+
−
⇧
i
D
T
terrace (high-res multi-view) - Tolerance 1cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (83.44%)
3Dnovator - completeness (79.12%)
3Dnovator+
3Dnovator+ - accuracy (91.06%)
3Dnovator+ - completeness (73.08%)
ACMH
ACMH - accuracy (86.00%)
ACMH - completeness (68.91%)
ACMH+
ACMH+ - accuracy (89.26%)
ACMH+ - completeness (68.62%)
ACMM
ACMM - accuracy (91.42%)
ACMM - completeness (74.14%)
ACMMP
ACMMP - accuracy (92.30%)
ACMMP - completeness (74.93%)
ACMMPR
ACMMPR - accuracy (91.80%)
ACMMPR - completeness (75.21%)
ACMMP_NAP
ACMMP_NAP - accuracy (89.73%)
ACMMP_NAP - completeness (77.10%)
ACMP
ACMP - accuracy (91.48%)
ACMP - completeness (75.75%)
AdaColmap
AdaColmap - accuracy (85.95%)
AdaColmap - completeness (74.28%)
ADS-MVSNet
ADS-MVSNet - accuracy (35.64%)
ADS-MVSNet - completeness (68.15%)
ambc
ambc - accuracy (75.41%)
ambc - completeness (47.91%)
Anonymous20231206
Anonymous20231206 - accuracy (51.74%)
Anonymous20231206 - completeness (67.85%)
Anonymous202405211
Anonymous202405211 - accuracy (75.45%)
Anonymous202405211 - completeness (75.37%)
anonymousdsp
anonymousdsp - accuracy (91.74%)
anonymousdsp - completeness (62.32%)
APD-MVS
APD-MVS - accuracy (88.01%)
APD-MVS - completeness (76.02%)
APDe-MVS
APDe-MVS - accuracy (88.98%)
APDe-MVS - completeness (78.47%)
baseline1
baseline1 - accuracy (66.07%)
baseline1 - completeness (77.20%)
baseline2
baseline2 - accuracy (71.56%)
baseline2 - completeness (78.56%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (70.34%)
Baseline_NR-MVSNet - completeness (75.53%)
CANet
CANet - accuracy (82.25%)
CANet - completeness (78.94%)
CANet_DTU
CANet_DTU - accuracy (73.69%)
CANet_DTU - completeness (74.57%)
canonicalmvs
canonicalmvs - accuracy (78.87%)
canonicalmvs - completeness (78.16%)
casdiffmvs
casdiffmvs - accuracy (77.70%)
casdiffmvs - completeness (79.41%)
CDPH-MVS
CDPH-MVS - accuracy (87.79%)
CDPH-MVS - completeness (78.02%)
CDS-MVSNet
CDS-MVSNet - accuracy (69.22%)
CDS-MVSNet - completeness (67.48%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (57.01%)
CHOSEN 1792x2688 - completeness (81.60%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (43.28%)
CHOSEN 280x420 - completeness (55.28%)
CLD-MVS
CLD-MVS - accuracy (73.09%)
CLD-MVS - completeness (79.40%)
CMPMVS
CMPMVS - accuracy (61.08%)
CMPMVS - completeness (59.12%)
CNLPA
CNLPA - accuracy (84.02%)
CNLPA - completeness (64.06%)
CNVR-MVS
CNVR-MVS - accuracy (86.10%)
CNVR-MVS - completeness (80.32%)
COLMAP_ROB
COLMAP_ROB - accuracy (92.17%)
COLMAP_ROB - completeness (59.22%)
CostFormer
CostFormer - accuracy (59.68%)
CostFormer - completeness (79.74%)
CP-MVS
CP-MVS - accuracy (91.40%)
CP-MVS - completeness (73.78%)
CP-MVSNet
CP-MVSNet - accuracy (82.56%)
CP-MVSNet - completeness (63.54%)
CPTT-MVS
CPTT-MVS - accuracy (90.87%)
CPTT-MVS - completeness (70.18%)
CR-MVSNet
CR-MVSNet - accuracy (69.38%)
CR-MVSNet - completeness (61.99%)
CS-MVS
CS-MVS - accuracy (84.46%)
