baseline1
baseline1 - accuracy (85.14%)
baseline1 - completeness (75.05%)
baseline2
baseline2 - accuracy (75.88%)
baseline2 - completeness (80.39%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (90.07%)
Baseline_NR-MVSNet - completeness (65.10%)
CANet
CANet - accuracy (84.77%)
CANet - completeness (90.87%)
CANet_DTU
CANet_DTU - accuracy (80.07%)
CANet_DTU - completeness (85.45%)
canonicalmvs
canonicalmvs - accuracy (93.07%)
canonicalmvs - completeness (87.83%)
casdiffmvs
casdiffmvs - accuracy (91.53%)
casdiffmvs - completeness (79.48%)
CDPH-MVS
CDPH-MVS - accuracy (87.21%)
CDPH-MVS - completeness (90.36%)
CDS-MVSNet
CDS-MVSNet - accuracy (83.26%)
CDS-MVSNet - completeness (59.01%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (83.95%)
CHOSEN 1792x2688 - completeness (76.17%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (77.25%)
CHOSEN 280x420 - completeness (78.99%)
CLD-MVS
CLD-MVS - accuracy (89.40%)
CLD-MVS - completeness (87.17%)
CMPMVS
CMPMVS - accuracy (79.32%)
CMPMVS - completeness (51.24%)
CNLPA
CNLPA - accuracy (92.85%)
CNLPA - completeness (90.90%)
CNVR-MVS
CNVR-MVS - accuracy (92.08%)
CNVR-MVS - completeness (94.86%)
COLMAP_ROB
COLMAP_ROB - accuracy (97.53%)
COLMAP_ROB - completeness (63.82%)
CostFormer
CostFormer - accuracy (79.19%)
CostFormer - completeness (80.86%)
CP-MVS
CP-MVS - accuracy (92.62%)
CP-MVS - completeness (92.12%)
CP-MVSNet
CP-MVSNet - accuracy (93.50%)
CP-MVSNet - completeness (52.45%)
CPTT-MVS
CPTT-MVS - accuracy (92.20%)
CPTT-MVS - completeness (89.87%)
CR-MVSNet
CR-MVSNet - accuracy (75.38%)
CR-MVSNet - completeness (74.05%)
CS-MVS
CS-MVS - accuracy (80.81%)
CS-MVS - completeness (87.63%)
CSCG
CSCG - accuracy (96.51%)
CSCG - completeness (88.74%)
CVMVSNet
CVMVSNet - accuracy (88.94%)
CVMVSNet - completeness (56.20%)
DCV-MVSNet
DCV-MVSNet - accuracy (92.76%)
DCV-MVSNet - completeness (75.17%)
DeepC-MVS
DeepC-MVS - accuracy (95.29%)
DeepC-MVS - completeness (89.25%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (92.98%)
DeepC-MVS_fast - completeness (93.31%)
DeepMVS_CX
DeepMVS_CX - accuracy (63.24%)
DeepMVS_CX - completeness (50.93%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (93.39%)
DeepPCF-MVS - completeness (97.01%)
DELS-MVS
DELS-MVS - accuracy (87.78%)
DELS-MVS - completeness (77.87%)
diffmvs
diffmvs - accuracy (89.88%)
diffmvs - completeness (82.71%)
DPE-MVS
DPE-MVS - accuracy (92.38%)
DPE-MVS - completeness (96.34%)
DPM-MVS
DPM-MVS - accuracy (89.59%)
DPM-MVS - completeness (92.88%)
dps
dps - accuracy (74.37%)
dps - completeness (75.91%)
DTE-MVSNet
DTE-MVSNet - accuracy (95.30%)
DTE-MVSNet - completeness (50.53%)
DU-MVS
DU-MVS - accuracy (89.97%)
DU-MVS - completeness (65.39%)
DVP-MVS
DVP-MVS - accuracy (95.47%)
DVP-MVS - completeness (96.85%)
E-PMN
E-PMN - accuracy (86.66%)
E-PMN - completeness (15.25%)
Effi-MVS+
Effi-MVS+ - accuracy (85.27%)
Effi-MVS+ - completeness (74.15%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (81.74%)
Effi-MVS+-dtu - completeness (67.36%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (92.77%)
EG-PatchMatch MVS - completeness (43.95%)
EIA-MVS
EIA-MVS - accuracy (78.01%)
EIA-MVS - completeness (87.61%)
EMVS
EMVS - accuracy (86.38%)
EMVS - completeness (15.65%)
EPMVS
EPMVS - accuracy (82.63%)
EPMVS - completeness (79.43%)
EPNet
EPNet - accuracy (80.96%)
