+
−
⇧
i
D
T
relief (high-res multi-view) - Tolerance 2cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (87.22%)
3Dnovator - completeness (82.89%)
3Dnovator+
3Dnovator+ - accuracy (93.03%)
3Dnovator+ - completeness (82.27%)
ACMH
ACMH - accuracy (94.14%)
ACMH - completeness (70.55%)
ACMH+
ACMH+ - accuracy (95.28%)
ACMH+ - completeness (67.24%)
ACMM
ACMM - accuracy (95.79%)
ACMM - completeness (74.97%)
ACMMP
ACMMP - accuracy (95.59%)
ACMMP - completeness (78.56%)
ACMMPR
ACMMPR - accuracy (95.24%)
ACMMPR - completeness (80.78%)
ACMMP_NAP
ACMMP_NAP - accuracy (94.36%)
ACMMP_NAP - completeness (84.85%)
ACMP
ACMP - accuracy (95.31%)
ACMP - completeness (73.74%)
AdaColmap
AdaColmap - accuracy (91.58%)
AdaColmap - completeness (76.82%)
ADS-MVSNet
ADS-MVSNet - accuracy (59.34%)
ADS-MVSNet - completeness (64.91%)
ambc
ambc - accuracy (89.14%)
ambc - completeness (64.88%)
Anonymous20231206
Anonymous20231206 - accuracy (74.52%)
Anonymous20231206 - completeness (66.79%)
Anonymous202405211
Anonymous202405211 - accuracy (86.68%)
Anonymous202405211 - completeness (76.28%)
anonymousdsp
anonymousdsp - accuracy (94.56%)
anonymousdsp - completeness (64.53%)
APD-MVS
APD-MVS - accuracy (92.94%)
APD-MVS - completeness (82.00%)
APDe-MVS
APDe-MVS - accuracy (93.16%)
APDe-MVS - completeness (83.38%)
baseline1
baseline1 - accuracy (79.65%)
baseline1 - completeness (83.35%)
baseline2
baseline2 - accuracy (76.53%)
baseline2 - completeness (79.74%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (91.79%)
Baseline_NR-MVSNet - completeness (69.67%)
CANet
CANet - accuracy (87.65%)
CANet - completeness (84.68%)
CANet_DTU
CANet_DTU - accuracy (82.05%)
CANet_DTU - completeness (81.13%)
canonicalmvs
canonicalmvs - accuracy (88.62%)
canonicalmvs - completeness (78.87%)
casdiffmvs
casdiffmvs - accuracy (82.89%)
casdiffmvs - completeness (82.16%)
CDPH-MVS
CDPH-MVS - accuracy (91.00%)
CDPH-MVS - completeness (81.33%)
CDS-MVSNet
CDS-MVSNet - accuracy (84.20%)
CDS-MVSNet - completeness (75.68%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (72.13%)
CHOSEN 1792x2688 - completeness (86.22%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (73.61%)
CHOSEN 280x420 - completeness (73.85%)
CLD-MVS
CLD-MVS - accuracy (89.41%)
CLD-MVS - completeness (81.75%)
CMPMVS
CMPMVS - accuracy (81.58%)
CMPMVS - completeness (64.81%)
CNLPA
CNLPA - accuracy (91.27%)
CNLPA - completeness (73.00%)
CNVR-MVS
CNVR-MVS - accuracy (91.69%)
CNVR-MVS - completeness (87.04%)
COLMAP_ROB
COLMAP_ROB - accuracy (96.49%)
COLMAP_ROB - completeness (63.88%)
CostFormer
CostFormer - accuracy (65.69%)
CostFormer - completeness (75.84%)
CP-MVS
CP-MVS - accuracy (95.77%)
CP-MVS - completeness (79.56%)
CP-MVSNet
CP-MVSNet - accuracy (96.16%)
CP-MVSNet - completeness (56.60%)
CPTT-MVS
CPTT-MVS - accuracy (94.28%)
CPTT-MVS - completeness (73.89%)
CR-MVSNet
CR-MVSNet - accuracy (71.64%)
CR-MVSNet - completeness (72.76%)
CS-MVS