CS-MVS - completeness (78.64%)
CSCG
CSCG - accuracy (89.83%)
CSCG - completeness (79.56%)
CVMVSNet
CVMVSNet - accuracy (71.51%)
CVMVSNet - completeness (57.59%)
DCV-MVSNet
DCV-MVSNet - accuracy (77.01%)
DCV-MVSNet - completeness (75.45%)
DeepC-MVS
DeepC-MVS - accuracy (91.46%)
DeepC-MVS - completeness (76.85%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (88.46%)
DeepC-MVS_fast - completeness (76.70%)
DeepMVS_CX
DeepMVS_CX - accuracy (11.34%)
DeepMVS_CX - completeness (6.30%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (87.26%)
DeepPCF-MVS - completeness (74.13%)
DELS-MVS
DELS-MVS - accuracy (79.90%)
DELS-MVS - completeness (79.51%)
diffmvs
diffmvs - accuracy (70.78%)
diffmvs - completeness (75.89%)
DPE-MVS
DPE-MVS - accuracy (87.87%)
DPE-MVS - completeness (77.33%)
DPM-MVS
DPM-MVS - accuracy (83.79%)
DPM-MVS - completeness (81.45%)
dps
dps - accuracy (55.14%)
dps - completeness (73.33%)
DTE-MVSNet
DTE-MVSNet - accuracy (83.39%)
DTE-MVSNet - completeness (63.86%)
DU-MVS
DU-MVS - accuracy (82.72%)
DU-MVS - completeness (70.35%)
DVP-MVS
DVP-MVS - accuracy (85.66%)
DVP-MVS - completeness (79.21%)
E-PMN
E-PMN - accuracy (37.04%)
E-PMN - completeness (16.03%)
Effi-MVS+
Effi-MVS+ - accuracy (83.84%)
Effi-MVS+ - completeness (75.91%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (86.44%)
Effi-MVS+-dtu - completeness (69.99%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (80.51%)
EG-PatchMatch MVS - completeness (75.40%)
EIA-MVS
EIA-MVS - accuracy (81.59%)
EIA-MVS - completeness (78.06%)
EMVS
EMVS - accuracy (36.38%)
EMVS - completeness (14.44%)
EPMVS
EPMVS - accuracy (39.59%)
EPMVS - completeness (77.86%)
EPNet
EPNet - accuracy (76.81%)
EPNet - completeness (75.75%)
EPNet_dtu
EPNet_dtu - accuracy (65.39%)
EPNet_dtu - completeness (70.35%)
EPP-MVSNet
EPP-MVSNet - accuracy (89.02%)
EPP-MVSNet - completeness (71.41%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (80.05%)
ET-MVSNet_ETH3D - completeness (74.79%)
ETV-MVS
ETV-MVS - accuracy (83.68%)
ETV-MVS - completeness (77.34%)
EU-MVSNet
EU-MVSNet - accuracy (71.26%)
EU-MVSNet - completeness (54.08%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (81.74%)
Fast-Effi-MVS+ - completeness (75.90%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (76.60%)
Fast-Effi-MVS+-dtu - completeness (74.17%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (70.68%)
FC-MVSNet-test - completeness (37.10%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (78.43%)
FC-MVSNet-train - completeness (73.56%)
FMVSNet1
FMVSNet1 - accuracy (72.66%)
FMVSNet1 - completeness (74.75%)
FMVSNet2
FMVSNet2 - accuracy (70.38%)
FMVSNet2 - completeness (77.32%)
FMVSNet3
FMVSNet3 - accuracy (68.88%)
FMVSNet3 - completeness (78.35%)
FMVSNet5
FMVSNet5 - accuracy (45.16%)
FMVSNet5 - completeness (70.10%)
FPMVS
FPMVS - accuracy (77.86%)
FPMVS - completeness (42.56%)
GA-MVS
GA-MVS - accuracy (73.19%)
GA-MVS - completeness (75.83%)
GBi-Net
GBi-Net - accuracy (70.38%)