EPNet - completeness (91.14%)
EPNet_dtu
EPNet_dtu - accuracy (78.11%)
EPNet_dtu - completeness (83.28%)
EPP-MVSNet
EPP-MVSNet - accuracy (91.74%)
EPP-MVSNet - completeness (73.79%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (81.22%)
ET-MVSNet_ETH3D - completeness (83.13%)
ETV-MVS
ETV-MVS - accuracy (78.90%)
ETV-MVS - completeness (92.59%)
EU-MVSNet
EU-MVSNet - accuracy (92.45%)
EU-MVSNet - completeness (48.47%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (83.98%)
Fast-Effi-MVS+ - completeness (72.99%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (78.94%)
Fast-Effi-MVS+-dtu - completeness (67.64%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (93.24%)
FC-MVSNet-test - completeness (65.58%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (91.13%)
FC-MVSNet-train - completeness (70.90%)
FMVSNet1
FMVSNet1 - accuracy (93.18%)
FMVSNet1 - completeness (57.08%)
FMVSNet2
FMVSNet2 - accuracy (86.53%)
FMVSNet2 - completeness (72.97%)
FMVSNet3
FMVSNet3 - accuracy (79.40%)
FMVSNet3 - completeness (83.02%)
FMVSNet5
FMVSNet5 - accuracy (69.54%)
FMVSNet5 - completeness (77.27%)
FPMVS
FPMVS - accuracy (91.59%)
FPMVS - completeness (46.66%)
GA-MVS
GA-MVS - accuracy (83.82%)
GA-MVS - completeness (60.79%)
GBi-Net
GBi-Net - accuracy (79.40%)
GBi-Net - completeness (83.02%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (74.71%)
GG-mvs-BLEND - completeness (85.07%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (95.29%)
gg-mvs-nofinetune - completeness (35.68%)
Gipuma
Gipuma - accuracy (97.82%)
Gipuma - completeness (38.87%)
gm-plane-assit
gm-plane-assit - accuracy (92.15%)
gm-plane-assit - completeness (34.68%)
HFP-MVS
HFP-MVS - accuracy (94.45%)
HFP-MVS - completeness (93.79%)
HPM-MVS++
HPM-MVS++ - accuracy (91.91%)
HPM-MVS++ - completeness (95.91%)
HQP-MVS
HQP-MVS - accuracy (88.54%)
HQP-MVS - completeness (88.52%)
HyFIR lowres test
HyFIR lowres test - accuracy (84.06%)
HyFIR lowres test - completeness (69.81%)
IB-MVS
IB-MVS - accuracy (78.24%)
IB-MVS - completeness (74.95%)
IS_MVSNet
IS_MVSNet - accuracy (88.10%)
IS_MVSNet - completeness (75.05%)
IterMVS
IterMVS - accuracy (86.77%)
IterMVS - completeness (63.57%)
IterMVS-LS
IterMVS-LS - accuracy (90.82%)
IterMVS-LS - completeness (66.17%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (87.05%)
IterMVS-SCA-FT - completeness (63.67%)
LGP-MVS_train
LGP-MVS_train - accuracy (90.81%)
LGP-MVS_train - completeness (81.26%)
LS3D
LS3D - accuracy (94.92%)
LS3D - completeness (76.81%)
LTVRE_ROB
LTVRE_ROB - accuracy (98.61%)
LTVRE_ROB - completeness (34.01%)
MAR-MVS
MAR-MVS - accuracy (81.66%)
MAR-MVS - completeness (89.23%)
MCST-MVS
MCST-MVS - accuracy (90.08%)
MCST-MVS - completeness (94.41%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (91.64%)
MDA-MVSNet-bldmvs - completeness (43.65%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (79.07%)
MDTV_nov1_ep13 - completeness (78.63%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (88.86%)
MDTV_nov1_ep13_2view - completeness (55.92%)
MIMVSNet
MIMVSNet - accuracy (85.28%)
MIMVSNet - completeness (60.85%)
MIMVSNet1
MIMVSNet1 - accuracy (95.92%)
MIMVSNet1 - completeness (39.36%)
MP-MVS
MP-MVS - accuracy (91.39%)
MP-MVS - completeness (90.27%)
MS-PatchMatch
MS-PatchMatch - accuracy (85.86%)
MS-PatchMatch - completeness (70.79%)
MSDG
MSDG - accuracy (90.24%)
