+
−
⇧
i
D
T
terrains (high-res multi-view) - Tolerance 1cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (79.14%)
3Dnovator - completeness (81.34%)
3Dnovator+
3Dnovator+ - accuracy (86.28%)
3Dnovator+ - completeness (80.40%)
ACMH
ACMH - accuracy (82.46%)
ACMH - completeness (70.00%)
ACMH+
ACMH+ - accuracy (83.56%)
ACMH+ - completeness (70.05%)
ACMM
ACMM - accuracy (87.22%)
ACMM - completeness (75.91%)
ACMMP
ACMMP - accuracy (88.62%)
ACMMP - completeness (83.17%)
ACMMPR
ACMMPR - accuracy (89.13%)
ACMMPR - completeness (84.05%)
ACMMP_NAP
ACMMP_NAP - accuracy (89.58%)
ACMMP_NAP - completeness (87.72%)
ACMP
ACMP - accuracy (86.84%)
ACMP - completeness (81.91%)
AdaColmap
AdaColmap - accuracy (79.27%)
AdaColmap - completeness (76.69%)
ADS-MVSNet
ADS-MVSNet - accuracy (34.64%)
ADS-MVSNet - completeness (61.07%)
ambc
ambc - accuracy (78.85%)
ambc - completeness (58.89%)
Anonymous20231206
Anonymous20231206 - accuracy (46.94%)
Anonymous20231206 - completeness (65.23%)
Anonymous202405211
Anonymous202405211 - accuracy (64.32%)
Anonymous202405211 - completeness (83.17%)
anonymousdsp
anonymousdsp - accuracy (88.81%)
anonymousdsp - completeness (76.66%)
APD-MVS
APD-MVS - accuracy (87.77%)
APD-MVS - completeness (88.84%)
APDe-MVS
APDe-MVS - accuracy (88.95%)
APDe-MVS - completeness (91.49%)
baseline1
baseline1 - accuracy (54.54%)
baseline1 - completeness (73.39%)
baseline2
baseline2 - accuracy (58.28%)
baseline2 - completeness (82.06%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (68.58%)
Baseline_NR-MVSNet - completeness (70.60%)
CANet
CANet - accuracy (77.40%)
CANet - completeness (88.00%)
CANet_DTU
CANet_DTU - accuracy (70.19%)
CANet_DTU - completeness (81.29%)
canonicalmvs
canonicalmvs - accuracy (76.35%)
canonicalmvs - completeness (85.25%)
casdiffmvs
casdiffmvs - accuracy (69.14%)
casdiffmvs - completeness (87.99%)
CDPH-MVS
CDPH-MVS - accuracy (83.57%)
CDPH-MVS - completeness (86.67%)
CDS-MVSNet
CDS-MVSNet - accuracy (54.68%)
CDS-MVSNet - completeness (73.28%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (61.99%)
CHOSEN 1792x2688 - completeness (91.53%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (48.62%)
CHOSEN 280x420 - completeness (73.32%)
CLD-MVS
CLD-MVS - accuracy (69.63%)
CLD-MVS - completeness (69.87%)
CMPMVS
CMPMVS - accuracy (77.85%)
CMPMVS - completeness (62.74%)
CNLPA
CNLPA - accuracy (82.40%)
CNLPA - completeness (71.68%)
CNVR-MVS
CNVR-MVS - accuracy (85.68%)
CNVR-MVS - completeness (92.93%)
COLMAP_ROB
COLMAP_ROB - accuracy (88.61%)
COLMAP_ROB - completeness (50.82%)
CostFormer
CostFormer - accuracy (58.98%)
CostFormer - completeness (87.09%)
CP-MVS
CP-MVS - accuracy (89.14%)
CP-MVS - completeness (84.89%)
CP-MVSNet
CP-MVSNet - accuracy (78.65%)
CP-MVSNet - completeness (58.90%)
CPTT-MVS
CPTT-MVS - accuracy (87.74%)
CPTT-MVS - completeness (84.31%)
CR-MVSNet
CR-MVSNet - accuracy (57.07%)
CR-MVSNet - completeness (69.47%)
CS-MVS
CS-MVS - accuracy (69.33%)
CS-MVS - completeness (88.45%)
CSCG
CSCG - accuracy (86.84%)
CSCG - completeness (89.13%)
CVMVSNet
CVMVSNet - accuracy (72.97%)
CVMVSNet - completeness (62.85%)
DCV-MVSNet
DCV-MVSNet - accuracy (72.37%)
DCV-MVSNet - completeness (79.95%)
DeepC-MVS
DeepC-MVS - accuracy (88.37%)
DeepC-MVS - completeness (87.94%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (86.33%)
DeepC-MVS_fast - completeness (86.10%)
DeepMVS_CX
DeepMVS_CX - accuracy (25.07%)
DeepMVS_CX - completeness (14.51%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (87.34%)
DeepPCF-MVS - completeness (89.49%)
DELS-MVS
DELS-MVS - accuracy (73.20%)
DELS-MVS - completeness (91.95%)
diffmvs
diffmvs - accuracy (70.02%)
