+
−
⇧
i
D
T
meadow (high-res multi-view) - Tolerance 5cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (92.38%)
3Dnovator - completeness (83.66%)
3Dnovator+
3Dnovator+ - accuracy (94.29%)
3Dnovator+ - completeness (85.94%)
ACMH
ACMH - accuracy (95.38%)
ACMH - completeness (46.16%)
ACMH+
ACMH+ - accuracy (90.50%)
ACMH+ - completeness (51.63%)
ACMM
ACMM - accuracy (93.81%)
ACMM - completeness (74.18%)
ACMMP
ACMMP - accuracy (93.13%)
ACMMP - completeness (78.62%)
ACMMPR
ACMMPR - accuracy (94.19%)
ACMMPR - completeness (84.78%)
ACMMP_NAP
ACMMP_NAP - accuracy (93.99%)
ACMMP_NAP - completeness (83.71%)
ACMP
ACMP - accuracy (92.31%)
ACMP - completeness (72.52%)
AdaColmap
AdaColmap - accuracy (91.28%)
AdaColmap - completeness (86.17%)
ADS-MVSNet
ADS-MVSNet - accuracy (76.76%)
ADS-MVSNet - completeness (49.17%)
ambc
ambc - accuracy (96.46%)
ambc - completeness (35.81%)
Anonymous20231206
Anonymous20231206 - accuracy (75.03%)
Anonymous20231206 - completeness (36.68%)
anonymousdsp
anonymousdsp - accuracy (96.10%)
anonymousdsp - completeness (42.42%)
APD-MVS
APD-MVS - accuracy (90.35%)
APD-MVS - completeness (89.57%)
APDe-MVS
APDe-MVS - accuracy (89.80%)
APDe-MVS - completeness (92.19%)
baseline1
baseline1 - accuracy (77.26%)
baseline1 - completeness (65.96%)
baseline2
baseline2 - accuracy (85.23%)
baseline2 - completeness (63.94%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (90.17%)
Baseline_NR-MVSNet - completeness (48.78%)
CANet
CANet - accuracy (93.36%)
CANet - completeness (81.90%)
CANet_DTU
CANet_DTU - accuracy (90.71%)
CANet_DTU - completeness (50.54%)
canonicalmvs
canonicalmvs - accuracy (88.47%)
canonicalmvs - completeness (77.70%)
casdiffmvs
casdiffmvs - accuracy (84.53%)
casdiffmvs - completeness (77.59%)
CDPH-MVS
CDPH-MVS - accuracy (91.25%)
CDPH-MVS - completeness (67.93%)
CDS-MVSNet
CDS-MVSNet - accuracy (80.52%)
CDS-MVSNet - completeness (62.95%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (82.32%)
CHOSEN 1792x2688 - completeness (61.32%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (78.02%)
CHOSEN 280x420 - completeness (63.99%)
CLD-MVS
CLD-MVS - accuracy (91.94%)
CLD-MVS - completeness (79.28%)
CMPMVS
CMPMVS - accuracy (88.82%)
CMPMVS - completeness (51.75%)
CNLPA
CNLPA - accuracy (92.43%)
CNLPA - completeness (83.16%)
CNVR-MVS
CNVR-MVS - accuracy (91.28%)
CNVR-MVS - completeness (88.46%)
COLMAP_ROB
COLMAP_ROB - accuracy (96.01%)
COLMAP_ROB - completeness (50.92%)
CostFormer
CostFormer - accuracy (83.87%)
CostFormer - completeness (72.69%)
CP-MVS
CP-MVS - accuracy (94.13%)
CP-MVS - completeness (84.19%)
CP-MVSNet
CP-MVSNet - accuracy (95.21%)
CP-MVSNet - completeness (37.40%)
CPTT-MVS
CPTT-MVS - accuracy (92.35%)
CPTT-MVS - completeness (81.72%)
CR-MVSNet
CR-MVSNet - accuracy (90.73%)
CR-MVSNet - completeness (51.09%)
CS-MVS
CS-MVS - accuracy (94.18%)
CS-MVS - completeness (71.30%)
CSCG
CSCG - accuracy (93.60%)
CSCG - completeness (86.17%)
CVMVSNet
CVMVSNet - accuracy (86.98%)