MSDG - completeness (72.84%)
MSLP-MVS++
MSLP-MVS++ - accuracy (91.45%)
MSLP-MVS++ - completeness (88.37%)
MSP-MVS
MSP-MVS - accuracy (94.15%)
MSP-MVS - completeness (96.68%)
MVE
MVE - accuracy (87.14%)
MVE - completeness (12.51%)
MVS-HIRNet
MVS-HIRNet - accuracy (70.76%)
MVS-HIRNet - completeness (55.42%)
MVSTER
MVSTER - accuracy (74.16%)
MVSTER - completeness (91.37%)
MVS_0304
MVS_0304 - accuracy (85.99%)
MVS_0304 - completeness (87.16%)
MVS_111021_LR
MVS_111021_LR - accuracy (91.26%)
MVS_111021_LR - completeness (89.08%)
MVS_Test
MVS_Test - accuracy (82.80%)
MVS_Test - completeness (84.31%)
NCCC
NCCC - accuracy (92.36%)
NCCC - completeness (94.47%)
new-patchmatchnet
new-patchmatchnet - accuracy (94.47%)
new-patchmatchnet - completeness (41.09%)
new_pmnet
new_pmnet - accuracy (84.41%)
new_pmnet - completeness (47.55%)
NP-MVS
NP-MVS - accuracy (85.48%)
NP-MVS - completeness (89.55%)
NR-MVSNet
NR-MVSNet - accuracy (89.97%)
NR-MVSNet - completeness (65.39%)
N_pmnet
N_pmnet - accuracy (92.38%)
N_pmnet - completeness (51.90%)
OMC-MVS
OMC-MVS - accuracy (94.20%)
OMC-MVS - completeness (92.32%)
OpenMVS
OpenMVS - accuracy (86.10%)
OpenMVS - completeness (79.19%)
OPM-MVS
OPM-MVS - accuracy (95.27%)
OPM-MVS - completeness (62.39%)
PatchMatch-RL
PatchMatch-RL - accuracy (84.75%)
PatchMatch-RL - completeness (77.33%)
PatchmatchNet
PatchmatchNet - accuracy (82.39%)
PatchmatchNet - completeness (79.43%)
PatchT
PatchT - accuracy (75.88%)
PatchT - completeness (72.00%)
PCF-MVS
PCF-MVS - accuracy (87.57%)
PCF-MVS - completeness (77.87%)
PEN-MVS
PEN-MVS - accuracy (95.09%)
PEN-MVS - completeness (51.21%)
PGM-MVS
PGM-MVS - accuracy (90.25%)
PGM-MVS - completeness (90.04%)
PHI-MVS
PHI-MVS - accuracy (88.96%)
PHI-MVS - completeness (92.52%)
PLC
PLC - accuracy (91.69%)
PLC - completeness (86.76%)
PM-MVS
PM-MVS - accuracy (91.31%)
PM-MVS - completeness (58.13%)
pm-mvs1
pm-mvs1 - accuracy (95.73%)
pm-mvs1 - completeness (46.55%)
PMMVS
PMMVS - accuracy (77.02%)
PMMVS - completeness (86.30%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (90.98%)
pmmvs-eth3d - completeness (52.59%)
PMMVS2
PMMVS2 - accuracy (88.50%)
PMMVS2 - completeness (22.21%)
pmmvs3
pmmvs3 - accuracy (78.88%)
pmmvs3 - completeness (35.31%)
pmmvs5
pmmvs5 - accuracy (83.34%)
pmmvs5 - completeness (53.84%)
pmmvs6
pmmvs6 - accuracy (98.51%)
pmmvs6 - completeness (36.05%)
pmnet_mix02
pmnet_mix02 - accuracy (91.50%)
pmnet_mix02 - completeness (57.87%)
PMVS
PMVS - accuracy (94.43%)
PMVS - completeness (28.25%)
PS-CasMVS
PS-CasMVS - accuracy (94.71%)
PS-CasMVS - completeness (50.64%)
PVSNet_Blended
PVSNet_Blended - accuracy (80.54%)
PVSNet_Blended - completeness (89.78%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (80.54%)
PVSNet_BlendedMVS - completeness (89.78%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (88.08%)
PVSNet_Blended_VisFu - completeness (72.53%)
QAPM
QAPM - accuracy (91.49%)
QAPM - completeness (80.58%)
RPMNet
RPMNet - accuracy (75.38%)
RPMNet - completeness (74.05%)
RPSCF
RPSCF - accuracy (95.31%)
RPSCF - completeness (74.84%)
SCA
SCA - accuracy (82.72%)
SCA - completeness (79.95%)
SD-MVS
SD-MVS - accuracy (94.03%)
SD-MVS - completeness (94.80%)
SED-MVS
SED-MVS - accuracy (94.20%)
SED-MVS - completeness (97.14%)
SF-MVS
SF-MVS - accuracy (93.11%)
SF-MVS - completeness (94.87%)
SMA-MVS
SMA-MVS - accuracy (94.05%)