diffmvs - completeness (87.70%)
DPE-MVS
DPE-MVS - accuracy (89.01%)
DPE-MVS - completeness (92.19%)
DPM-MVS
DPM-MVS - accuracy (81.74%)
DPM-MVS - completeness (85.71%)
dps
dps - accuracy (53.41%)
dps - completeness (68.86%)
DTE-MVSNet
DTE-MVSNet - accuracy (75.98%)
DTE-MVSNet - completeness (55.23%)
DU-MVS
DU-MVS - accuracy (69.54%)
DU-MVS - completeness (71.94%)
DVP-MVS
DVP-MVS - accuracy (88.09%)
DVP-MVS - completeness (94.17%)
E-PMN
E-PMN - accuracy (30.79%)
E-PMN - completeness (14.30%)
Effi-MVS+
Effi-MVS+ - accuracy (74.09%)
Effi-MVS+ - completeness (83.93%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (74.05%)
Effi-MVS+-dtu - completeness (76.91%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (76.98%)
EG-PatchMatch MVS - completeness (71.39%)
EIA-MVS
EIA-MVS - accuracy (65.82%)
EIA-MVS - completeness (86.60%)
EMVS
EMVS - accuracy (29.87%)
EMVS - completeness (12.43%)
EPMVS
EPMVS - accuracy (37.16%)
EPMVS - completeness (70.08%)
EPNet
EPNet - accuracy (73.73%)
EPNet - completeness (83.87%)
EPNet_dtu
EPNet_dtu - accuracy (63.86%)
EPNet_dtu - completeness (68.71%)
EPP-MVSNet
EPP-MVSNet - accuracy (77.94%)
EPP-MVSNet - completeness (81.41%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (66.74%)
ET-MVSNet_ETH3D - completeness (82.35%)
ETV-MVS
ETV-MVS - accuracy (71.03%)
ETV-MVS - completeness (89.33%)
EU-MVSNet
EU-MVSNet - accuracy (71.96%)
EU-MVSNet - completeness (57.01%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (72.36%)
Fast-Effi-MVS+ - completeness (79.34%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (63.09%)
Fast-Effi-MVS+-dtu - completeness (80.37%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (59.77%)
FC-MVSNet-test - completeness (44.03%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (68.25%)
FC-MVSNet-train - completeness (75.76%)
FMVSNet1
FMVSNet1 - accuracy (68.83%)
FMVSNet1 - completeness (70.18%)
FMVSNet2
FMVSNet2 - accuracy (66.56%)
FMVSNet2 - completeness (73.03%)
FMVSNet3
FMVSNet3 - accuracy (65.53%)
FMVSNet3 - completeness (73.86%)
FMVSNet5
FMVSNet5 - accuracy (45.77%)
FMVSNet5 - completeness (56.46%)
FPMVS
FPMVS - accuracy (78.73%)
FPMVS - completeness (37.75%)
GA-MVS
GA-MVS - accuracy (64.22%)
GA-MVS - completeness (78.60%)
GBi-Net
GBi-Net - accuracy (66.56%)
GBi-Net - completeness (73.03%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (42.46%)
GG-mvs-BLEND - completeness (86.62%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (51.57%)
gg-mvs-nofinetune - completeness (80.68%)
Gipuma
Gipuma - accuracy (69.96%)
Gipuma - completeness (19.06%)
gm-plane-assit
gm-plane-assit - accuracy (48.13%)
gm-plane-assit - completeness (81.12%)
HFP-MVS
HFP-MVS - accuracy (89.10%)
HFP-MVS - completeness (84.84%)
HPM-MVS++
HPM-MVS++ - accuracy (86.00%)
HPM-MVS++ - completeness (88.97%)
HQP-MVS
HQP-MVS - accuracy (85.50%)
HQP-MVS - completeness (86.94%)
HyFIR lowres test
HyFIR lowres test - accuracy (61.11%)
HyFIR lowres test - completeness (85.70%)
IB-MVS
IB-MVS - accuracy (72.50%)
IB-MVS - completeness (85.59%)
IS_MVSNet
IS_MVSNet - accuracy (71.76%)
IS_MVSNet - completeness (77.33%)
IterMVS
IterMVS - accuracy (63.81%)
IterMVS - completeness (75.23%)
IterMVS-LS
IterMVS-LS - accuracy (74.95%)
IterMVS-LS - completeness (76.61%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (69.83%)
IterMVS-SCA-FT - completeness (72.25%)
LGP-MVS_train
LGP-MVS_train - accuracy (87.37%)
LGP-MVS_train - completeness (81.21%)
LS3D
LS3D - accuracy (85.70%)
LS3D - completeness (58.42%)
LTVRE_ROB
LTVRE_ROB - accuracy (90.72%)
LTVRE_ROB - completeness (55.45%)
MAR-MVS
MAR-MVS - accuracy (78.67%)
MAR-MVS - completeness (81.44%)