CVMVSNet - completeness (36.30%)
DCV-MVSNet
DCV-MVSNet - accuracy (87.01%)
DCV-MVSNet - completeness (70.81%)
DeepC-MVS
DeepC-MVS - accuracy (94.92%)
DeepC-MVS - completeness (79.59%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (93.72%)
DeepC-MVS_fast - completeness (83.19%)
DeepMVS_CX
DeepMVS_CX - accuracy (26.96%)
DeepMVS_CX - completeness (24.67%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (94.08%)
DeepPCF-MVS - completeness (76.77%)
DELS-MVS
DELS-MVS - accuracy (88.42%)
DELS-MVS - completeness (81.94%)
diffmvs
diffmvs - accuracy (85.09%)
diffmvs - completeness (75.95%)
DPE-MVS
DPE-MVS - accuracy (91.57%)
DPE-MVS - completeness (91.41%)
DPM-MVS
DPM-MVS - accuracy (89.67%)
DPM-MVS - completeness (81.84%)
dps
dps - accuracy (84.55%)
dps - completeness (71.98%)
DTE-MVSNet
DTE-MVSNet - accuracy (95.15%)
DTE-MVSNet - completeness (32.38%)
DU-MVS
DU-MVS - accuracy (93.78%)
DU-MVS - completeness (48.82%)
DVP-MVS
DVP-MVS - accuracy (89.57%)
DVP-MVS - completeness (94.00%)
E-PMN
E-PMN - accuracy (72.89%)
E-PMN - completeness (6.99%)
Effi-MVS+
Effi-MVS+ - accuracy (94.46%)
Effi-MVS+ - completeness (58.79%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (90.33%)
Effi-MVS+-dtu - completeness (53.06%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (94.88%)
EG-PatchMatch MVS - completeness (43.44%)
EIA-MVS
EIA-MVS - accuracy (93.72%)
EIA-MVS - completeness (71.03%)
EMVS
EMVS - accuracy (74.52%)
EMVS - completeness (6.53%)
EPMVS
EPMVS - accuracy (73.94%)
EPMVS - completeness (56.59%)
EPNet
EPNet - accuracy (91.85%)
EPNet - completeness (76.31%)
EPNet_dtu
EPNet_dtu - accuracy (91.29%)
EPNet_dtu - completeness (44.64%)
EPP-MVSNet
EPP-MVSNet - accuracy (85.76%)
EPP-MVSNet - completeness (64.46%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (89.78%)
ET-MVSNet_ETH3D - completeness (61.52%)
ETV-MVS
ETV-MVS - accuracy (92.13%)
ETV-MVS - completeness (73.20%)
EU-MVSNet
EU-MVSNet - accuracy (91.82%)
EU-MVSNet - completeness (27.91%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (92.71%)
Fast-Effi-MVS+ - completeness (60.26%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (87.65%)
Fast-Effi-MVS+-dtu - completeness (44.83%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (72.94%)
FC-MVSNet-test - completeness (26.74%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (81.71%)
FC-MVSNet-train - completeness (68.24%)
FMVSNet1
FMVSNet1 - accuracy (82.16%)
FMVSNet1 - completeness (65.08%)
FMVSNet2
FMVSNet2 - accuracy (79.89%)
FMVSNet2 - completeness (70.48%)
FMVSNet3
FMVSNet3 - accuracy (78.60%)
FMVSNet3 - completeness (72.63%)
FMVSNet5
FMVSNet5 - accuracy (70.64%)
FMVSNet5 - completeness (54.59%)
FPMVS
FPMVS - accuracy (88.45%)
FPMVS - completeness (37.94%)
GA-MVS
GA-MVS - accuracy (89.84%)
GA-MVS - completeness (42.68%)
GBi-Net
GBi-Net - accuracy (78.60%)
GBi-Net - completeness (72.63%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (5.36%)
GG-mvs-BLEND - completeness (0.21%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (87.15%)
