+
−
⇧
i
D
T
kicker (high-res multi-view) - Tolerance 2cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (85.65%)
3Dnovator - completeness (72.10%)
3Dnovator+
3Dnovator+ - accuracy (88.85%)
3Dnovator+ - completeness (74.89%)
ACMH
ACMH - accuracy (95.49%)
ACMH - completeness (39.81%)
ACMH+
ACMH+ - accuracy (93.55%)
ACMH+ - completeness (45.86%)
ACMM
ACMM - accuracy (90.17%)
ACMM - completeness (64.61%)
ACMMP
ACMMP - accuracy (87.89%)
ACMMP - completeness (79.38%)
ACMMPR
ACMMPR - accuracy (90.08%)
ACMMPR - completeness (83.91%)
ACMMP_NAP
ACMMP_NAP - accuracy (89.28%)
ACMMP_NAP - completeness (87.38%)
ACMP
ACMP - accuracy (87.47%)
ACMP - completeness (69.29%)
AdaColmap
AdaColmap - accuracy (82.40%)
AdaColmap - completeness (76.60%)
ADS-MVSNet
ADS-MVSNet - accuracy (72.82%)
ADS-MVSNet - completeness (50.51%)
ambc
ambc - accuracy (88.64%)
ambc - completeness (32.04%)
Anonymous20231206
Anonymous20231206 - accuracy (76.35%)
Anonymous20231206 - completeness (36.63%)
Anonymous202405211
Anonymous202405211 - accuracy (82.01%)
Anonymous202405211 - completeness (51.00%)
anonymousdsp
anonymousdsp - accuracy (85.63%)
anonymousdsp - completeness (33.74%)
APD-MVS
APD-MVS - accuracy (84.04%)
APD-MVS - completeness (90.98%)
APDe-MVS
APDe-MVS - accuracy (91.11%)
APDe-MVS - completeness (91.19%)
baseline1
baseline1 - accuracy (70.97%)
baseline1 - completeness (56.22%)
baseline2
baseline2 - accuracy (60.13%)
baseline2 - completeness (62.62%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (81.53%)
Baseline_NR-MVSNet - completeness (49.15%)
CANet
CANet - accuracy (72.16%)
CANet - completeness (81.60%)
CANet_DTU
CANet_DTU - accuracy (64.11%)
CANet_DTU - completeness (72.06%)
canonicalmvs
canonicalmvs - accuracy (85.97%)
canonicalmvs - completeness (80.05%)
casdiffmvs
casdiffmvs - accuracy (81.53%)
casdiffmvs - completeness (67.05%)
CDPH-MVS
CDPH-MVS - accuracy (80.55%)
CDPH-MVS - completeness (79.67%)
CDS-MVSNet
CDS-MVSNet - accuracy (69.56%)
CDS-MVSNet - completeness (43.53%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (61.63%)
CHOSEN 1792x2688 - completeness (62.08%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (56.29%)
CHOSEN 280x420 - completeness (54.17%)
CLD-MVS
CLD-MVS - accuracy (82.28%)
CLD-MVS - completeness (77.97%)
CMPMVS
CMPMVS - accuracy (68.79%)
CMPMVS - completeness (41.77%)
CNLPA
CNLPA - accuracy (88.18%)
CNLPA - completeness (82.36%)
CNVR-MVS
CNVR-MVS - accuracy (86.31%)
CNVR-MVS - completeness (88.44%)
COLMAP_ROB
COLMAP_ROB - accuracy (94.95%)
COLMAP_ROB - completeness (47.83%)
CostFormer
CostFormer - accuracy (65.52%)
CostFormer - completeness (66.07%)
CP-MVS
CP-MVS - accuracy (88.26%)
CP-MVS - completeness (81.82%)
CP-MVSNet
CP-MVSNet - accuracy (88.79%)
CP-MVSNet - completeness (37.41%)
CPTT-MVS
CPTT-MVS - accuracy (87.70%)
CPTT-MVS - completeness (77.95%)
CR-MVSNet
CR-MVSNet - accuracy (59.93%)
CR-MVSNet - completeness (55.83%)
CS-MVS
CS-MVS - accuracy (67.63%)