GBi-Net - completeness (77.32%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (41.70%)
GG-mvs-BLEND - completeness (75.13%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (63.60%)
gg-mvs-nofinetune - completeness (80.84%)
Gipuma
Gipuma - accuracy (78.98%)
Gipuma - completeness (25.92%)
gm-plane-assit
gm-plane-assit - accuracy (63.02%)
gm-plane-assit - completeness (82.47%)
HFP-MVS
HFP-MVS - accuracy (91.49%)
HFP-MVS - completeness (75.98%)
HPM-MVS++
HPM-MVS++ - accuracy (87.85%)
HPM-MVS++ - completeness (76.55%)
HQP-MVS
HQP-MVS - accuracy (86.48%)
HQP-MVS - completeness (77.57%)
HyFIR lowres test
HyFIR lowres test - accuracy (71.27%)
HyFIR lowres test - completeness (78.26%)
IB-MVS
IB-MVS - accuracy (75.97%)
IB-MVS - completeness (79.29%)
IS_MVSNet
IS_MVSNet - accuracy (86.94%)
IS_MVSNet - completeness (71.33%)
IterMVS
IterMVS - accuracy (68.04%)
IterMVS - completeness (73.23%)
IterMVS-LS
IterMVS-LS - accuracy (74.90%)
IterMVS-LS - completeness (70.92%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (67.70%)
IterMVS-SCA-FT - completeness (41.70%)
LGP-MVS_train
LGP-MVS_train - accuracy (91.71%)
LGP-MVS_train - completeness (75.51%)
LS3D
LS3D - accuracy (90.09%)
LS3D - completeness (64.29%)
LTVRE_ROB
LTVRE_ROB - accuracy (88.42%)
LTVRE_ROB - completeness (48.41%)
MAR-MVS
MAR-MVS - accuracy (80.87%)
MAR-MVS - completeness (78.59%)
MCST-MVS
MCST-MVS - accuracy (85.42%)
MCST-MVS - completeness (82.67%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (64.46%)
MDA-MVSNet-bldmvs - completeness (63.56%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (58.04%)
MDTV_nov1_ep13 - completeness (74.74%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (58.04%)
MDTV_nov1_ep13_2view - completeness (74.74%)
MIMVSNet
MIMVSNet - accuracy (47.11%)
MIMVSNet - completeness (74.20%)
MIMVSNet1
MIMVSNet1 - accuracy (51.40%)
MIMVSNet1 - completeness (55.97%)
MP-MVS
MP-MVS - accuracy (90.92%)
MP-MVS - completeness (74.98%)
MS-PatchMatch
MS-PatchMatch - accuracy (66.33%)
MS-PatchMatch - completeness (82.13%)
MSDG
MSDG - accuracy (81.71%)
MSDG - completeness (73.49%)
MSLP-MVS++
MSLP-MVS++ - accuracy (80.39%)
MSLP-MVS++ - completeness (79.03%)
MSP-MVS
MSP-MVS - accuracy (83.99%)
MSP-MVS - completeness (76.99%)
MVE
MVE - accuracy (24.76%)
MVE - completeness (9.44%)
MVS-HIRNet
MVS-HIRNet - accuracy (56.99%)
MVS-HIRNet - completeness (73.16%)
MVSTER
MVSTER - accuracy (74.73%)
MVSTER - completeness (76.41%)
MVS_0304
MVS_0304 - accuracy (85.10%)
MVS_0304 - completeness (78.41%)
MVS_111021_LR
MVS_111021_LR - accuracy (82.00%)
MVS_111021_LR - completeness (67.92%)
MVS_Test
MVS_Test - accuracy (74.04%)
MVS_Test - completeness (79.72%)
NCCC
NCCC - accuracy (86.62%)
NCCC - completeness (79.69%)
new-patchmatchnet
new-patchmatchnet - accuracy (38.51%)
new-patchmatchnet - completeness (51.94%)
new_pmnet
new_pmnet - accuracy (34.17%)
new_pmnet - completeness (35.38%)
NR-MVSNet
NR-MVSNet - accuracy (82.83%)