gg-mvs-nofinetune - completeness (22.17%)
Gipuma
Gipuma - accuracy (97.90%)
Gipuma - completeness (20.08%)
gm-plane-assit
gm-plane-assit - accuracy (93.15%)
gm-plane-assit - completeness (26.19%)
HFP-MVS
HFP-MVS - accuracy (92.52%)
HFP-MVS - completeness (88.17%)
HPM-MVS++
HPM-MVS++ - accuracy (94.35%)
HPM-MVS++ - completeness (87.43%)
HQP-MVS
HQP-MVS - accuracy (91.62%)
HQP-MVS - completeness (64.21%)
HyFIR lowres test
HyFIR lowres test - accuracy (85.45%)
HyFIR lowres test - completeness (59.53%)
IB-MVS
IB-MVS - accuracy (84.85%)
IB-MVS - completeness (77.25%)
IS_MVSNet
IS_MVSNet - accuracy (82.71%)
IS_MVSNet - completeness (61.10%)
IterMVS
IterMVS - accuracy (88.55%)
IterMVS - completeness (46.82%)
IterMVS-LS
IterMVS-LS - accuracy (90.59%)
IterMVS-LS - completeness (61.74%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (91.82%)
IterMVS-SCA-FT - completeness (46.73%)
LGP-MVS_train
LGP-MVS_train - accuracy (92.67%)
LGP-MVS_train - completeness (61.64%)
LS3D
LS3D - accuracy (94.58%)
LS3D - completeness (59.22%)
LTVRE_ROB
LTVRE_ROB - accuracy (97.73%)
LTVRE_ROB - completeness (29.61%)
MAR-MVS
MAR-MVS - accuracy (93.32%)
MAR-MVS - completeness (68.59%)
MCST-MVS
MCST-MVS - accuracy (91.72%)
MCST-MVS - completeness (83.05%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (91.03%)
MDA-MVSNet-bldmvs - completeness (32.54%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (88.82%)
MDTV_nov1_ep13 - completeness (56.98%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (93.20%)
MDTV_nov1_ep13_2view - completeness (43.29%)
MIMVSNet
MIMVSNet - accuracy (69.69%)
MIMVSNet - completeness (51.27%)
MIMVSNet1
MIMVSNet1 - accuracy (84.55%)
MIMVSNet1 - completeness (27.83%)
MP-MVS
MP-MVS - accuracy (94.38%)
MP-MVS - completeness (82.54%)
MS-PatchMatch
MS-PatchMatch - accuracy (80.40%)
MS-PatchMatch - completeness (60.43%)
MSDG
MSDG - accuracy (91.83%)
MSDG - completeness (69.69%)
MSLP-MVS++
MSLP-MVS++ - accuracy (91.40%)
MSLP-MVS++ - completeness (89.24%)
MSP-MVS
MSP-MVS - accuracy (89.63%)
MSP-MVS - completeness (91.57%)
MTAPA
MTAPA - accuracy (94.88%)
MTAPA - completeness (91.14%)
MTMP
MTMP - accuracy (95.43%)
MTMP - completeness (90.95%)
MVE
MVE - accuracy (41.39%)
MVE - completeness (9.46%)
MVS-HIRNet
MVS-HIRNet - accuracy (86.66%)
MVS-HIRNet - completeness (49.29%)
MVSTER
MVSTER - accuracy (82.78%)
MVSTER - completeness (79.97%)
MVS_0304
MVS_0304 - accuracy (94.43%)
MVS_0304 - completeness (73.80%)
MVS_111021_LR
MVS_111021_LR - accuracy (92.99%)
MVS_111021_LR - completeness (77.47%)
MVS_Test
MVS_Test - accuracy (87.50%)
MVS_Test - completeness (70.55%)
NCCC
NCCC - accuracy (92.05%)
NCCC - completeness (84.94%)
new-patchmatchnet
new-patchmatchnet - accuracy (71.53%)
new-patchmatchnet - completeness (30.82%)
new_pmnet
new_pmnet - accuracy (49.73%)
new_pmnet - completeness (26.27%)
NR-MVSNet
NR-MVSNet - accuracy (91.79%)
NR-MVSNet - completeness (46.09%)
N_pmnet
N_pmnet - accuracy (53.38%)
