+
−
⇧
i
D
T
terrains (high-res multi-view) - Tolerance 2cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (88.12%)
3Dnovator - completeness (89.99%)
3Dnovator+
3Dnovator+ - accuracy (92.21%)
3Dnovator+ - completeness (90.77%)
ACMH
ACMH - accuracy (89.94%)
ACMH - completeness (79.59%)
ACMH+
ACMH+ - accuracy (90.43%)
ACMH+ - completeness (78.32%)
ACMM
ACMM - accuracy (92.91%)
ACMM - completeness (83.29%)
ACMMP
ACMMP - accuracy (93.51%)
ACMMP - completeness (90.80%)
ACMMPR
ACMMPR - accuracy (93.85%)
ACMMPR - completeness (91.43%)
ACMMP_NAP
ACMMP_NAP - accuracy (94.32%)
ACMMP_NAP - completeness (94.21%)
ACMP
ACMP - accuracy (92.22%)
ACMP - completeness (88.98%)
AdaColmap
AdaColmap - accuracy (86.48%)
AdaColmap - completeness (86.45%)
ADS-MVSNet
ADS-MVSNet - accuracy (51.42%)
ADS-MVSNet - completeness (72.72%)
ambc
ambc - accuracy (86.84%)
ambc - completeness (67.12%)
Anonymous20231206
Anonymous20231206 - accuracy (63.17%)
Anonymous20231206 - completeness (75.73%)
Anonymous202405211
Anonymous202405211 - accuracy (78.98%)
Anonymous202405211 - completeness (90.85%)
anonymousdsp
anonymousdsp - accuracy (93.84%)
anonymousdsp - completeness (85.59%)
APD-MVS
APD-MVS - accuracy (92.24%)
APD-MVS - completeness (95.49%)
APDe-MVS
APDe-MVS - accuracy (93.58%)
APDe-MVS - completeness (96.78%)
baseline1
baseline1 - accuracy (70.27%)
baseline1 - completeness (83.28%)
baseline2
baseline2 - accuracy (70.88%)
baseline2 - completeness (91.43%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (82.09%)
Baseline_NR-MVSNet - completeness (82.82%)
CANet
CANet - accuracy (85.84%)
CANet - completeness (95.50%)
CANet_DTU
CANet_DTU - accuracy (79.88%)
CANet_DTU - completeness (90.21%)
canonicalmvs
canonicalmvs - accuracy (89.09%)
canonicalmvs - completeness (92.16%)
casdiffmvs
casdiffmvs - accuracy (80.34%)
casdiffmvs - completeness (93.72%)
CDPH-MVS
CDPH-MVS - accuracy (89.71%)
CDPH-MVS - completeness (92.84%)
CDS-MVSNet
CDS-MVSNet - accuracy (70.07%)
CDS-MVSNet - completeness (86.34%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (73.02%)
CHOSEN 1792x2688 - completeness (96.75%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (63.07%)
CHOSEN 280x420 - completeness (86.75%)
CLD-MVS
CLD-MVS - accuracy (81.01%)
CLD-MVS - completeness (90.39%)
CMPMVS
CMPMVS - accuracy (85.86%)
CMPMVS - completeness (68.03%)
CNLPA
CNLPA - accuracy (88.88%)
CNLPA - completeness (85.76%)
CNVR-MVS
CNVR-MVS - accuracy (91.64%)
CNVR-MVS - completeness (97.18%)
COLMAP_ROB
COLMAP_ROB - accuracy (93.60%)
COLMAP_ROB - completeness (63.02%)
CostFormer
CostFormer - accuracy (69.71%)
CostFormer - completeness (92.83%)
CP-MVS
CP-MVS - accuracy (93.78%)
CP-MVS - completeness (92.51%)
CP-MVSNet
CP-MVSNet - accuracy (89.64%)
CP-MVSNet - completeness (75.56%)
CPTT-MVS
CPTT-MVS - accuracy (92.45%)
CPTT-MVS - completeness (92.06%)
CR-MVSNet
CR-MVSNet - accuracy (69.40%)
CR-MVSNet - completeness (83.23%)
CS-MVS
CS-MVS - accuracy (81.18%)
CS-MVS - completeness (94.71%)
CSCG
CSCG - accuracy (93.44%)
CSCG - completeness (95.40%)
CVMVSNet
CVMVSNet - accuracy (83.43%)
CVMVSNet - completeness (75.01%)
DCV-MVSNet
DCV-MVSNet - accuracy (85.73%)
DCV-MVSNet - completeness (88.13%)
DeepC-MVS
DeepC-MVS - accuracy (92.57%)
DeepC-MVS - completeness (94.77%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (91.09%)
DeepC-MVS_fast - completeness (93.78%)
DeepMVS_CX
DeepMVS_CX - accuracy (45.77%)
DeepMVS_CX - completeness (30.01%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (92.03%)
DeepPCF-MVS - completeness (96.77%)
DELS-MVS
DELS-MVS - accuracy (83.57%)
DELS-MVS - completeness (97.22%)
diffmvs
diffmvs - accuracy (80.50%)