NR-MVSNet - completeness (73.10%)
N_pmnet
N_pmnet - accuracy (28.71%)
N_pmnet - completeness (57.13%)
OMC-MVS
OMC-MVS - accuracy (89.92%)
OMC-MVS - completeness (65.91%)
OpenMVS
OpenMVS - accuracy (77.73%)
OpenMVS - completeness (77.73%)
OPM-MVS
OPM-MVS - accuracy (88.86%)
OPM-MVS - completeness (76.45%)
PatchMatch-RL
PatchMatch-RL - accuracy (75.27%)
PatchMatch-RL - completeness (58.38%)
PatchmatchNet
PatchmatchNet - accuracy (51.19%)
PatchmatchNet - completeness (75.69%)
PatchT
PatchT - accuracy (55.62%)
PatchT - completeness (73.19%)
PCF-MVS
PCF-MVS - accuracy (86.15%)
PCF-MVS - completeness (72.22%)
PEN-MVS
PEN-MVS - accuracy (83.06%)
PEN-MVS - completeness (66.29%)
PGM-MVS
PGM-MVS - accuracy (91.57%)
PGM-MVS - completeness (75.18%)
PHI-MVS
PHI-MVS - accuracy (83.60%)
PHI-MVS - completeness (73.72%)
PLC
PLC - accuracy (87.54%)
PLC - completeness (64.84%)
PM-MVS
PM-MVS - accuracy (73.19%)
PM-MVS - completeness (54.07%)
pm-mvs1
pm-mvs1 - accuracy (71.28%)
pm-mvs1 - completeness (70.70%)
PMMVS
PMMVS - accuracy (68.43%)
PMMVS - completeness (67.67%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (74.00%)
pmmvs-eth3d - completeness (69.68%)
PMMVS2
PMMVS2 - accuracy (18.94%)
PMMVS2 - completeness (19.85%)
pmmvs3
pmmvs3 - accuracy (58.32%)
pmmvs3 - completeness (58.61%)
pmmvs5
pmmvs5 - accuracy (64.95%)
pmmvs5 - completeness (73.40%)
pmmvs6
pmmvs6 - accuracy (72.21%)
pmmvs6 - completeness (67.60%)
pmnet_mix02
pmnet_mix02 - accuracy (39.62%)
pmnet_mix02 - completeness (68.36%)
PMVS
PMVS - accuracy (88.13%)
PMVS - completeness (39.85%)
PS-CasMVS
PS-CasMVS - accuracy (82.60%)
PS-CasMVS - completeness (63.39%)
PVSNet_Blended
PVSNet_Blended - accuracy (76.64%)
PVSNet_Blended - completeness (76.24%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (76.64%)
PVSNet_BlendedMVS - completeness (76.24%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (83.90%)
PVSNet_Blended_VisFu - completeness (75.18%)
QAPM
QAPM - accuracy (76.71%)
QAPM - completeness (78.56%)
RPMNet
RPMNet - accuracy (69.44%)
RPMNet - completeness (61.75%)
RPSCF
RPSCF - accuracy (86.38%)
RPSCF - completeness (36.99%)
SCA
SCA - accuracy (55.82%)
SCA - completeness (71.38%)
SD-MVS
SD-MVS - accuracy (92.85%)
SD-MVS - completeness (74.13%)
SED-MVS
SED-MVS - accuracy (86.40%)
SED-MVS - completeness (79.22%)
SF-MVS
SF-MVS - accuracy (87.44%)
SF-MVS - completeness (79.63%)
SMA-MVS
SMA-MVS - accuracy (90.11%)
SMA-MVS - completeness (78.08%)
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 (89.36%)
SteuartSystems-ACMMP - completeness (79.14%)
TAMVS
TAMVS - accuracy (52.79%)
TAMVS - completeness (66.13%)
TAPA-MVS
TAPA-MVS - accuracy (87.17%)
TAPA-MVS - completeness (63.33%)
TDRefinement
TDRefinement - accuracy (93.47%)
TDRefinement - completeness (56.65%)
test-mter
test-mter - accuracy (60.97%)
test-mter - completeness (74.20%)
test1
test1 - accuracy (70.38%)
test1 - completeness (77.32%)
test123
test123 - accuracy (0.26%)
