+
−
⇧
i
D
T
relief (high-res multi-view) - Tolerance 1cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (76.86%)
3Dnovator - completeness (71.29%)
3Dnovator+
3Dnovator+ - accuracy (87.39%)
3Dnovator+ - completeness (68.51%)
ACMH
ACMH - accuracy (86.27%)
ACMH - completeness (60.88%)
ACMH+
ACMH+ - accuracy (89.17%)
ACMH+ - completeness (57.45%)
ACMM
ACMM - accuracy (91.38%)
ACMM - completeness (64.74%)
ACMMP
ACMMP - accuracy (91.30%)
ACMMP - completeness (66.58%)
ACMMPR
ACMMPR - accuracy (90.66%)
ACMMPR - completeness (68.93%)
ACMMP_NAP
ACMMP_NAP - accuracy (88.61%)
ACMMP_NAP - completeness (73.00%)
ACMP
ACMP - accuracy (90.49%)
ACMP - completeness (63.61%)
AdaColmap
AdaColmap - accuracy (85.37%)
AdaColmap - completeness (67.41%)
ADS-MVSNet
ADS-MVSNet - accuracy (44.35%)
ADS-MVSNet - completeness (53.13%)
ambc
ambc - accuracy (80.24%)
ambc - completeness (55.63%)
Anonymous20231206
Anonymous20231206 - accuracy (59.55%)
Anonymous20231206 - completeness (54.00%)
Anonymous202405211
Anonymous202405211 - accuracy (73.54%)
Anonymous202405211 - completeness (65.28%)
anonymousdsp
anonymousdsp - accuracy (88.94%)
anonymousdsp - completeness (53.96%)
APD-MVS
APD-MVS - accuracy (86.08%)
APD-MVS - completeness (69.47%)
APDe-MVS
APDe-MVS - accuracy (85.99%)
APDe-MVS - completeness (71.85%)
baseline1
baseline1 - accuracy (65.05%)
baseline1 - completeness (69.38%)
baseline2
baseline2 - accuracy (64.63%)
baseline2 - completeness (66.65%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (83.47%)
Baseline_NR-MVSNet - completeness (57.53%)
CANet
CANet - accuracy (79.89%)
CANet - completeness (69.31%)
CANet_DTU
CANet_DTU - accuracy (71.87%)
CANet_DTU - completeness (64.98%)
canonicalmvs
canonicalmvs - accuracy (76.77%)
canonicalmvs - completeness (67.56%)
casdiffmvs
casdiffmvs - accuracy (70.74%)
casdiffmvs - completeness (70.17%)
CDPH-MVS
CDPH-MVS - accuracy (84.09%)
CDPH-MVS - completeness (69.70%)
CDS-MVSNet
CDS-MVSNet - accuracy (72.49%)
CDS-MVSNet - completeness (61.77%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (59.28%)
CHOSEN 1792x2688 - completeness (77.29%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (59.16%)
CHOSEN 280x420 - completeness (54.46%)
CLD-MVS
CLD-MVS - accuracy (81.22%)
CLD-MVS - completeness (72.79%)
CMPMVS
CMPMVS - accuracy (70.15%)
CMPMVS - completeness (56.50%)
CNLPA
CNLPA - accuracy (85.28%)
CNLPA - completeness (58.89%)
CNVR-MVS
CNVR-MVS - accuracy (85.10%)
CNVR-MVS - completeness (75.88%)
COLMAP_ROB
COLMAP_ROB - accuracy (92.31%)
COLMAP_ROB - completeness (51.02%)
CostFormer
CostFormer - accuracy (54.92%)
CostFormer - completeness (67.03%)
CP-MVS
CP-MVS - accuracy (91.74%)
CP-MVS - completeness (67.33%)
CP-MVSNet
CP-MVSNet - accuracy (90.86%)
CP-MVSNet - completeness (43.37%)
CPTT-MVS
CPTT-MVS - accuracy (90.07%)
CPTT-MVS - completeness (61.83%)
CR-MVSNet
CR-MVSNet - accuracy (59.15%)
CR-MVSNet - completeness (58.80%)
CS-MVS
