+
−
⇧
i
D
T
kicker (high-res multi-view) - Tolerance 1cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (74.44%)
3Dnovator - completeness (61.52%)
3Dnovator+
3Dnovator+ - accuracy (81.33%)
3Dnovator+ - completeness (62.77%)
ACMH
ACMH - accuracy (89.24%)
ACMH - completeness (31.06%)
ACMH+
ACMH+ - accuracy (87.35%)
ACMH+ - completeness (37.49%)
ACMM
ACMM - accuracy (84.43%)
ACMM - completeness (53.69%)
ACMMP
ACMMP - accuracy (82.20%)
ACMMP - completeness (66.50%)
ACMMPR
ACMMPR - accuracy (84.35%)
ACMMPR - completeness (71.97%)
ACMMP_NAP
ACMMP_NAP - accuracy (83.55%)
ACMMP_NAP - completeness (79.32%)
ACMP
ACMP - accuracy (81.35%)
ACMP - completeness (58.56%)
AdaColmap
AdaColmap - accuracy (76.20%)
AdaColmap - completeness (65.14%)
ADS-MVSNet
ADS-MVSNet - accuracy (58.01%)
ADS-MVSNet - completeness (35.89%)
ambc
ambc - accuracy (80.32%)
ambc - completeness (25.20%)
Anonymous20231206
Anonymous20231206 - accuracy (62.02%)
Anonymous20231206 - completeness (28.16%)
Anonymous202405211
Anonymous202405211 - accuracy (71.25%)
Anonymous202405211 - completeness (39.26%)
anonymousdsp
anonymousdsp - accuracy (74.11%)
anonymousdsp - completeness (24.22%)
APD-MVS
APD-MVS - accuracy (77.54%)
APD-MVS - completeness (83.59%)
APDe-MVS
APDe-MVS - accuracy (85.83%)
APDe-MVS - completeness (85.31%)
baseline1
baseline1 - accuracy (56.81%)
baseline1 - completeness (43.39%)
baseline2
baseline2 - accuracy (46.69%)
baseline2 - completeness (48.10%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (71.25%)
Baseline_NR-MVSNet - completeness (37.71%)
CANet
CANet - accuracy (59.81%)
CANet - completeness (68.49%)
CANet_DTU
CANet_DTU - accuracy (50.49%)
CANet_DTU - completeness (56.49%)
canonicalmvs
canonicalmvs - accuracy (76.82%)
canonicalmvs - completeness (71.54%)
casdiffmvs
casdiffmvs - accuracy (69.49%)
casdiffmvs - completeness (55.89%)
CDPH-MVS
CDPH-MVS - accuracy (73.00%)
CDPH-MVS - completeness (67.02%)
CDS-MVSNet
CDS-MVSNet - accuracy (57.41%)
CDS-MVSNet - completeness (33.77%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (45.46%)
CHOSEN 1792x2688 - completeness (47.90%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (40.94%)
CHOSEN 280x420 - completeness (34.66%)
CLD-MVS
CLD-MVS - accuracy (74.23%)
CLD-MVS - completeness (69.64%)
CMPMVS
CMPMVS - accuracy (58.06%)
CMPMVS - completeness (34.20%)
CNLPA
CNLPA - accuracy (81.82%)
CNLPA - completeness (74.55%)
CNVR-MVS
CNVR-MVS - accuracy (79.41%)
CNVR-MVS - completeness (80.12%)
COLMAP_ROB
COLMAP_ROB - accuracy (89.37%)
COLMAP_ROB - completeness (37.81%)
CostFormer
CostFormer - accuracy (52.85%)
CostFormer - completeness (54.04%)
CP-MVS
CP-MVS - accuracy (83.13%)
CP-MVS - completeness (69.40%)
CP-MVSNet
CP-MVSNet - accuracy (82.09%)
CP-MVSNet - completeness (27.88%)
CPTT-MVS
CPTT-MVS - accuracy (82.55%)
CPTT-MVS - completeness (64.81%)
CR-MVSNet
CR-MVSNet - accuracy (46.90%)
CR-MVSNet - completeness (42.17%)
CS-MVS
CS-MVS - accuracy (54.33%)
