+
−
⇧
i
D
T
electro (low-res many-view) - Tolerance 2cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (rig eval)
3Dnovator
3Dnovator - accuracy (76.83%)
3Dnovator - completeness (52.03%)
3Dnovator+
3Dnovator+ - accuracy (78.07%)
3Dnovator+ - completeness (52.65%)
A-TVSNet + Gipuma
A-TVSNet + Gipuma - accuracy (38.96%)
A-TVSNet + Gipuma - completeness (50.14%)
ACMH
ACMH - accuracy (50.36%)
ACMH - completeness (55.34%)
ACMH+
ACMH+ - accuracy (54.48%)
ACMH+ - completeness (60.58%)
ACMM
ACMM - accuracy (64.20%)
ACMM - completeness (59.48%)
ACMP
ACMP - accuracy (58.13%)
ACMP - completeness (64.39%)
BP-MVSNet
BP-MVSNet - accuracy (40.86%)
BP-MVSNet - completeness (63.61%)
CasMVSNet(base)
CasMVSNet(base) - accuracy (63.36%)
CasMVSNet(base) - completeness (45.69%)
CasMVSNet(SR_A)
CasMVSNet(SR_A) - accuracy (59.92%)
CasMVSNet(SR_A) - completeness (17.56%)
CasMVSNet(SR_B)
CasMVSNet(SR_B) - accuracy (63.53%)
CasMVSNet(SR_B) - completeness (48.96%)
CIDER
CIDER - accuracy (44.18%)
CIDER - completeness (48.33%)
CMPMVS
CMPMVS - accuracy (0.00%)
CMPMVS - completeness (0.00%)
COLMAP(base)
COLMAP(base) - accuracy (57.58%)
COLMAP(base) - completeness (50.72%)
COLMAP(SR)
COLMAP(SR) - accuracy (51.72%)
COLMAP(SR) - completeness (59.27%)
COLMAP_ROB
COLMAP_ROB - accuracy (75.96%)
COLMAP_ROB - completeness (39.89%)
DeepC-MVS
DeepC-MVS - accuracy (70.11%)
DeepC-MVS - completeness (61.68%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (72.92%)
DeepC-MVS_fast - completeness (60.00%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (70.31%)
DeepPCF-MVS - completeness (61.30%)
dnet
dnet - accuracy (0.00%)
dnet - completeness (0.00%)
DPSNet
DPSNet - accuracy (8.06%)
DPSNet - completeness (4.67%)
example
example - accuracy (5.26%)
example - completeness (5.16%)
GSE
GSE - accuracy (51.37%)
GSE - completeness (47.91%)
hgnet
hgnet - accuracy (8.06%)
hgnet - completeness (4.67%)
IB-MVS
IB-MVS - accuracy (60.44%)
IB-MVS - completeness (61.99%)
LPCS
LPCS - accuracy (57.64%)
LPCS - completeness (45.83%)
LTVRE_ROB
LTVRE_ROB - accuracy (76.95%)
LTVRE_ROB - completeness (41.51%)
MVE
MVE - accuracy (11.70%)
MVE - completeness (17.82%)
OpenMVS
OpenMVS - accuracy (71.84%)
OpenMVS - completeness (49.81%)
PCF-MVS
PCF-MVS - accuracy (56.38%)
PCF-MVS - completeness (56.34%)
PLC
PLC - accuracy (53.45%)
PLC - completeness (51.13%)
PMVS
PMVS - accuracy (36.39%)
PMVS - completeness (6.74%)
TAPA-MVS
TAPA-MVS - accuracy (72.19%)
TAPA-MVS - completeness (46.81%)
TAPA-MVS(SR)
TAPA-MVS(SR) - accuracy (57.98%)
TAPA-MVS(SR) - completeness (58.23%)
unsupervisedMVS_cas
unsupervisedMVS_cas - accuracy (22.21%)
unsupervisedMVS_cas - completeness (34.84%)
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
:
-33.95 to 183.84
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
:
150.9
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