N_pmnet - completeness (41.26%)
OMC-MVS
OMC-MVS - accuracy (94.15%)
OMC-MVS - completeness (77.37%)
OpenMVS
OpenMVS - accuracy (90.73%)
OpenMVS - completeness (75.20%)
OPM-MVS
OPM-MVS - accuracy (93.46%)
OPM-MVS - completeness (65.91%)
PatchMatch-RL
PatchMatch-RL - accuracy (88.25%)
PatchMatch-RL - completeness (71.98%)
PatchmatchNet
PatchmatchNet - accuracy (88.85%)
PatchmatchNet - completeness (52.74%)
Patchmtry
Patchmtry - accuracy (90.73%)
Patchmtry - completeness (51.09%)
PatchT
PatchT - accuracy (90.73%)
PatchT - completeness (51.09%)
PCF-MVS
PCF-MVS - accuracy (92.23%)
PCF-MVS - completeness (70.67%)
PEN-MVS
PEN-MVS - accuracy (94.93%)
PEN-MVS - completeness (35.29%)
PGM-MVS
PGM-MVS - accuracy (93.71%)
PGM-MVS - completeness (80.37%)
PHI-MVS
PHI-MVS - accuracy (96.00%)
PHI-MVS - completeness (69.72%)
PLC
PLC - accuracy (92.14%)
PLC - completeness (82.17%)
PM-MVS
PM-MVS - accuracy (92.41%)
PM-MVS - completeness (46.56%)
pm-mvs1
pm-mvs1 - accuracy (84.28%)
pm-mvs1 - completeness (51.17%)
PMMVS
PMMVS - accuracy (82.22%)
PMMVS - completeness (61.11%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (93.60%)
pmmvs-eth3d - completeness (50.94%)
PMMVS2
PMMVS2 - accuracy (25.11%)
PMMVS2 - completeness (4.31%)
pmmvs3
pmmvs3 - accuracy (84.34%)
pmmvs3 - completeness (30.19%)
pmmvs5
pmmvs5 - accuracy (87.86%)
pmmvs5 - completeness (47.22%)
pmmvs6
pmmvs6 - accuracy (85.61%)
pmmvs6 - completeness (48.48%)
pmnet_mix02
pmnet_mix02 - accuracy (80.32%)
pmnet_mix02 - completeness (41.69%)
PMVS
PMVS - accuracy (95.33%)
PMVS - completeness (37.92%)
PS-CasMVS
PS-CasMVS - accuracy (95.32%)
PS-CasMVS - completeness (36.48%)
PVSNet_Blended
PVSNet_Blended - accuracy (90.30%)
PVSNet_Blended - completeness (82.78%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (90.30%)
PVSNet_BlendedMVS - completeness (82.78%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (93.17%)
PVSNet_Blended_VisFu - completeness (73.64%)
QAPM
QAPM - accuracy (91.21%)
QAPM - completeness (71.28%)
RE-MVS-def
RE-MVS-def - accuracy (97.21%)
RE-MVS-def - completeness (39.41%)
RPMNet
RPMNet - accuracy (87.10%)
RPMNet - completeness (46.10%)
RPSCF
RPSCF - accuracy (91.34%)
RPSCF - completeness (68.24%)
SCA
SCA - accuracy (89.68%)
SCA - completeness (52.72%)
SD-MVS
SD-MVS - accuracy (92.71%)
SD-MVS - completeness (90.04%)
SED-MVS
SED-MVS - accuracy (89.61%)
SED-MVS - completeness (94.19%)
SF-MVS
SF-MVS - accuracy (91.93%)
SF-MVS - completeness (90.26%)
SMA-MVS
SMA-MVS - accuracy (93.79%)
SMA-MVS - completeness (87.15%)
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 (91.91%)
SteuartSystems-ACMMP - completeness (83.20%)
TAMVS
TAMVS - accuracy (65.81%)
TAMVS - completeness (56.91%)
TAPA-MVS
TAPA-MVS - accuracy (93.88%)
TAPA-MVS - completeness (69.78%)
TDRefinement
TDRefinement - accuracy (96.44%)
TDRefinement - completeness (48.35%)
test-mter
test-mter - accuracy (78.87%)
test-mter - completeness (51.29%)
test1
test1 - accuracy (78.60%)
test1 - completeness (72.63%)