CS-MVS - accuracy (88.31%)
CS-MVS - completeness (82.50%)
CSCG
CSCG - accuracy (91.45%)
CSCG - completeness (82.32%)
CVMVSNet
CVMVSNet - accuracy (81.02%)
CVMVSNet - completeness (64.42%)
DCV-MVSNet
DCV-MVSNet - accuracy (88.66%)
DCV-MVSNet - completeness (75.05%)
DeepC-MVS
DeepC-MVS - accuracy (92.90%)
DeepC-MVS - completeness (84.30%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (91.16%)
DeepC-MVS_fast - completeness (85.08%)
DeepMVS_CX
DeepMVS_CX - accuracy (28.41%)
DeepMVS_CX - completeness (22.60%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (90.62%)
DeepPCF-MVS - completeness (85.94%)
DELS-MVS
DELS-MVS - accuracy (85.12%)
DELS-MVS - completeness (88.07%)
diffmvs
diffmvs - accuracy (79.74%)
diffmvs - completeness (78.30%)
DPE-MVS
DPE-MVS - accuracy (92.75%)
DPE-MVS - completeness (84.84%)
DPM-MVS
DPM-MVS - accuracy (82.81%)
DPM-MVS - completeness (90.24%)
dps
dps - accuracy (69.57%)
dps - completeness (69.50%)
DTE-MVSNet
DTE-MVSNet - accuracy (95.65%)
DTE-MVSNet - completeness (58.01%)
DU-MVS
DU-MVS - accuracy (91.79%)
DU-MVS - completeness (69.67%)
DVP-MVS
DVP-MVS - accuracy (92.49%)
DVP-MVS - completeness (86.26%)
E-PMN
E-PMN - accuracy (80.97%)
E-PMN - completeness (11.34%)
Effi-MVS+
Effi-MVS+ - accuracy (85.06%)
Effi-MVS+ - completeness (78.34%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (88.40%)
Effi-MVS+-dtu - completeness (68.08%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (89.95%)
EG-PatchMatch MVS - completeness (74.30%)
EIA-MVS
EIA-MVS - accuracy (88.49%)
EIA-MVS - completeness (77.35%)
EMVS
EMVS - accuracy (80.41%)
EMVS - completeness (10.13%)
EPMVS
EPMVS - accuracy (59.81%)
EPMVS - completeness (71.82%)
EPNet
EPNet - accuracy (85.02%)
EPNet - completeness (82.43%)
EPNet_dtu
EPNet_dtu - accuracy (78.83%)
EPNet_dtu - completeness (72.20%)
EPP-MVSNet
EPP-MVSNet - accuracy (92.56%)
EPP-MVSNet - completeness (74.40%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (84.40%)
ET-MVSNet_ETH3D - completeness (73.56%)
ETV-MVS
ETV-MVS - accuracy (90.30%)
ETV-MVS - completeness (80.99%)
EU-MVSNet
EU-MVSNet - accuracy (83.73%)
EU-MVSNet - completeness (53.80%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (88.15%)
Fast-Effi-MVS+ - completeness (76.06%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (81.74%)
Fast-Effi-MVS+-dtu - completeness (71.57%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (91.09%)
FC-MVSNet-test - completeness (58.39%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (88.30%)
FC-MVSNet-train - completeness (75.57%)
FMVSNet1
FMVSNet1 - accuracy (85.57%)
FMVSNet1 - completeness (77.49%)
FMVSNet2
FMVSNet2 - accuracy (80.66%)
FMVSNet2 - completeness (81.15%)
FMVSNet3
FMVSNet3 - accuracy (76.58%)
FMVSNet3 - completeness (82.49%)
FMVSNet5
FMVSNet5 - accuracy (73.88%)
FMVSNet5 - completeness (70.88%)
FPMVS
FPMVS - accuracy (91.24%)
FPMVS - completeness (43.57%)
GA-MVS
GA-MVS - accuracy (77.28%)