diffmvs - completeness (94.23%)
DPE-MVS
DPE-MVS - accuracy (93.74%)
DPE-MVS - completeness (97.28%)
DPM-MVS
DPM-MVS - accuracy (88.48%)
DPM-MVS - completeness (90.78%)
dps
dps - accuracy (64.77%)
dps - completeness (79.02%)
DTE-MVSNet
DTE-MVSNet - accuracy (87.84%)
DTE-MVSNet - completeness (70.93%)
DU-MVS
DU-MVS - accuracy (83.02%)
DU-MVS - completeness (84.95%)
DVP-MVS
DVP-MVS - accuracy (93.54%)
DVP-MVS - completeness (98.25%)
E-PMN
E-PMN - accuracy (42.26%)
E-PMN - completeness (21.32%)
Effi-MVS+
Effi-MVS+ - accuracy (84.20%)
Effi-MVS+ - completeness (90.73%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (84.57%)
Effi-MVS+-dtu - completeness (86.38%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (85.65%)
EG-PatchMatch MVS - completeness (77.14%)
EIA-MVS
EIA-MVS - accuracy (78.78%)
EIA-MVS - completeness (94.01%)
EMVS
EMVS - accuracy (41.11%)
EMVS - completeness (18.51%)
EPMVS
EPMVS - accuracy (53.35%)
EPMVS - completeness (79.37%)
EPNet
EPNet - accuracy (84.61%)
EPNet - completeness (92.09%)
EPNet_dtu
EPNet_dtu - accuracy (75.60%)
EPNet_dtu - completeness (79.38%)
EPP-MVSNet
EPP-MVSNet - accuracy (87.56%)
EPP-MVSNet - completeness (90.30%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (77.67%)
ET-MVSNet_ETH3D - completeness (89.80%)
ETV-MVS
ETV-MVS - accuracy (81.95%)
ETV-MVS - completeness (95.73%)
EU-MVSNet
EU-MVSNet - accuracy (83.07%)
EU-MVSNet - completeness (68.21%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (83.17%)
Fast-Effi-MVS+ - completeness (86.65%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (75.78%)
Fast-Effi-MVS+-dtu - completeness (87.79%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (74.34%)
FC-MVSNet-test - completeness (64.40%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (81.95%)
FC-MVSNet-train - completeness (87.12%)
FMVSNet1
FMVSNet1 - accuracy (82.40%)
FMVSNet1 - completeness (81.60%)
FMVSNet2
FMVSNet2 - accuracy (80.37%)
FMVSNet2 - completeness (83.73%)
FMVSNet3
FMVSNet3 - accuracy (79.43%)
FMVSNet3 - completeness (84.34%)
FMVSNet5
FMVSNet5 - accuracy (62.26%)
FMVSNet5 - completeness (66.91%)
FPMVS
FPMVS - accuracy (85.21%)
FPMVS - completeness (45.54%)
GA-MVS
GA-MVS - accuracy (75.30%)
GA-MVS - completeness (86.56%)
GBi-Net
GBi-Net - accuracy (80.37%)
GBi-Net - completeness (83.73%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (55.18%)
GG-mvs-BLEND - completeness (95.20%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (66.57%)
gg-mvs-nofinetune - completeness (91.78%)
Gipuma
Gipuma - accuracy (83.69%)
Gipuma - completeness (26.55%)
gm-plane-assit
gm-plane-assit - accuracy (60.37%)
gm-plane-assit - completeness (89.28%)
HFP-MVS
HFP-MVS - accuracy (93.87%)
HFP-MVS - completeness (92.40%)
HPM-MVS++
HPM-MVS++ - accuracy (91.69%)
HPM-MVS++ - completeness (95.60%)
HQP-MVS
HQP-MVS - accuracy (90.95%)
HQP-MVS - completeness (93.18%)
HyFIR lowres test
HyFIR lowres test - accuracy (70.10%)
HyFIR lowres test - completeness (93.35%)
IB-MVS
IB-MVS - accuracy (82.36%)
IB-MVS - completeness (92.93%)
IS_MVSNet
IS_MVSNet - accuracy (83.42%)
IS_MVSNet - completeness (89.47%)
IterMVS
IterMVS - accuracy (74.25%)
IterMVS - completeness (83.99%)
IterMVS-LS
IterMVS-LS - accuracy (84.36%)
IterMVS-LS - completeness (86.01%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (79.70%)
IterMVS-SCA-FT - completeness (83.53%)
LGP-MVS_train
LGP-MVS_train - accuracy (92.63%)
LGP-MVS_train - completeness (88.93%)
LS3D
LS3D - accuracy (91.35%)
LS3D - completeness (71.43%)
LTVRE_ROB
LTVRE_ROB - accuracy (95.56%)
LTVRE_ROB - completeness (72.00%)
MAR-MVS
MAR-MVS - accuracy (87.57%)
MAR-MVS - completeness (87.67%)