CS-MVS - completeness (69.17%)
CSCG
CSCG - accuracy (91.37%)
CSCG - completeness (81.96%)
CVMVSNet
CVMVSNet - accuracy (69.12%)
CVMVSNet - completeness (42.28%)
DCV-MVSNet
DCV-MVSNet - accuracy (85.01%)
DCV-MVSNet - completeness (54.92%)
DeepC-MVS
DeepC-MVS - accuracy (90.01%)
DeepC-MVS - completeness (82.78%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (86.02%)
DeepC-MVS_fast - completeness (83.77%)
DeepMVS_CX
DeepMVS_CX - accuracy (31.41%)
DeepMVS_CX - completeness (23.61%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (88.93%)
DeepPCF-MVS - completeness (93.10%)
DELS-MVS
DELS-MVS - accuracy (75.43%)
DELS-MVS - completeness (65.27%)
diffmvs
diffmvs - accuracy (77.48%)
diffmvs - completeness (68.66%)
DPE-MVS
DPE-MVS - accuracy (88.18%)
DPE-MVS - completeness (93.06%)
DPM-MVS
DPM-MVS - accuracy (81.00%)
DPM-MVS - completeness (86.90%)
dps
dps - accuracy (58.56%)
dps - completeness (56.94%)
DTE-MVSNet
DTE-MVSNet - accuracy (91.38%)
DTE-MVSNet - completeness (36.11%)
DU-MVS
DU-MVS - accuracy (80.64%)
DU-MVS - completeness (49.31%)
DVP-MVS
DVP-MVS - accuracy (92.28%)
DVP-MVS - completeness (93.90%)
E-PMN
E-PMN - accuracy (72.95%)
E-PMN - completeness (10.71%)
Effi-MVS+
Effi-MVS+ - accuracy (74.94%)
Effi-MVS+ - completeness (59.56%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (69.04%)
Effi-MVS+-dtu - completeness (54.12%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (84.24%)
EG-PatchMatch MVS - completeness (32.49%)
EIA-MVS
EIA-MVS - accuracy (62.63%)
EIA-MVS - completeness (69.66%)
EMVS
EMVS - accuracy (72.80%)
EMVS - completeness (11.00%)
EPMVS
EPMVS - accuracy (65.15%)
EPMVS - completeness (61.55%)
EPNet
EPNet - accuracy (68.27%)
EPNet - completeness (81.76%)
EPNet_dtu
EPNet_dtu - accuracy (63.26%)
EPNet_dtu - completeness (69.78%)
EPP-MVSNet
EPP-MVSNet - accuracy (84.17%)
EPP-MVSNet - completeness (53.02%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (65.45%)
ET-MVSNet_ETH3D - completeness (63.61%)
ETV-MVS
ETV-MVS - accuracy (63.22%)
ETV-MVS - completeness (77.50%)
EU-MVSNet
EU-MVSNet - accuracy (75.47%)
EU-MVSNet - completeness (33.03%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (73.01%)
Fast-Effi-MVS+ - completeness (58.88%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (64.46%)
Fast-Effi-MVS+-dtu - completeness (52.51%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (84.87%)
FC-MVSNet-test - completeness (45.66%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (82.90%)
FC-MVSNet-train - completeness (54.96%)
FMVSNet1
FMVSNet1 - accuracy (83.02%)
FMVSNet1 - completeness (43.32%)
FMVSNet2
FMVSNet2 - accuracy (72.28%)
FMVSNet2 - completeness (56.29%)
FMVSNet3
FMVSNet3 - accuracy (62.99%)
FMVSNet3 - completeness (65.32%)
FMVSNet5
FMVSNet5 - accuracy (52.68%)
FMVSNet5 - completeness (57.85%)
FPMVS
FPMVS - accuracy (84.67%)
FPMVS - completeness (35.73%)
GA-MVS
GA-MVS - accuracy (70.51%)
GA-MVS - completeness (45.23%)