test123
test123 - accuracy (2.27%)
test123 - completeness (0.02%)
testgi
testgi - accuracy (69.54%)
testgi - completeness (34.56%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (78.59%)
TESTMET0.1,1 - completeness (52.14%)
testmvs
testmvs - accuracy (1.63%)
testmvs - completeness (0.05%)
test_part1
test_part1 - accuracy (93.11%)
test_part1 - completeness (74.88%)
thisisatest0515
thisisatest0515 - accuracy (92.45%)
thisisatest0515 - completeness (52.94%)
thisisatest0530
thisisatest0530 - accuracy (89.17%)
thisisatest0530 - completeness (63.85%)
TinyColmap
TinyColmap - accuracy (97.48%)
TinyColmap - completeness (45.52%)
tmp_tt
tmp_tt - accuracy (51.96%)
tmp_tt - completeness (50.83%)
tpm
tpm - accuracy (92.05%)
tpm - completeness (48.90%)
tpm cat1
tpm cat1 - accuracy (86.10%)
tpm cat1 - completeness (72.64%)
tpmrst
tpmrst - accuracy (83.48%)
tpmrst - completeness (56.27%)
train_agg
train_agg - accuracy (90.52%)
train_agg - completeness (77.75%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (91.92%)
TranMVSNet+NR-MVSNet - completeness (45.29%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (85.12%)
TransMVSNet (Re) - completeness (45.20%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (90.99%)
TSAR-MVS + ACMM - completeness (76.32%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (91.64%)
TSAR-MVS + COLMAP - completeness (61.66%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (88.92%)
TSAR-MVS + GP. - completeness (83.77%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (92.71%)
TSAR-MVS + MP. - completeness (89.20%)
tttt0517
tttt0517 - accuracy (89.39%)
tttt0517 - completeness (63.59%)
UA-Net
UA-Net - accuracy (92.54%)
UA-Net - completeness (60.52%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (85.76%)
UGNet - completeness (71.35%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (92.13%)
UniMVSNet (Re) - completeness (50.24%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (90.42%)
UniMVSNet_ETH3D - completeness (55.71%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (93.78%)
UniMVSNet_NR-MVSNet - completeness (48.82%)
USDC
USDC - accuracy (97.99%)
USDC - completeness (46.94%)
Vis-MVSNet
Vis-MVSNet - accuracy (89.20%)
Vis-MVSNet - completeness (55.25%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (75.01%)
Vis-MVSNet (Re-imp) - completeness (53.47%)
WR-MVS_H
WR-MVS_H - accuracy (93.71%)
WR-MVS_H - completeness (36.47%)
X-MVS
X-MVS - accuracy (93.28%)
X-MVS - completeness (76.32%)
X-MVStestdata
X-MVStestdata - accuracy (93.28%)
X-MVStestdata - completeness (76.32%)
XVS
XVS - accuracy (93.28%)
XVS - completeness (76.32%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (91.93%)
xxxxxxxxxxxxxcwj - completeness (90.26%)
zzz-MVS
zzz-MVS - accuracy (94.81%)
zzz-MVS - completeness (90.76%)
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
:
-56.43 to 3775.15
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
:
2654.6
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