GA-MVS - completeness (79.62%)
GBi-Net
GBi-Net - accuracy (85.57%)
GBi-Net - completeness (77.49%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (64.11%)
GG-mvs-BLEND - completeness (78.40%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (77.60%)
gg-mvs-nofinetune - completeness (85.06%)
Gipuma
Gipuma - accuracy (94.45%)
Gipuma - completeness (43.20%)
gm-plane-assit
gm-plane-assit - accuracy (73.65%)
gm-plane-assit - completeness (87.09%)
HFP-MVS
HFP-MVS - accuracy (94.17%)
HFP-MVS - completeness (81.85%)
HPM-MVS++
HPM-MVS++ - accuracy (90.97%)
HPM-MVS++ - completeness (86.33%)
HQP-MVS
HQP-MVS - accuracy (86.49%)
HQP-MVS - completeness (82.46%)
HyFIR lowres test
HyFIR lowres test - accuracy (74.13%)
HyFIR lowres test - completeness (79.11%)
IB-MVS
IB-MVS - accuracy (86.26%)
IB-MVS - completeness (69.18%)
IS_MVSNet
IS_MVSNet - accuracy (91.08%)
IS_MVSNet - completeness (78.83%)
IterMVS
IterMVS - accuracy (76.28%)
IterMVS - completeness (72.12%)
IterMVS-LS
IterMVS-LS - accuracy (80.54%)
IterMVS-LS - completeness (73.93%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (80.28%)
IterMVS-SCA-FT - completeness (70.36%)
LGP-MVS_train
LGP-MVS_train - accuracy (95.44%)
LGP-MVS_train - completeness (75.97%)
LS3D
LS3D - accuracy (94.43%)
LS3D - completeness (69.88%)
LTVRE_ROB
LTVRE_ROB - accuracy (97.06%)
LTVRE_ROB - completeness (60.47%)
MAR-MVS
MAR-MVS - accuracy (88.71%)
MAR-MVS - completeness (82.37%)
MCST-MVS
MCST-MVS - accuracy (87.27%)
MCST-MVS - completeness (88.35%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (92.78%)
MDA-MVSNet-bldmvs - completeness (41.11%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (68.19%)
MDTV_nov1_ep13 - completeness (70.72%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (76.80%)
MDTV_nov1_ep13_2view - completeness (62.36%)
MIMVSNet
MIMVSNet - accuracy (71.43%)
MIMVSNet - completeness (74.97%)
MIMVSNet1
MIMVSNet1 - accuracy (85.37%)
MIMVSNet1 - completeness (57.14%)
MP-MVS
MP-MVS - accuracy (94.94%)
MP-MVS - completeness (80.97%)
MS-PatchMatch
MS-PatchMatch - accuracy (76.62%)
MS-PatchMatch - completeness (81.70%)
MSDG
MSDG - accuracy (87.20%)
MSDG - completeness (72.12%)
MSLP-MVS++
MSLP-MVS++ - accuracy (93.23%)
MSLP-MVS++ - completeness (78.43%)
MSP-MVS
MSP-MVS - accuracy (88.30%)
MSP-MVS - completeness (87.67%)
MVE
MVE - accuracy (67.19%)
MVE - completeness (18.89%)
MVS-HIRNet
MVS-HIRNet - accuracy (61.11%)
MVS-HIRNet - completeness (65.42%)
MVSTER
MVSTER - accuracy (79.68%)
MVSTER - completeness (83.29%)
MVS_0304
MVS_0304 - accuracy (88.62%)
MVS_0304 - completeness (85.54%)
MVS_111021_LR
MVS_111021_LR - accuracy (89.50%)
MVS_111021_LR - completeness (77.01%)
MVS_Test
MVS_Test - accuracy (78.30%)
MVS_Test - completeness (82.07%)
NCCC
NCCC - accuracy (91.72%)
NCCC - completeness (84.64%)
new-patchmatchnet
new-patchmatchnet - accuracy (76.80%)
new-patchmatchnet - completeness (50.96%)
new_pmnet