CS-MVS - completeness (53.40%)
CSCG
CSCG - accuracy (83.47%)
CSCG - completeness (75.61%)
CVMVSNet
CVMVSNet - accuracy (55.07%)
CVMVSNet - completeness (31.45%)
DCV-MVSNet
DCV-MVSNet - accuracy (74.32%)
DCV-MVSNet - completeness (41.01%)
DeepC-MVS
DeepC-MVS - accuracy (83.10%)
DeepC-MVS - completeness (73.91%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (77.79%)
DeepC-MVS_fast - completeness (72.26%)
DeepMVS_CX
DeepMVS_CX - accuracy (16.70%)
DeepMVS_CX - completeness (9.04%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (82.41%)
DeepPCF-MVS - completeness (87.46%)
DELS-MVS
DELS-MVS - accuracy (62.29%)
DELS-MVS - completeness (53.38%)
diffmvs
diffmvs - accuracy (64.18%)
diffmvs - completeness (55.45%)
DPE-MVS
DPE-MVS - accuracy (81.66%)
DPE-MVS - completeness (86.55%)
DPM-MVS
DPM-MVS - accuracy (71.91%)
DPM-MVS - completeness (80.49%)
dps
dps - accuracy (44.91%)
dps - completeness (42.49%)
DTE-MVSNet
DTE-MVSNet - accuracy (85.03%)
DTE-MVSNet - completeness (27.03%)
DU-MVS
DU-MVS - accuracy (69.95%)
DU-MVS - completeness (37.26%)
DVP-MVS
DVP-MVS - accuracy (86.47%)
DVP-MVS - completeness (88.62%)
E-PMN
E-PMN - accuracy (57.76%)
E-PMN - completeness (8.37%)
Effi-MVS+
Effi-MVS+ - accuracy (63.33%)
Effi-MVS+ - completeness (47.18%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (56.98%)
Effi-MVS+-dtu - completeness (43.84%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (72.02%)
EG-PatchMatch MVS - completeness (26.22%)
EIA-MVS
EIA-MVS - accuracy (48.31%)
EIA-MVS - completeness (51.78%)
EMVS
EMVS - accuracy (57.88%)
EMVS - completeness (8.65%)
EPMVS
EPMVS - accuracy (49.89%)
EPMVS - completeness (46.46%)
EPNet
EPNet - accuracy (56.78%)
EPNet - completeness (69.93%)
EPNet_dtu
EPNet_dtu - accuracy (50.27%)
EPNet_dtu - completeness (56.13%)
EPP-MVSNet
EPP-MVSNet - accuracy (73.60%)
EPP-MVSNet - completeness (37.53%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (51.40%)
ET-MVSNet_ETH3D - completeness (46.52%)
ETV-MVS
ETV-MVS - accuracy (49.27%)
ETV-MVS - completeness (58.27%)
EU-MVSNet
EU-MVSNet - accuracy (62.08%)
EU-MVSNet - completeness (22.94%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (60.89%)
Fast-Effi-MVS+ - completeness (46.92%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (51.46%)
Fast-Effi-MVS+-dtu - completeness (41.27%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (71.42%)
FC-MVSNet-test - completeness (31.37%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (70.99%)
FC-MVSNet-train - completeness (42.36%)
FMVSNet1
FMVSNet1 - accuracy (70.24%)
FMVSNet1 - completeness (34.10%)
FMVSNet2
FMVSNet2 - accuracy (58.21%)
FMVSNet2 - completeness (43.13%)
FMVSNet3
FMVSNet3 - accuracy (49.06%)
FMVSNet3 - completeness (49.30%)
FMVSNet5
FMVSNet5 - accuracy (39.45%)
FMVSNet5 - completeness (42.17%)
FPMVS
FPMVS - accuracy (76.73%)
FPMVS - completeness (28.09%)
GA-MVS
GA-MVS - accuracy (57.39%)
GA-MVS - completeness (34.31%)