CS-MVS - accuracy (77.69%)
CS-MVS - completeness (69.85%)
CSCG
CSCG - accuracy (81.01%)
CSCG - completeness (74.24%)
CVMVSNet
CVMVSNet - accuracy (69.14%)
CVMVSNet - completeness (47.77%)
DCV-MVSNet
DCV-MVSNet - accuracy (75.20%)
DCV-MVSNet - completeness (64.41%)
DeepC-MVS
DeepC-MVS - accuracy (87.81%)
DeepC-MVS - completeness (71.99%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (85.40%)
DeepC-MVS_fast - completeness (71.64%)
DeepMVS_CX
DeepMVS_CX - accuracy (13.75%)
DeepMVS_CX - completeness (9.74%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (84.80%)
DeepPCF-MVS - completeness (72.79%)
DELS-MVS
DELS-MVS - accuracy (73.71%)
DELS-MVS - completeness (74.93%)
diffmvs
diffmvs - accuracy (68.04%)
diffmvs - completeness (66.57%)
DPE-MVS
DPE-MVS - accuracy (85.40%)
DPE-MVS - completeness (72.99%)
DPM-MVS
DPM-MVS - accuracy (74.15%)
DPM-MVS - completeness (79.35%)
dps
dps - accuracy (57.71%)
dps - completeness (60.45%)
DTE-MVSNet
DTE-MVSNet - accuracy (89.73%)
DTE-MVSNet - completeness (45.58%)
DU-MVS
DU-MVS - accuracy (83.47%)
DU-MVS - completeness (57.53%)
DVP-MVS
DVP-MVS - accuracy (84.62%)
DVP-MVS - completeness (75.84%)
E-PMN
E-PMN - accuracy (70.78%)
E-PMN - completeness (8.98%)
Effi-MVS+
Effi-MVS+ - accuracy (73.58%)
Effi-MVS+ - completeness (67.45%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (80.96%)
Effi-MVS+-dtu - completeness (58.72%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (80.29%)
EG-PatchMatch MVS - completeness (64.79%)
EIA-MVS
EIA-MVS - accuracy (78.00%)
EIA-MVS - completeness (65.01%)
EMVS
EMVS - accuracy (70.26%)
EMVS - completeness (8.15%)
EPMVS
EPMVS - accuracy (44.75%)
EPMVS - completeness (61.25%)
EPNet
EPNet - accuracy (76.08%)
EPNet - completeness (68.65%)
EPNet_dtu
EPNet_dtu - accuracy (68.60%)
EPNet_dtu - completeness (58.19%)
EPP-MVSNet
EPP-MVSNet - accuracy (83.41%)
EPP-MVSNet - completeness (61.37%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (74.72%)
ET-MVSNet_ETH3D - completeness (60.75%)
ETV-MVS
ETV-MVS - accuracy (80.19%)
ETV-MVS - completeness (68.00%)
EU-MVSNet
EU-MVSNet - accuracy (70.06%)
EU-MVSNet - completeness (41.22%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (78.46%)
Fast-Effi-MVS+ - completeness (65.31%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (72.03%)
Fast-Effi-MVS+-dtu - completeness (62.90%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (82.33%)
FC-MVSNet-test - completeness (41.40%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (77.61%)
FC-MVSNet-train - completeness (61.58%)
FMVSNet1
FMVSNet1 - accuracy (72.33%)
FMVSNet1 - completeness (64.25%)
FMVSNet2
FMVSNet2 - accuracy (66.91%)
FMVSNet2 - completeness (67.23%)
FMVSNet3
FMVSNet3 - accuracy (62.88%)
FMVSNet3 - completeness (68.29%)
FMVSNet5
FMVSNet5 - accuracy (58.27%)
FMVSNet5 - completeness (56.82%)
FPMVS
FPMVS - accuracy (83.41%)
FPMVS - completeness (35.11%)
GA-MVS
GA-MVS - accuracy (64.47%)