GBi-Net
GBi-Net - accuracy (62.99%)
GBi-Net - completeness (65.32%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (57.64%)
GG-mvs-BLEND - completeness (66.83%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (86.92%)
gg-mvs-nofinetune - completeness (25.74%)
Gipuma
Gipuma - accuracy (92.69%)
Gipuma - completeness (25.43%)
gm-plane-assit
gm-plane-assit - accuracy (84.08%)
gm-plane-assit - completeness (21.18%)
HFP-MVS
HFP-MVS - accuracy (89.94%)
HFP-MVS - completeness (85.22%)
HPM-MVS++
HPM-MVS++ - accuracy (87.08%)
HPM-MVS++ - completeness (90.68%)
HQP-MVS
HQP-MVS - accuracy (82.79%)
HQP-MVS - completeness (79.88%)
HyFIR lowres test
HyFIR lowres test - accuracy (63.81%)
HyFIR lowres test - completeness (54.87%)
IB-MVS
IB-MVS - accuracy (63.01%)
IB-MVS - completeness (56.65%)
IS_MVSNet
IS_MVSNet - accuracy (80.11%)
IS_MVSNet - completeness (55.75%)
IterMVS
IterMVS - accuracy (72.23%)
IterMVS - completeness (47.48%)
IterMVS-LS
IterMVS-LS - accuracy (78.93%)
IterMVS-LS - completeness (50.42%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (73.10%)
IterMVS-SCA-FT - completeness (47.56%)
LGP-MVS_train
LGP-MVS_train - accuracy (86.26%)
LGP-MVS_train - completeness (70.09%)
LS3D
LS3D - accuracy (90.83%)
LS3D - completeness (60.77%)
LTVRE_ROB
LTVRE_ROB - accuracy (95.48%)
LTVRE_ROB - completeness (20.36%)
MAR-MVS
MAR-MVS - accuracy (71.21%)
MAR-MVS - completeness (77.62%)
MCST-MVS
MCST-MVS - accuracy (83.14%)
MCST-MVS - completeness (85.66%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (81.62%)
MDA-MVSNet-bldmvs - completeness (29.83%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (62.27%)
MDTV_nov1_ep13 - completeness (58.08%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (76.30%)
MDTV_nov1_ep13_2view - completeness (39.43%)
MIMVSNet
MIMVSNet - accuracy (71.56%)
MIMVSNet - completeness (46.59%)
MIMVSNet1
MIMVSNet1 - accuracy (90.84%)
MIMVSNet1 - completeness (27.00%)
MP-MVS
MP-MVS - accuracy (86.83%)
MP-MVS - completeness (80.79%)
MS-PatchMatch
MS-PatchMatch - accuracy (67.35%)
MS-PatchMatch - completeness (58.01%)
MSDG
MSDG - accuracy (79.73%)
MSDG - completeness (56.52%)
MSLP-MVS++
MSLP-MVS++ - accuracy (85.17%)
MSLP-MVS++ - completeness (75.96%)
MSP-MVS
MSP-MVS - accuracy (90.48%)
MSP-MVS - completeness (93.55%)
MVE
MVE - accuracy (69.11%)
MVE - completeness (8.28%)
MVS-HIRNet
MVS-HIRNet - accuracy (55.69%)
MVS-HIRNet - completeness (39.45%)
MVSTER
MVSTER - accuracy (55.18%)
MVSTER - completeness (78.02%)
MVS_0304
MVS_0304 - accuracy (73.79%)
MVS_0304 - completeness (76.83%)
MVS_111021_LR
MVS_111021_LR - accuracy (82.08%)
MVS_111021_LR - completeness (70.92%)
MVS_Test
MVS_Test - accuracy (69.67%)
MVS_Test - completeness (69.77%)
NCCC
NCCC - accuracy (86.50%)
NCCC - completeness (86.85%)
new-patchmatchnet
new-patchmatchnet - accuracy (85.43%)
new-patchmatchnet - completeness (28.26%)
new_pmnet
new_pmnet - accuracy (65.88%)
new_pmnet - completeness (29.00%)