MCST-MVS
MCST-MVS - accuracy (81.85%)
MCST-MVS - completeness (93.51%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (62.08%)
MDA-MVSNet-bldmvs - completeness (51.39%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (50.01%)
MDTV_nov1_ep13 - completeness (70.62%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (55.13%)
MDTV_nov1_ep13_2view - completeness (63.86%)
MIMVSNet
MIMVSNet - accuracy (43.96%)
MIMVSNet - completeness (64.07%)
MIMVSNet1
MIMVSNet1 - accuracy (52.38%)
MIMVSNet1 - completeness (44.92%)
MP-MVS
MP-MVS - accuracy (88.59%)
MP-MVS - completeness (87.53%)
MS-PatchMatch
MS-PatchMatch - accuracy (64.56%)
MS-PatchMatch - completeness (75.17%)
MSDG
MSDG - accuracy (71.93%)
MSDG - completeness (64.41%)
MSLP-MVS++
MSLP-MVS++ - accuracy (87.56%)
MSLP-MVS++ - completeness (76.08%)
MSP-MVS
MSP-MVS - accuracy (85.42%)
MSP-MVS - completeness (93.75%)
MVE
MVE - accuracy (40.37%)
MVE - completeness (18.09%)
MVS-HIRNet
MVS-HIRNet - accuracy (41.95%)
MVS-HIRNet - completeness (61.80%)
MVSTER
MVSTER - accuracy (70.23%)
MVSTER - completeness (82.04%)
MVS_0304
MVS_0304 - accuracy (80.27%)
MVS_0304 - completeness (87.44%)
MVS_111021_LR
MVS_111021_LR - accuracy (75.29%)
MVS_111021_LR - completeness (81.53%)
MVS_Test
MVS_Test - accuracy (69.27%)
MVS_Test - completeness (85.63%)
NCCC
NCCC - accuracy (85.30%)
NCCC - completeness (90.19%)
new-patchmatchnet
new-patchmatchnet - accuracy (41.32%)
new-patchmatchnet - completeness (49.74%)
new_pmnet
new_pmnet - accuracy (31.41%)
new_pmnet - completeness (30.93%)
NR-MVSNet
NR-MVSNet - accuracy (69.49%)
NR-MVSNet - completeness (71.89%)
N_pmnet
N_pmnet - accuracy (29.86%)
N_pmnet - completeness (49.35%)
OMC-MVS
OMC-MVS - accuracy (87.10%)
OMC-MVS - completeness (73.42%)
OpenMVS
OpenMVS - accuracy (77.39%)
OpenMVS - completeness (80.44%)
OPM-MVS
OPM-MVS - accuracy (85.58%)
OPM-MVS - completeness (82.25%)
PatchMatch-RL
PatchMatch-RL - accuracy (61.44%)
PatchMatch-RL - completeness (58.64%)
PatchmatchNet
PatchmatchNet - accuracy (44.37%)
PatchmatchNet - completeness (70.87%)
PatchT
PatchT - accuracy (57.07%)
PatchT - completeness (69.47%)
PCF-MVS
PCF-MVS - accuracy (81.13%)
PCF-MVS - completeness (85.83%)
PEN-MVS
PEN-MVS - accuracy (77.14%)
PEN-MVS - completeness (58.83%)
PGM-MVS
PGM-MVS - accuracy (88.50%)
PGM-MVS - completeness (82.93%)
PHI-MVS
PHI-MVS - accuracy (81.99%)
PHI-MVS - completeness (86.46%)
PLC
PLC - accuracy (79.80%)
PLC - completeness (64.10%)
PM-MVS
PM-MVS - accuracy (69.83%)
PM-MVS - completeness (61.34%)
pm-mvs1
pm-mvs1 - accuracy (62.65%)
pm-mvs1 - completeness (70.20%)
PMMVS
PMMVS - accuracy (49.19%)
PMMVS - completeness (79.48%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (63.38%)
pmmvs-eth3d - completeness (66.12%)
PMMVS2
PMMVS2 - accuracy (27.28%)
PMMVS2 - completeness (21.56%)
pmmvs3
pmmvs3 - accuracy (49.29%)
pmmvs3 - completeness (54.98%)
pmmvs5
pmmvs5 - accuracy (52.18%)
pmmvs5 - completeness (71.92%)
pmmvs6
pmmvs6 - accuracy (65.12%)
pmmvs6 - completeness (66.24%)
pmnet_mix02
pmnet_mix02 - accuracy (43.05%)
pmnet_mix02 - completeness (60.58%)
PMVS
PMVS - accuracy (86.00%)
PMVS - completeness (35.20%)
PS-CasMVS
PS-CasMVS - accuracy (79.19%)
PS-CasMVS - completeness (58.63%)
PVSNet_Blended
PVSNet_Blended - accuracy (66.86%)
PVSNet_Blended - completeness (89.39%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (66.86%)
PVSNet_BlendedMVS - completeness (89.39%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (79.43%)
PVSNet_Blended_VisFu - completeness (87.44%)
QAPM
QAPM - accuracy (78.96%)
QAPM - completeness (85.59%)
RPMNet
RPMNet - accuracy (55.43%)