GA-MVS - completeness (67.45%)
GBi-Net
GBi-Net - accuracy (72.33%)
GBi-Net - completeness (64.25%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (48.19%)
GG-mvs-BLEND - completeness (63.83%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (62.51%)
gg-mvs-nofinetune - completeness (70.50%)
Gipuma
Gipuma - accuracy (87.90%)
Gipuma - completeness (34.32%)
gm-plane-assit
gm-plane-assit - accuracy (58.77%)
gm-plane-assit - completeness (72.93%)
HFP-MVS
HFP-MVS - accuracy (89.08%)
HFP-MVS - completeness (70.49%)
HPM-MVS++
HPM-MVS++ - accuracy (84.15%)
HPM-MVS++ - completeness (73.99%)
HQP-MVS
HQP-MVS - accuracy (79.42%)
HQP-MVS - completeness (72.90%)
HyFIR lowres test
HyFIR lowres test - accuracy (62.77%)
HyFIR lowres test - completeness (68.39%)
IB-MVS
IB-MVS - accuracy (76.26%)
IB-MVS - completeness (59.27%)
IS_MVSNet
IS_MVSNet - accuracy (81.25%)
IS_MVSNet - completeness (63.43%)
IterMVS
IterMVS - accuracy (64.81%)
IterMVS - completeness (60.22%)
IterMVS-LS
IterMVS-LS - accuracy (69.46%)
IterMVS-LS - completeness (61.82%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (70.24%)
IterMVS-SCA-FT - completeness (56.25%)
LGP-MVS_train
LGP-MVS_train - accuracy (90.70%)
LGP-MVS_train - completeness (65.39%)
LS3D
LS3D - accuracy (86.30%)
LS3D - completeness (57.17%)
LTVRE_ROB
LTVRE_ROB - accuracy (92.58%)
LTVRE_ROB - completeness (46.92%)
MAR-MVS
MAR-MVS - accuracy (78.39%)
MAR-MVS - completeness (72.67%)
MCST-MVS
MCST-MVS - accuracy (78.51%)
MCST-MVS - completeness (77.49%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (86.67%)
MDA-MVSNet-bldmvs - completeness (35.59%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (56.20%)
MDTV_nov1_ep13 - completeness (60.07%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (65.95%)
MDTV_nov1_ep13_2view - completeness (53.36%)
MIMVSNet
MIMVSNet - accuracy (55.81%)
MIMVSNet - completeness (61.97%)
MIMVSNet1
MIMVSNet1 - accuracy (73.98%)
MIMVSNet1 - completeness (43.83%)
MP-MVS
MP-MVS - accuracy (90.14%)
MP-MVS - completeness (68.41%)
MS-PatchMatch
MS-PatchMatch - accuracy (64.25%)
MS-PatchMatch - completeness (72.89%)
MSDG
MSDG - accuracy (76.72%)
MSDG - completeness (62.13%)
MSLP-MVS++
MSLP-MVS++ - accuracy (88.10%)
MSLP-MVS++ - completeness (62.04%)
MSP-MVS
MSP-MVS - accuracy (81.15%)
MSP-MVS - completeness (75.48%)
MVE
MVE - accuracy (47.26%)
MVE - completeness (12.78%)
MVS-HIRNet
MVS-HIRNet - accuracy (47.97%)
MVS-HIRNet - completeness (53.92%)
MVSTER
MVSTER - accuracy (67.29%)
MVSTER - completeness (69.13%)
MVS_0304
MVS_0304 - accuracy (81.20%)
MVS_0304 - completeness (71.09%)
MVS_111021_LR
MVS_111021_LR - accuracy (81.94%)
MVS_111021_LR - completeness (61.46%)
MVS_Test
MVS_Test - accuracy (66.95%)
MVS_Test - completeness (70.27%)
NCCC
NCCC - accuracy (85.62%)
NCCC - completeness (73.56%)
new-patchmatchnet
new-patchmatchnet - accuracy (63.54%)
new-patchmatchnet - completeness (41.32%)
new_pmnet