NP-MVS
NP-MVS - accuracy (78.65%)
NP-MVS - completeness (81.60%)
NR-MVSNet
NR-MVSNet - accuracy (80.64%)
NR-MVSNet - completeness (49.31%)
N_pmnet
N_pmnet - accuracy (79.54%)
N_pmnet - completeness (36.01%)
OMC-MVS
OMC-MVS - accuracy (90.35%)
OMC-MVS - completeness (84.48%)
OpenMVS
OpenMVS - accuracy (77.34%)
OpenMVS - completeness (66.09%)
OPM-MVS
OPM-MVS - accuracy (91.16%)
OPM-MVS - completeness (49.96%)
PatchMatch-RL
PatchMatch-RL - accuracy (71.66%)
PatchMatch-RL - completeness (56.09%)
PatchmatchNet
PatchmatchNet - accuracy (65.92%)
PatchmatchNet - completeness (60.40%)
PatchT
PatchT - accuracy (59.80%)
PatchT - completeness (53.89%)
PCF-MVS
PCF-MVS - accuracy (82.36%)
PCF-MVS - completeness (69.24%)
PEN-MVS
PEN-MVS - accuracy (91.04%)
PEN-MVS - completeness (36.87%)
PGM-MVS
PGM-MVS - accuracy (85.41%)
PGM-MVS - completeness (80.39%)
PHI-MVS
PHI-MVS - accuracy (82.55%)
PHI-MVS - completeness (82.22%)
PLC
PLC - accuracy (87.06%)
PLC - completeness (69.26%)
PM-MVS
PM-MVS - accuracy (80.13%)
PM-MVS - completeness (41.90%)
pm-mvs1
pm-mvs1 - accuracy (87.59%)
pm-mvs1 - completeness (34.73%)
PMMVS
PMMVS - accuracy (55.49%)
PMMVS - completeness (71.31%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (80.83%)
pmmvs-eth3d - completeness (40.93%)
PMMVS2
PMMVS2 - accuracy (74.75%)
PMMVS2 - completeness (13.69%)
pmmvs3
pmmvs3 - accuracy (61.57%)
pmmvs3 - completeness (23.40%)
pmmvs5
pmmvs5 - accuracy (67.17%)
pmmvs5 - completeness (40.21%)
pmmvs6
pmmvs6 - accuracy (93.72%)
pmmvs6 - completeness (26.77%)
pmnet_mix02
pmnet_mix02 - accuracy (79.13%)
pmnet_mix02 - completeness (40.38%)
PMVS
PMVS - accuracy (90.00%)
PMVS - completeness (20.45%)
PS-CasMVS
PS-CasMVS - accuracy (90.50%)
PS-CasMVS - completeness (36.42%)
PVSNet_Blended
PVSNet_Blended - accuracy (65.42%)
PVSNet_Blended - completeness (74.99%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (65.42%)
PVSNet_BlendedMVS - completeness (74.99%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (76.05%)
PVSNet_Blended_VisFu - completeness (56.46%)
QAPM
QAPM - accuracy (83.28%)
QAPM - completeness (66.22%)
RPMNet
RPMNet - accuracy (59.93%)
RPMNet - completeness (55.83%)
RPSCF
RPSCF - accuracy (91.46%)
RPSCF - completeness (62.42%)
SCA
SCA - accuracy (66.41%)
SCA - completeness (61.13%)
SD-MVS
SD-MVS - accuracy (89.26%)
SD-MVS - completeness (89.09%)
SED-MVS
SED-MVS - accuracy (90.73%)
SED-MVS - completeness (94.16%)
SF-MVS
SF-MVS - accuracy (89.28%)
SF-MVS - completeness (89.15%)
SMA-MVS
SMA-MVS - accuracy (90.79%)
SMA-MVS - completeness (90.56%)
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 (86.33%)
SteuartSystems-ACMMP - completeness (82.86%)
TAMVS
TAMVS - accuracy (70.23%)
TAMVS - completeness (38.76%)
TAPA-MVS
TAPA-MVS - accuracy (89.15%)
TAPA-MVS - completeness (80.80%)
TDRefinement
TDRefinement - accuracy (95.55%)
TDRefinement - completeness (44.03%)
test-mter
test-mter - accuracy (53.19%)