MCST-MVS
MCST-MVS - accuracy (89.30%)
MCST-MVS - completeness (97.65%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (73.69%)
MDA-MVSNet-bldmvs - completeness (61.65%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (61.57%)
MDTV_nov1_ep13 - completeness (80.52%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (66.26%)
MDTV_nov1_ep13_2view - completeness (73.19%)
MIMVSNet
MIMVSNet - accuracy (59.83%)
MIMVSNet - completeness (73.60%)
MIMVSNet1
MIMVSNet1 - accuracy (69.18%)
MIMVSNet1 - completeness (56.78%)
MP-MVS
MP-MVS - accuracy (93.24%)
MP-MVS - completeness (94.06%)
MS-PatchMatch
MS-PatchMatch - accuracy (75.90%)
MS-PatchMatch - completeness (80.02%)
MSDG
MSDG - accuracy (80.67%)
MSDG - completeness (73.37%)
MSLP-MVS++
MSLP-MVS++ - accuracy (92.46%)
MSLP-MVS++ - completeness (90.18%)
MSP-MVS
MSP-MVS - accuracy (91.01%)
MSP-MVS - completeness (98.29%)
MVE
MVE - accuracy (57.38%)
MVE - completeness (28.53%)
MVS-HIRNet
MVS-HIRNet - accuracy (52.28%)
MVS-HIRNet - completeness (71.08%)
MVSTER
MVSTER - accuracy (80.20%)
MVSTER - completeness (91.12%)
MVS_0304
MVS_0304 - accuracy (88.05%)
MVS_0304 - completeness (94.32%)
MVS_111021_LR
MVS_111021_LR - accuracy (84.23%)
MVS_111021_LR - completeness (91.93%)
MVS_Test
MVS_Test - accuracy (80.31%)
MVS_Test - completeness (91.41%)
NCCC
NCCC - accuracy (91.30%)
NCCC - completeness (95.41%)
new-patchmatchnet
new-patchmatchnet - accuracy (58.69%)
new-patchmatchnet - completeness (61.92%)
new_pmnet
new_pmnet - accuracy (48.81%)
new_pmnet - completeness (47.87%)
NR-MVSNet
NR-MVSNet - accuracy (82.75%)
NR-MVSNet - completeness (84.45%)
N_pmnet
N_pmnet - accuracy (47.23%)
N_pmnet - completeness (63.04%)
OMC-MVS
OMC-MVS - accuracy (91.68%)
OMC-MVS - completeness (86.15%)
OpenMVS
OpenMVS - accuracy (86.40%)
OpenMVS - completeness (89.20%)
OPM-MVS
OPM-MVS - accuracy (91.49%)
OPM-MVS - completeness (88.20%)
PatchMatch-RL
PatchMatch-RL - accuracy (73.22%)
PatchMatch-RL - completeness (74.02%)
PatchmatchNet
PatchmatchNet - accuracy (58.24%)
PatchmatchNet - completeness (81.91%)
PatchT
PatchT - accuracy (69.40%)
PatchT - completeness (83.23%)
PCF-MVS
PCF-MVS - accuracy (88.53%)
PCF-MVS - completeness (94.01%)
PEN-MVS
PEN-MVS - accuracy (88.78%)
PEN-MVS - completeness (74.00%)
PGM-MVS
PGM-MVS - accuracy (93.40%)
PGM-MVS - completeness (90.76%)
PHI-MVS
PHI-MVS - accuracy (89.03%)
PHI-MVS - completeness (94.24%)
PLC
PLC - accuracy (86.74%)
PLC - completeness (77.19%)
PM-MVS
PM-MVS - accuracy (81.18%)
PM-MVS - completeness (74.32%)
pm-mvs1
pm-mvs1 - accuracy (77.96%)
pm-mvs1 - completeness (81.77%)
PMMVS
PMMVS - accuracy (63.66%)
PMMVS - completeness (88.32%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (76.01%)
pmmvs-eth3d - completeness (75.81%)
PMMVS2
PMMVS2 - accuracy (40.01%)
PMMVS2 - completeness (35.81%)
pmmvs3
pmmvs3 - accuracy (62.55%)
pmmvs3 - completeness (65.03%)
pmmvs5
pmmvs5 - accuracy (68.03%)
pmmvs5 - completeness (82.45%)
pmmvs6
pmmvs6 - accuracy (80.38%)
pmmvs6 - completeness (78.00%)
pmnet_mix02
pmnet_mix02 - accuracy (60.32%)
pmnet_mix02 - completeness (71.24%)
PMVS
PMVS - accuracy (90.96%)
PMVS - completeness (42.44%)
PS-CasMVS
PS-CasMVS - accuracy (90.11%)
PS-CasMVS - completeness (75.18%)
PVSNet_Blended
PVSNet_Blended - accuracy (78.60%)
PVSNet_Blended - completeness (97.10%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (78.60%)
PVSNet_BlendedMVS - completeness (97.10%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (87.40%)
PVSNet_Blended_VisFu - completeness (94.74%)
QAPM
QAPM - accuracy (88.14%)
QAPM - completeness (92.79%)
RPMNet
RPMNet - accuracy (68.49%)