new_pmnet - accuracy (67.00%)
new_pmnet - completeness (44.07%)
NR-MVSNet
NR-MVSNet - accuracy (87.19%)
NR-MVSNet - completeness (74.35%)
N_pmnet
N_pmnet - accuracy (64.68%)
N_pmnet - completeness (55.67%)
OMC-MVS
OMC-MVS - accuracy (92.63%)
OMC-MVS - completeness (76.60%)
OpenMVS
OpenMVS - accuracy (84.67%)
OpenMVS - completeness (79.92%)
OPM-MVS
OPM-MVS - accuracy (93.32%)
OPM-MVS - completeness (80.38%)
PatchMatch-RL
PatchMatch-RL - accuracy (84.83%)
PatchMatch-RL - completeness (68.22%)
PatchmatchNet
PatchmatchNet - accuracy (66.58%)
PatchmatchNet - completeness (70.61%)
PatchT
PatchT - accuracy (71.64%)
PatchT - completeness (72.76%)
PCF-MVS
PCF-MVS - accuracy (85.88%)
PCF-MVS - completeness (77.11%)
PEN-MVS
PEN-MVS - accuracy (95.70%)
PEN-MVS - completeness (57.63%)
PGM-MVS
PGM-MVS - accuracy (95.01%)
PGM-MVS - completeness (80.45%)
PHI-MVS
PHI-MVS - accuracy (90.88%)
PHI-MVS - completeness (84.01%)
PLC
PLC - accuracy (90.88%)
PLC - completeness (72.05%)
PM-MVS
PM-MVS - accuracy (86.56%)
PM-MVS - completeness (57.64%)
pm-mvs1
pm-mvs1 - accuracy (86.37%)
pm-mvs1 - completeness (74.32%)
PMMVS
PMMVS - accuracy (70.21%)
PMMVS - completeness (79.03%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (80.78%)
pmmvs-eth3d - completeness (65.54%)
PMMVS2
PMMVS2 - accuracy (73.78%)
PMMVS2 - completeness (27.64%)
pmmvs3
pmmvs3 - accuracy (73.36%)
pmmvs3 - completeness (55.98%)
pmmvs5
pmmvs5 - accuracy (73.21%)
pmmvs5 - completeness (72.55%)
pmmvs6
pmmvs6 - accuracy (89.21%)
pmmvs6 - completeness (68.77%)
pmnet_mix02
pmnet_mix02 - accuracy (70.48%)
pmnet_mix02 - completeness (60.97%)
PMVS
PMVS - accuracy (97.01%)
PMVS - completeness (41.99%)
PS-CasMVS
PS-CasMVS - accuracy (96.30%)
PS-CasMVS - completeness (56.42%)
PVSNet_Blended
PVSNet_Blended - accuracy (82.73%)
PVSNet_Blended - completeness (84.24%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (82.73%)
PVSNet_BlendedMVS - completeness (84.24%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (87.38%)
PVSNet_Blended_VisFu - completeness (81.17%)
QAPM
QAPM - accuracy (84.99%)
QAPM - completeness (82.46%)
RPMNet
RPMNet - accuracy (70.37%)
RPMNet - completeness (66.10%)
RPSCF
RPSCF - accuracy (95.15%)
RPSCF - completeness (57.15%)
SCA
SCA - accuracy (68.99%)
SCA - completeness (70.96%)
SD-MVS
SD-MVS - accuracy (93.10%)
SD-MVS - completeness (82.66%)
SED-MVS
SED-MVS - accuracy (92.94%)
SED-MVS - completeness (86.36%)
SF-MVS
SF-MVS - accuracy (91.69%)
SF-MVS - completeness (83.52%)
SMA-MVS
SMA-MVS - accuracy (93.89%)
SMA-MVS - completeness (86.28%)
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 (95.13%)
SteuartSystems-ACMMP - completeness (83.63%)
TAMVS
TAMVS - accuracy (74.48%)
TAMVS - completeness (70.23%)
TAPA-MVS
TAPA-MVS - accuracy (90.11%)
TAPA-MVS - completeness (74.59%)
TDRefinement
TDRefinement - accuracy (97.69%)
TDRefinement - completeness (61.86%)
test-mter
test-mter - accuracy (68.69%)