SMA-MVS - completeness (94.96%)
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 (91.49%)
SteuartSystems-ACMMP - completeness (92.62%)
TAMVS
TAMVS - accuracy (84.06%)
TAMVS - completeness (53.52%)
TAPA-MVS
TAPA-MVS - accuracy (93.43%)
TAPA-MVS - completeness (89.99%)
TDRefinement
TDRefinement - accuracy (98.24%)
TDRefinement - completeness (59.62%)
test-mter
test-mter - accuracy (71.06%)
test-mter - completeness (76.37%)
test1
test1 - accuracy (79.40%)
test1 - completeness (83.02%)
test123
test123 - accuracy (2.78%)
test123 - completeness (0.77%)
testgi
testgi - accuracy (93.23%)
testgi - completeness (48.77%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (70.11%)
TESTMET0.1,1 - completeness (77.71%)
testmvs
testmvs - accuracy (3.59%)
testmvs - completeness (0.94%)
test_part1
test_part1 - accuracy (98.92%)
test_part1 - completeness (55.24%)
thisisatest0515
thisisatest0515 - accuracy (91.61%)
thisisatest0515 - completeness (59.70%)
thisisatest0530
thisisatest0530 - accuracy (82.96%)
thisisatest0530 - completeness (81.35%)
TinyColmap
TinyColmap - accuracy (93.97%)
TinyColmap - completeness (56.58%)
tmp_tt
tmp_tt - accuracy (54.52%)
tmp_tt - completeness (82.57%)
tpm
tpm - accuracy (79.30%)
tpm - completeness (65.64%)
tpm cat1
tpm cat1 - accuracy (79.24%)
tpm cat1 - completeness (75.72%)
tpmrst
tpmrst - accuracy (80.08%)
tpmrst - completeness (77.19%)
train_agg
train_agg - accuracy (88.12%)
train_agg - completeness (93.33%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (92.62%)
TranMVSNet+NR-MVSNet - completeness (61.99%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (97.15%)
TransMVSNet (Re) - completeness (43.19%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (93.84%)
TSAR-MVS + ACMM - completeness (92.99%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (92.18%)
TSAR-MVS + COLMAP - completeness (91.29%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (90.89%)
TSAR-MVS + GP. - completeness (94.24%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (93.25%)
TSAR-MVS + MP. - completeness (95.26%)
tttt0517
tttt0517 - accuracy (82.77%)
tttt0517 - completeness (81.21%)
UA-Net
UA-Net - accuracy (92.78%)
UA-Net - completeness (60.47%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (91.35%)
UGNet - completeness (73.83%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (90.36%)
UniMVSNet (Re) - completeness (65.76%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (97.86%)
UniMVSNet_ETH3D - completeness (48.08%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (90.04%)
UniMVSNet_NR-MVSNet - completeness (65.59%)
USDC
USDC - accuracy (93.49%)
USDC - completeness (71.69%)
Vis-MVSNet
Vis-MVSNet - accuracy (91.95%)
Vis-MVSNet - completeness (62.58%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (89.21%)
Vis-MVSNet (Re-imp) - completeness (74.05%)
WR-MVS_H
WR-MVS_H - accuracy (94.40%)
WR-MVS_H - completeness (51.81%)
X-MVS
X-MVS - accuracy (92.30%)
X-MVS - completeness (90.73%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (93.11%)
xxxxxxxxxxxxxcwj - completeness (94.87%)
zzz-MVS
zzz-MVS - accuracy (94.56%)
zzz-MVS - completeness (93.63%)
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
:
-2.72 to 7.60
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
:
7.2
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