new_pmnet - accuracy (49.21%)
new_pmnet - completeness (30.57%)
NR-MVSNet
NR-MVSNet - accuracy (74.52%)
NR-MVSNet - completeness (63.52%)
N_pmnet
N_pmnet - accuracy (50.17%)
N_pmnet - completeness (44.59%)
OMC-MVS
OMC-MVS - accuracy (87.25%)
OMC-MVS - completeness (60.28%)
OpenMVS
OpenMVS - accuracy (72.20%)
OpenMVS - completeness (68.28%)
OPM-MVS
OPM-MVS - accuracy (87.20%)
OPM-MVS - completeness (69.92%)
PatchMatch-RL
PatchMatch-RL - accuracy (73.73%)
PatchMatch-RL - completeness (51.99%)
PatchmatchNet
PatchmatchNet - accuracy (53.80%)
PatchmatchNet - completeness (60.29%)
PatchT
PatchT - accuracy (59.15%)
PatchT - completeness (58.80%)
PCF-MVS
PCF-MVS - accuracy (78.61%)
PCF-MVS - completeness (65.64%)
PEN-MVS
PEN-MVS - accuracy (89.83%)
PEN-MVS - completeness (45.64%)
PGM-MVS
PGM-MVS - accuracy (90.46%)
PGM-MVS - completeness (68.94%)
PHI-MVS
PHI-MVS - accuracy (81.10%)
PHI-MVS - completeness (70.68%)
PLC
PLC - accuracy (84.73%)
PLC - completeness (57.13%)
PM-MVS
PM-MVS - accuracy (76.30%)
PM-MVS - completeness (44.33%)
pm-mvs1
pm-mvs1 - accuracy (72.93%)
pm-mvs1 - completeness (60.03%)
PMMVS
PMMVS - accuracy (54.13%)
PMMVS - completeness (65.88%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (70.44%)
pmmvs-eth3d - completeness (55.13%)
PMMVS2
PMMVS2 - accuracy (57.24%)
PMMVS2 - completeness (19.26%)
pmmvs3
pmmvs3 - accuracy (58.43%)
pmmvs3 - completeness (44.82%)
pmmvs5
pmmvs5 - accuracy (57.53%)
pmmvs5 - completeness (59.05%)
pmmvs6
pmmvs6 - accuracy (76.43%)
pmmvs6 - completeness (55.94%)
pmnet_mix02
pmnet_mix02 - accuracy (54.53%)
pmnet_mix02 - completeness (51.50%)
PMVS
PMVS - accuracy (93.02%)
PMVS - completeness (34.92%)
PS-CasMVS
PS-CasMVS - accuracy (91.02%)
PS-CasMVS - completeness (43.28%)
PVSNet_Blended
PVSNet_Blended - accuracy (71.49%)
PVSNet_Blended - completeness (69.46%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (71.49%)
PVSNet_BlendedMVS - completeness (69.46%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (79.35%)
PVSNet_Blended_VisFu - completeness (67.99%)
QAPM
QAPM - accuracy (73.00%)
QAPM - completeness (72.20%)
RPMNet
RPMNet - accuracy (57.30%)
RPMNet - completeness (50.85%)
RPSCF
RPSCF - accuracy (88.25%)
RPSCF - completeness (41.14%)
SCA
SCA - accuracy (56.39%)
SCA - completeness (60.37%)
SD-MVS
SD-MVS - accuracy (88.66%)
SD-MVS - completeness (65.63%)
SED-MVS
SED-MVS - accuracy (85.12%)
SED-MVS - completeness (76.19%)
SF-MVS
SF-MVS - accuracy (83.28%)
SF-MVS - completeness (71.81%)
SMA-MVS
SMA-MVS - accuracy (88.10%)
SMA-MVS - completeness (74.96%)
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 (90.25%)
SteuartSystems-ACMMP - completeness (72.78%)
TAMVS
TAMVS - accuracy (59.50%)
TAMVS - completeness (56.85%)
TAPA-MVS
TAPA-MVS - accuracy (83.21%)
TAPA-MVS - completeness (58.00%)
TDRefinement
TDRefinement - accuracy (94.71%)
TDRefinement - completeness (48.60%)
test-mter
test-mter - accuracy (54.55%)