test-mter - completeness (73.52%)
test1
test1 - accuracy (85.57%)
test1 - completeness (77.49%)
test123
test123 - accuracy (1.43%)
test123 - completeness (0.02%)
testgi
testgi - accuracy (76.54%)
testgi - completeness (65.26%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (66.54%)
TESTMET0.1,1 - completeness (75.64%)
testmvs
testmvs - accuracy (1.25%)
testmvs - completeness (0.05%)
test_part1
test_part1 - accuracy (92.93%)
test_part1 - completeness (72.19%)
thisisatest0515
thisisatest0515 - accuracy (85.98%)
thisisatest0515 - completeness (71.69%)
thisisatest0530
thisisatest0530 - accuracy (83.88%)
thisisatest0530 - completeness (76.99%)
TinyColmap
TinyColmap - accuracy (89.29%)
TinyColmap - completeness (63.95%)
tmp_tt
tmp_tt - accuracy (33.23%)
tmp_tt - completeness (29.91%)
tpm
tpm - accuracy (64.20%)
tpm - completeness (70.58%)
tpm cat1
tpm cat1 - accuracy (61.53%)
tpm cat1 - completeness (70.11%)
tpmrst
tpmrst - accuracy (56.47%)
tpmrst - completeness (71.80%)
train_agg
train_agg - accuracy (90.12%)
train_agg - completeness (83.10%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (91.61%)
TranMVSNet+NR-MVSNet - completeness (70.36%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (86.27%)
TransMVSNet (Re) - completeness (73.84%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (92.75%)
TSAR-MVS + ACMM - completeness (82.06%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (87.53%)
TSAR-MVS + COLMAP - completeness (78.76%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (91.11%)
TSAR-MVS + GP. - completeness (80.43%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (93.58%)
TSAR-MVS + MP. - completeness (81.22%)
tttt0517
tttt0517 - accuracy (84.49%)
tttt0517 - completeness (76.48%)
UA-Net
UA-Net - accuracy (96.06%)
UA-Net - completeness (73.27%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (88.39%)
UGNet - completeness (74.78%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (91.23%)
UniMVSNet (Re) - completeness (70.49%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (93.63%)
UniMVSNet_ETH3D - completeness (65.81%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (90.43%)
UniMVSNet_NR-MVSNet - completeness (71.02%)
USDC
USDC - accuracy (83.63%)
USDC - completeness (70.60%)
Vis-MVSNet
Vis-MVSNet - accuracy (91.34%)
Vis-MVSNet - completeness (77.49%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (86.87%)
Vis-MVSNet (Re-imp) - completeness (73.10%)
WR-MVS_H
WR-MVS_H - accuracy (95.82%)
WR-MVS_H - completeness (56.43%)
X-MVS
X-MVS - accuracy (95.25%)
X-MVS - completeness (80.03%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (91.69%)
xxxxxxxxxxxxxcwj - completeness (83.52%)
zzz-MVS
zzz-MVS - accuracy (95.05%)
zzz-MVS - completeness (81.59%)
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
:
-11.88 to 39.19
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
:
35.4
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