RPMNet - completeness (84.40%)
RPSCF
RPSCF - accuracy (93.40%)
RPSCF - completeness (65.75%)
SCA
SCA - accuracy (61.54%)
SCA - completeness (80.92%)
SD-MVS
SD-MVS - accuracy (93.02%)
SD-MVS - completeness (94.51%)
SED-MVS
SED-MVS - accuracy (93.37%)
SED-MVS - completeness (98.21%)
SF-MVS
SF-MVS - accuracy (92.47%)
SF-MVS - completeness (95.37%)
SMA-MVS
SMA-MVS - accuracy (94.62%)
SMA-MVS - completeness (95.77%)
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 (93.59%)
SteuartSystems-ACMMP - completeness (94.34%)
TAMVS
TAMVS - accuracy (57.75%)
TAMVS - completeness (78.82%)
TAPA-MVS
TAPA-MVS - accuracy (89.97%)
TAPA-MVS - completeness (80.97%)
TDRefinement
TDRefinement - accuracy (95.34%)
TDRefinement - completeness (66.06%)
test-mter
test-mter - accuracy (65.00%)
test-mter - completeness (92.05%)
test1
test1 - accuracy (80.37%)
test1 - completeness (83.73%)
test123
test123 - accuracy (1.62%)
test123 - completeness (0.26%)
testgi
testgi - accuracy (64.55%)
testgi - completeness (61.10%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (61.87%)
TESTMET0.1,1 - completeness (93.21%)
testmvs
testmvs - accuracy (1.68%)
testmvs - completeness (0.24%)
test_part1
test_part1 - accuracy (90.46%)
test_part1 - completeness (86.81%)
thisisatest0515
thisisatest0515 - accuracy (85.56%)
thisisatest0515 - completeness (82.08%)
thisisatest0530
thisisatest0530 - accuracy (84.20%)
thisisatest0530 - completeness (85.07%)
TinyColmap
TinyColmap - accuracy (81.12%)
TinyColmap - completeness (63.87%)
tpm
tpm - accuracy (63.47%)
tpm - completeness (89.45%)
tpm cat1
tpm cat1 - accuracy (63.95%)
tpm cat1 - completeness (89.49%)
tpmrst
tpmrst - accuracy (58.02%)
tpmrst - completeness (90.48%)
train_agg
train_agg - accuracy (89.04%)
train_agg - completeness (95.30%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (82.95%)
TranMVSNet+NR-MVSNet - completeness (82.46%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (79.61%)
TransMVSNet (Re) - completeness (74.69%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (93.59%)
TSAR-MVS + ACMM - completeness (93.75%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (87.80%)
TSAR-MVS + COLMAP - completeness (84.23%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (89.45%)
TSAR-MVS + GP. - completeness (95.66%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (93.01%)
TSAR-MVS + MP. - completeness (94.66%)
tttt0517
tttt0517 - accuracy (84.80%)
tttt0517 - completeness (84.58%)
UA-Net
UA-Net - accuracy (95.58%)
UA-Net - completeness (71.68%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (86.43%)
UGNet - completeness (91.02%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (84.00%)
UniMVSNet (Re) - completeness (85.81%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (82.74%)
UniMVSNet_ETH3D - completeness (82.44%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (83.02%)
UniMVSNet_NR-MVSNet - completeness (84.95%)
USDC
USDC - accuracy (77.45%)
USDC - completeness (73.42%)
Vis-MVSNet
Vis-MVSNet - accuracy (90.26%)
Vis-MVSNet - completeness (85.99%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (71.12%)
Vis-MVSNet (Re-imp) - completeness (83.31%)
WR-MVS_H
WR-MVS_H - accuracy (90.83%)
WR-MVS_H - completeness (72.73%)
X-MVS
X-MVS - accuracy (93.55%)
X-MVS - completeness (91.20%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (92.47%)
xxxxxxxxxxxxxcwj - completeness (95.37%)
zzz-MVS
zzz-MVS - accuracy (91.94%)
zzz-MVS - completeness (93.19%)
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
:
-5.32 to 42.78
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
:
33.3
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