test-mter - completeness (60.30%)
test1
test1 - accuracy (72.33%)
test1 - completeness (64.25%)
test123
test123 - accuracy (0.68%)
test123 - completeness (0.00%)
testgi
testgi - accuracy (63.01%)
testgi - completeness (49.28%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (51.78%)
TESTMET0.1,1 - completeness (62.91%)
testmvs
testmvs - accuracy (0.62%)
testmvs - completeness (0.01%)
test_part1
test_part1 - accuracy (82.20%)
test_part1 - completeness (63.09%)
thisisatest0515
thisisatest0515 - accuracy (75.69%)
thisisatest0515 - completeness (58.75%)
thisisatest0530
thisisatest0530 - accuracy (73.07%)
thisisatest0530 - completeness (63.00%)
TinyColmap
TinyColmap - accuracy (80.66%)
TinyColmap - completeness (50.33%)
tmp_tt
tmp_tt - accuracy (20.02%)
tmp_tt - completeness (12.88%)
tpm
tpm - accuracy (48.33%)
tpm - completeness (61.46%)
tpm cat1
tpm cat1 - accuracy (51.31%)
tpm cat1 - completeness (61.39%)
tpmrst
tpmrst - accuracy (42.00%)
tpmrst - completeness (62.19%)
train_agg
train_agg - accuracy (83.70%)
train_agg - completeness (71.96%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (82.74%)
TranMVSNet+NR-MVSNet - completeness (59.34%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (72.73%)
TransMVSNet (Re) - completeness (63.05%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (88.19%)
TSAR-MVS + ACMM - completeness (65.33%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (80.30%)
TSAR-MVS + COLMAP - completeness (61.26%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (83.65%)
TSAR-MVS + GP. - completeness (65.49%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (86.64%)
TSAR-MVS + MP. - completeness (69.11%)
tttt0517
tttt0517 - accuracy (73.84%)
tttt0517 - completeness (62.58%)
UA-Net
UA-Net - accuracy (92.21%)
UA-Net - completeness (54.11%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (79.39%)
UGNet - completeness (59.85%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (82.50%)
UniMVSNet (Re) - completeness (57.56%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (85.14%)
UniMVSNet_ETH3D - completeness (54.18%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (81.07%)
UniMVSNet_NR-MVSNet - completeness (59.59%)
USDC
USDC - accuracy (73.73%)
USDC - completeness (55.35%)
Vis-MVSNet
Vis-MVSNet - accuracy (82.92%)
Vis-MVSNet - completeness (62.12%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (75.30%)
Vis-MVSNet (Re-imp) - completeness (54.09%)
WR-MVS_H
WR-MVS_H - accuracy (90.44%)
WR-MVS_H - completeness (42.47%)
X-MVS
X-MVS - accuracy (90.57%)
X-MVS - completeness (68.25%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (83.28%)
xxxxxxxxxxxxxcwj - completeness (71.81%)
zzz-MVS
zzz-MVS - accuracy (90.01%)
zzz-MVS - completeness (69.19%)
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
:
-7.64 to 37.50
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
:
31.3
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