RPMNet - completeness (69.00%)
RPSCF
RPSCF - accuracy (86.64%)
RPSCF - completeness (50.63%)
SCA
SCA - accuracy (48.03%)
SCA - completeness (68.90%)
SD-MVS
SD-MVS - accuracy (89.04%)
SD-MVS - completeness (81.73%)
SED-MVS
SED-MVS - accuracy (87.63%)
SED-MVS - completeness (94.46%)
SF-MVS
SF-MVS - accuracy (87.49%)
SF-MVS - completeness (88.22%)
SMA-MVS
SMA-MVS - accuracy (89.83%)
SMA-MVS - completeness (89.42%)
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 (88.30%)
SteuartSystems-ACMMP - completeness (88.74%)
TAMVS
TAMVS - accuracy (41.82%)
TAMVS - completeness (66.54%)
TAPA-MVS
TAPA-MVS - accuracy (81.82%)
TAPA-MVS - completeness (68.00%)
TDRefinement
TDRefinement - accuracy (91.56%)
TDRefinement - completeness (52.12%)
test-mter
test-mter - accuracy (52.03%)
test-mter - completeness (82.12%)
test1
test1 - accuracy (66.56%)
test1 - completeness (73.03%)
test123
test123 - accuracy (0.88%)
test123 - completeness (0.03%)
testgi
testgi - accuracy (49.27%)
testgi - completeness (42.23%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (48.84%)
TESTMET0.1,1 - completeness (84.62%)
testmvs
testmvs - accuracy (0.77%)
testmvs - completeness (0.03%)
test_part1
test_part1 - accuracy (80.63%)
test_part1 - completeness (80.54%)
thisisatest0515
thisisatest0515 - accuracy (75.66%)
thisisatest0515 - completeness (71.59%)
thisisatest0530
thisisatest0530 - accuracy (74.14%)
thisisatest0530 - completeness (74.00%)
TinyColmap
TinyColmap - accuracy (73.02%)
TinyColmap - completeness (52.42%)
tpm
tpm - accuracy (47.01%)
tpm - completeness (83.39%)
tpm cat1
tpm cat1 - accuracy (53.24%)
tpm cat1 - completeness (81.81%)
tpmrst
tpmrst - accuracy (43.75%)
tpmrst - completeness (84.73%)
train_agg
train_agg - accuracy (82.73%)
train_agg - completeness (88.69%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (69.48%)
TranMVSNet+NR-MVSNet - completeness (70.31%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (64.84%)
TransMVSNet (Re) - completeness (65.47%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (89.95%)
TSAR-MVS + ACMM - completeness (81.67%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (81.61%)
TSAR-MVS + COLMAP - completeness (71.74%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (81.47%)
TSAR-MVS + GP. - completeness (86.62%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (88.67%)
TSAR-MVS + MP. - completeness (81.97%)
tttt0517
tttt0517 - accuracy (74.89%)
tttt0517 - completeness (73.46%)
UA-Net
UA-Net - accuracy (89.36%)
UA-Net - completeness (56.51%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (76.01%)
UGNet - completeness (80.70%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (71.08%)
UniMVSNet (Re) - completeness (72.69%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (68.40%)
UniMVSNet_ETH3D - completeness (69.17%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (69.54%)
UniMVSNet_NR-MVSNet - completeness (71.94%)
USDC
USDC - accuracy (68.21%)
USDC - completeness (61.75%)
Vis-MVSNet
Vis-MVSNet - accuracy (81.21%)
Vis-MVSNet - completeness (77.12%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (54.91%)
Vis-MVSNet (Re-imp) - completeness (63.65%)
WR-MVS_H
WR-MVS_H - accuracy (80.89%)
WR-MVS_H - completeness (55.54%)
X-MVS
X-MVS - accuracy (88.73%)
X-MVS - completeness (83.16%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (87.49%)
xxxxxxxxxxxxxcwj - completeness (88.22%)
zzz-MVS
zzz-MVS - accuracy (86.49%)
zzz-MVS - completeness (86.11%)
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
:
-24.52 to 39.39
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
:
55.6
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