test123 - completeness (0.00%)
testgi
testgi - accuracy (49.93%)
testgi - completeness (60.05%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (58.60%)
TESTMET0.1,1 - completeness (78.43%)
testmvs
testmvs - accuracy (0.15%)
testmvs - completeness (0.00%)
test_part1
test_part1 - accuracy (86.80%)
test_part1 - completeness (75.61%)
thisisatest0515
thisisatest0515 - accuracy (84.69%)
thisisatest0515 - completeness (64.70%)
thisisatest0530
thisisatest0530 - accuracy (82.60%)
thisisatest0530 - completeness (69.34%)
TinyColmap
TinyColmap - accuracy (80.85%)
TinyColmap - completeness (57.71%)
tmp_tt
tmp_tt - accuracy (12.70%)
tmp_tt - completeness (9.23%)
tpm
tpm - accuracy (43.88%)
tpm - completeness (73.31%)
tpm cat1
tpm cat1 - accuracy (54.25%)
tpm cat1 - completeness (74.11%)
tpmrst
tpmrst - accuracy (43.64%)
tpmrst - completeness (77.37%)
train_agg
train_agg - accuracy (86.71%)
train_agg - completeness (77.25%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (82.96%)
TranMVSNet+NR-MVSNet - completeness (72.81%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (71.50%)
TransMVSNet (Re) - completeness (75.10%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (86.18%)
TSAR-MVS + ACMM - completeness (66.94%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (81.95%)
TSAR-MVS + COLMAP - completeness (64.83%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (83.54%)
TSAR-MVS + GP. - completeness (77.35%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (88.51%)
TSAR-MVS + MP. - completeness (75.97%)
tttt0517
tttt0517 - accuracy (82.99%)
tttt0517 - completeness (68.67%)
UA-Net
UA-Net - accuracy (92.32%)
UA-Net - completeness (61.79%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (77.95%)
UGNet - completeness (67.23%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (84.40%)
UniMVSNet (Re) - completeness (70.98%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (75.64%)
UniMVSNet_ETH3D - completeness (70.05%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (84.28%)
UniMVSNet_NR-MVSNet - completeness (73.52%)
USDC
USDC - accuracy (80.39%)
USDC - completeness (62.61%)
Vis-MVSNet
Vis-MVSNet - accuracy (79.08%)
Vis-MVSNet - completeness (67.49%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (75.69%)
Vis-MVSNet (Re-imp) - completeness (63.00%)
WR-MVS_H
WR-MVS_H - accuracy (83.63%)
WR-MVS_H - completeness (65.24%)
X-MVS
X-MVS - accuracy (91.54%)
X-MVS - completeness (74.61%)
X-MVStestdata
X-MVStestdata - accuracy (91.52%)
X-MVStestdata - completeness (74.68%)
XVS
XVS - accuracy (91.52%)
XVS - completeness (74.68%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (87.44%)
xxxxxxxxxxxxxcwj - completeness (79.63%)
zzz-MVS
zzz-MVS - accuracy (90.48%)
zzz-MVS - completeness (74.96%)
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
:
-5.18 to 68.68
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
:
51.2
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