GBi-Net
GBi-Net - accuracy (49.06%)
GBi-Net - completeness (49.30%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (44.04%)
GG-mvs-BLEND - completeness (50.70%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (74.77%)
gg-mvs-nofinetune - completeness (20.05%)
Gipuma
Gipuma - accuracy (83.79%)
Gipuma - completeness (17.94%)
gm-plane-assit
gm-plane-assit - accuracy (73.71%)
gm-plane-assit - completeness (14.44%)
HFP-MVS
HFP-MVS - accuracy (84.04%)
HFP-MVS - completeness (73.50%)
HPM-MVS++
HPM-MVS++ - accuracy (80.85%)
HPM-MVS++ - completeness (83.11%)
HQP-MVS
HQP-MVS - accuracy (76.12%)
HQP-MVS - completeness (69.92%)
HyFIR lowres test
HyFIR lowres test - accuracy (50.25%)
HyFIR lowres test - completeness (41.84%)
IB-MVS
IB-MVS - accuracy (49.37%)
IB-MVS - completeness (43.22%)
IS_MVSNet
IS_MVSNet - accuracy (70.11%)
IS_MVSNet - completeness (39.82%)
IterMVS
IterMVS - accuracy (58.17%)
IterMVS - completeness (36.07%)
IterMVS-LS
IterMVS-LS - accuracy (65.65%)
IterMVS-LS - completeness (38.72%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (59.44%)
IterMVS-SCA-FT - completeness (36.01%)
LGP-MVS_train
LGP-MVS_train - accuracy (80.15%)
LGP-MVS_train - completeness (59.75%)
LS3D
LS3D - accuracy (84.42%)
LS3D - completeness (48.57%)
LTVRE_ROB
LTVRE_ROB - accuracy (89.00%)
LTVRE_ROB - completeness (12.73%)
MAR-MVS
MAR-MVS - accuracy (60.28%)
MAR-MVS - completeness (67.78%)
MCST-MVS
MCST-MVS - accuracy (74.77%)
MCST-MVS - completeness (75.89%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (69.05%)
MDA-MVSNet-bldmvs - completeness (21.59%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (48.80%)
MDTV_nov1_ep13 - completeness (42.78%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (63.52%)
MDTV_nov1_ep13_2view - completeness (29.08%)
MIMVSNet
MIMVSNet - accuracy (57.09%)
MIMVSNet - completeness (36.53%)
MIMVSNet1
MIMVSNet1 - accuracy (81.01%)
MIMVSNet1 - completeness (19.95%)
MP-MVS
MP-MVS - accuracy (81.43%)
MP-MVS - completeness (70.07%)
MS-PatchMatch
MS-PatchMatch - accuracy (51.34%)
MS-PatchMatch - completeness (50.56%)
MSDG
MSDG - accuracy (67.61%)
MSDG - completeness (44.17%)
MSLP-MVS++
MSLP-MVS++ - accuracy (77.79%)
MSLP-MVS++ - completeness (63.96%)
MSP-MVS
MSP-MVS - accuracy (83.85%)
MSP-MVS - completeness (88.04%)
MVE
MVE - accuracy (49.90%)
MVE - completeness (5.74%)
MVS-HIRNet
MVS-HIRNet - accuracy (42.80%)
MVS-HIRNet - completeness (30.15%)
MVSTER
MVSTER - accuracy (40.63%)
MVSTER - completeness (61.11%)
MVS_0304
MVS_0304 - accuracy (62.26%)
MVS_0304 - completeness (64.35%)
MVS_111021_LR
MVS_111021_LR - accuracy (70.89%)
MVS_111021_LR - completeness (52.32%)
MVS_Test
MVS_Test - accuracy (57.08%)
MVS_Test - completeness (57.45%)
NCCC
NCCC - accuracy (79.61%)
NCCC - completeness (76.93%)
new-patchmatchnet
new-patchmatchnet - accuracy (72.36%)
new-patchmatchnet - completeness (20.52%)
new_pmnet
new_pmnet - accuracy (49.06%)
new_pmnet - completeness (18.68%)