test-mter - completeness (55.64%)
test1
test1 - accuracy (62.99%)
test1 - completeness (65.32%)
test123
test123 - accuracy (1.11%)
test123 - completeness (0.05%)
testgi
testgi - accuracy (84.91%)
testgi - completeness (29.12%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (50.76%)
TESTMET0.1,1 - completeness (58.62%)
testmvs
testmvs - accuracy (1.48%)
testmvs - completeness (0.05%)
test_part1
test_part1 - accuracy (96.50%)
test_part1 - completeness (44.52%)
thisisatest0515
thisisatest0515 - accuracy (81.05%)
thisisatest0515 - completeness (41.55%)
thisisatest0530
thisisatest0530 - accuracy (69.17%)
thisisatest0530 - completeness (59.77%)
TinyColmap
TinyColmap - accuracy (88.71%)
TinyColmap - completeness (40.28%)
tmp_tt
tmp_tt - accuracy (28.69%)
tmp_tt - completeness (55.09%)
tpm
tpm - accuracy (65.72%)
tpm - completeness (51.61%)
tpm cat1
tpm cat1 - accuracy (64.88%)
tpm cat1 - completeness (61.18%)
tpmrst
tpmrst - accuracy (63.80%)
tpmrst - completeness (60.69%)
train_agg
train_agg - accuracy (81.71%)
train_agg - completeness (86.31%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (85.47%)
TranMVSNet+NR-MVSNet - completeness (46.74%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (90.68%)
TransMVSNet (Re) - completeness (32.30%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (88.86%)
TSAR-MVS + ACMM - completeness (85.96%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (86.40%)
TSAR-MVS + COLMAP - completeness (83.16%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (82.45%)
TSAR-MVS + GP. - completeness (87.10%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (87.88%)
TSAR-MVS + MP. - completeness (90.13%)
tttt0517
tttt0517 - accuracy (69.24%)
tttt0517 - completeness (59.30%)
UA-Net
UA-Net - accuracy (85.41%)
UA-Net - completeness (47.01%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (79.85%)
UGNet - completeness (54.71%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (81.18%)
UniMVSNet (Re) - completeness (49.83%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (93.84%)
UniMVSNet_ETH3D - completeness (36.17%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (81.46%)
UniMVSNet_NR-MVSNet - completeness (50.03%)
USDC
USDC - accuracy (87.45%)
USDC - completeness (54.90%)
Vis-MVSNet
Vis-MVSNet - accuracy (81.11%)
Vis-MVSNet - completeness (48.40%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (80.48%)
Vis-MVSNet (Re-imp) - completeness (55.22%)
WR-MVS_H
WR-MVS_H - accuracy (90.14%)
WR-MVS_H - completeness (36.51%)
X-MVS
X-MVS - accuracy (87.29%)
X-MVS - completeness (78.33%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (89.28%)
xxxxxxxxxxxxxcwj - completeness (89.15%)
zzz-MVS
zzz-MVS - accuracy (90.23%)
zzz-MVS - completeness (86.92%)
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
:
0.00 to 1.00
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
:
0.4
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