NP-MVS
NP-MVS - accuracy (71.39%)
NP-MVS - completeness (72.62%)
NR-MVSNet
NR-MVSNet - accuracy (69.95%)
NR-MVSNet - completeness (37.26%)
N_pmnet
N_pmnet - accuracy (64.20%)
N_pmnet - completeness (26.22%)
OMC-MVS
OMC-MVS - accuracy (84.62%)
OMC-MVS - completeness (75.67%)
OpenMVS
OpenMVS - accuracy (67.17%)
OpenMVS - completeness (56.44%)
OPM-MVS
OPM-MVS - accuracy (85.25%)
OPM-MVS - completeness (40.82%)
PatchMatch-RL
PatchMatch-RL - accuracy (57.85%)
PatchMatch-RL - completeness (39.04%)
PatchmatchNet
PatchmatchNet - accuracy (51.38%)
PatchmatchNet - completeness (44.85%)
PatchT
PatchT - accuracy (46.37%)
PatchT - completeness (40.38%)
PCF-MVS
PCF-MVS - accuracy (74.88%)
PCF-MVS - completeness (61.35%)
PEN-MVS
PEN-MVS - accuracy (84.66%)
PEN-MVS - completeness (27.64%)
PGM-MVS
PGM-MVS - accuracy (79.38%)
PGM-MVS - completeness (68.80%)
PHI-MVS
PHI-MVS - accuracy (73.39%)
PHI-MVS - completeness (68.03%)
PLC
PLC - accuracy (80.74%)
PLC - completeness (55.69%)
PM-MVS
PM-MVS - accuracy (66.12%)
PM-MVS - completeness (29.16%)
pm-mvs1
pm-mvs1 - accuracy (74.40%)
pm-mvs1 - completeness (27.66%)
PMMVS
PMMVS - accuracy (39.27%)
PMMVS - completeness (56.43%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (68.14%)
pmmvs-eth3d - completeness (31.96%)
PMMVS2
PMMVS2 - accuracy (58.71%)
PMMVS2 - completeness (9.31%)
pmmvs3
pmmvs3 - accuracy (46.31%)
pmmvs3 - completeness (16.89%)
pmmvs5
pmmvs5 - accuracy (50.77%)
pmmvs5 - completeness (30.59%)
pmmvs6
pmmvs6 - accuracy (82.90%)
pmmvs6 - completeness (21.74%)
pmnet_mix02
pmnet_mix02 - accuracy (64.14%)
pmnet_mix02 - completeness (29.38%)
PMVS
PMVS - accuracy (83.33%)
PMVS - completeness (15.69%)
PS-CasMVS
PS-CasMVS - accuracy (84.14%)
PS-CasMVS - completeness (27.36%)
PVSNet_Blended
PVSNet_Blended - accuracy (51.27%)
PVSNet_Blended - completeness (58.67%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (51.27%)
PVSNet_BlendedMVS - completeness (58.67%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (63.65%)
PVSNet_Blended_VisFu - completeness (44.23%)
QAPM
QAPM - accuracy (73.09%)
QAPM - completeness (56.07%)
RPMNet
RPMNet - accuracy (46.90%)
RPMNet - completeness (42.17%)
RPSCF
RPSCF - accuracy (84.01%)
RPSCF - completeness (50.13%)
SCA
SCA - accuracy (51.92%)
SCA - completeness (45.16%)
SD-MVS
SD-MVS - accuracy (82.50%)
SD-MVS - completeness (79.64%)
SED-MVS
SED-MVS - accuracy (84.85%)
SED-MVS - completeness (88.89%)
SF-MVS
SF-MVS - accuracy (84.00%)
SF-MVS - completeness (81.67%)
SMA-MVS
SMA-MVS - accuracy (85.54%)
SMA-MVS - completeness (84.14%)
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 (80.55%)
SteuartSystems-ACMMP - completeness (70.68%)
TAMVS
TAMVS - accuracy (56.33%)
TAMVS - completeness (29.95%)
TAPA-MVS
TAPA-MVS - accuracy (81.82%)
TAPA-MVS - completeness (69.51%)
TDRefinement
TDRefinement - accuracy (89.57%)
TDRefinement - completeness (33.49%)
test-mter
test-mter - accuracy (39.07%)
test-mter - completeness (38.43%)
test1
test1 - accuracy (49.06%)
test1 - completeness (49.30%)
test123
test123 - accuracy (0.66%)
test123 - completeness (0.01%)
testgi
testgi - accuracy (70.87%)
testgi - completeness (20.32%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (36.41%)
TESTMET0.1,1 - completeness (42.51%)
testmvs
testmvs - accuracy (0.66%)
testmvs - completeness (0.01%)
test_part1
test_part1 - accuracy (90.52%)
test_part1 - completeness (38.22%)
thisisatest0515
thisisatest0515 - accuracy (67.59%)
thisisatest0515 - completeness (30.34%)
thisisatest0530
thisisatest0530 - accuracy (55.45%)
thisisatest0530 - completeness (42.72%)
TinyColmap
TinyColmap - accuracy (79.93%)
TinyColmap - completeness (29.83%)
tmp_tt
tmp_tt - accuracy (15.58%)
tmp_tt - completeness (20.12%)
tpm
tpm - accuracy (52.70%)
tpm - completeness (41.93%)
tpm cat1
tpm cat1 - accuracy (52.38%)
tpm cat1 - completeness (49.18%)
tpmrst
tpmrst - accuracy (49.50%)
tpmrst - completeness (47.91%)
train_agg
train_agg - accuracy (74.03%)
train_agg - completeness (75.74%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (75.91%)
TranMVSNet+NR-MVSNet - completeness (36.11%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (78.81%)
TransMVSNet (Re) - completeness (26.33%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (82.99%)
TSAR-MVS + ACMM - completeness (76.00%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (79.25%)
TSAR-MVS + COLMAP - completeness (74.06%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (69.84%)
TSAR-MVS + GP. - completeness (72.98%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (80.87%)
TSAR-MVS + MP. - completeness (80.73%)
tttt0517
tttt0517 - accuracy (55.70%)
tttt0517 - completeness (42.00%)
UA-Net
UA-Net - accuracy (77.25%)
UA-Net - completeness (36.42%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (67.14%)
UGNet - completeness (39.90%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (70.20%)
UniMVSNet (Re) - completeness (37.24%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (86.58%)
UniMVSNet_ETH3D - completeness (28.18%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (70.90%)
UniMVSNet_NR-MVSNet - completeness (37.87%)
USDC
USDC - accuracy (77.89%)
USDC - completeness (39.59%)
Vis-MVSNet
Vis-MVSNet - accuracy (69.10%)
Vis-MVSNet - completeness (37.75%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (68.55%)
Vis-MVSNet (Re-imp) - completeness (39.10%)
WR-MVS_H
WR-MVS_H - accuracy (83.47%)
WR-MVS_H - completeness (26.90%)
X-MVS
X-MVS - accuracy (81.41%)
X-MVS - completeness (65.77%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (84.00%)
xxxxxxxxxxxxxcwj - completeness (81.67%)
zzz-MVS
zzz-MVS - accuracy (84.54%)
zzz-MVS - completeness (77.27%)
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
:
-96.05 to 748.35
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
:
585.0
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