+
−
⇧
i
D
T
relief_2 (high-res multi-view) - Tolerance 2cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (86.47%)
3Dnovator - completeness (84.24%)
3Dnovator+
3Dnovator+ - accuracy (92.21%)
3Dnovator+ - completeness (82.04%)
ACMH
ACMH - accuracy (89.57%)
ACMH - completeness (73.47%)
ACMH+
ACMH+ - accuracy (92.34%)
ACMH+ - completeness (69.80%)
ACMM
ACMM - accuracy (94.49%)
ACMM - completeness (75.57%)
ACMMP
ACMMP - accuracy (94.50%)
ACMMP - completeness (78.50%)
ACMMPR
ACMMPR - accuracy (94.27%)
ACMMPR - completeness (81.13%)
ACMMP_NAP
ACMMP_NAP - accuracy (93.82%)
ACMMP_NAP - completeness (83.64%)
ACMP
ACMP - accuracy (93.44%)
ACMP - completeness (75.27%)
AdaColmap
AdaColmap - accuracy (89.90%)
AdaColmap - completeness (76.82%)
ADS-MVSNet
ADS-MVSNet - accuracy (54.66%)
ADS-MVSNet - completeness (66.55%)
ambc
ambc - accuracy (83.86%)
ambc - completeness (56.26%)
Anonymous20231206
Anonymous20231206 - accuracy (69.97%)
Anonymous20231206 - completeness (67.83%)
Anonymous202405211
Anonymous202405211 - accuracy (84.26%)
Anonymous202405211 - completeness (76.84%)
anonymousdsp
anonymousdsp - accuracy (92.83%)
anonymousdsp - completeness (70.60%)
APD-MVS
APD-MVS - accuracy (92.20%)
APD-MVS - completeness (81.37%)
APDe-MVS
APDe-MVS - accuracy (91.90%)
APDe-MVS - completeness (82.58%)
baseline1
baseline1 - accuracy (76.94%)
baseline1 - completeness (80.99%)
baseline2
baseline2 - accuracy (74.03%)
baseline2 - completeness (79.31%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (83.37%)
Baseline_NR-MVSNet - completeness (73.61%)
CANet
CANet - accuracy (86.17%)
CANet - completeness (84.77%)
CANet_DTU
CANet_DTU - accuracy (81.11%)
CANet_DTU - completeness (80.82%)
canonicalmvs
canonicalmvs - accuracy (86.15%)
canonicalmvs - completeness (82.73%)
casdiffmvs
casdiffmvs - accuracy (77.07%)
casdiffmvs - completeness (81.78%)
CDPH-MVS
CDPH-MVS - accuracy (89.85%)
CDPH-MVS - completeness (82.74%)
CDS-MVSNet
CDS-MVSNet - accuracy (83.93%)
CDS-MVSNet - completeness (76.08%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (72.01%)
CHOSEN 1792x2688 - completeness (85.41%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (67.66%)
CHOSEN 280x420 - completeness (69.52%)
CLD-MVS
CLD-MVS - accuracy (88.29%)
CLD-MVS - completeness (81.27%)
CMPMVS
CMPMVS - accuracy (77.20%)
CMPMVS - completeness (64.65%)
CNLPA
CNLPA - accuracy (89.00%)
CNLPA - completeness (70.52%)
CNVR-MVS
CNVR-MVS - accuracy (90.69%)
CNVR-MVS - completeness (86.58%)
COLMAP_ROB
COLMAP_ROB - accuracy (95.27%)
COLMAP_ROB - completeness (62.52%)
CostFormer
CostFormer - accuracy (62.35%)
CostFormer - completeness (76.41%)
CP-MVS
CP-MVS - accuracy (94.72%)
CP-MVS - completeness (79.58%)
CP-MVSNet
CP-MVSNet - accuracy (93.18%)
CP-MVSNet - completeness (63.71%)
CPTT-MVS
CPTT-MVS - accuracy (92.68%)
CPTT-MVS - completeness (73.32%)
CR-MVSNet
CR-MVSNet - accuracy (72.91%)
CR-MVSNet - completeness (73.27%)
CS-MVS
CS-MVS - accuracy (84.36%)
CS-MVS - completeness (81.29%)
CSCG
CSCG - accuracy (88.21%)
CSCG - completeness (85.18%)
CVMVSNet
CVMVSNet - accuracy (81.01%)
CVMVSNet - completeness (63.81%)
DCV-MVSNet
DCV-MVSNet - accuracy (85.91%)
DCV-MVSNet - completeness (76.56%)
DeepC-MVS
DeepC-MVS - accuracy (92.52%)
DeepC-MVS - completeness (84.20%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (90.44%)
DeepC-MVS_fast - completeness (84.97%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (90.19%)
DeepPCF-MVS - completeness (85.39%)
DELS-MVS
DELS-MVS - accuracy (83.87%)
DELS-MVS - completeness (88.03%)
diffmvs
diffmvs - accuracy (76.18%)
diffmvs - completeness (79.87%)
DPE-MVS
DPE-MVS - accuracy (92.07%)
DPE-MVS - completeness (83.52%)
DPM-MVS
DPM-MVS - accuracy (83.46%)
DPM-MVS - completeness (90.65%)
dps
dps - accuracy (64.65%)
dps - completeness (69.82%)
DTE-MVSNet
DTE-MVSNet - accuracy (92.32%)
DTE-MVSNet - completeness (65.22%)
DU-MVS
DU-MVS - accuracy (89.29%)
DU-MVS - completeness (73.20%)
DVP-MVS
DVP-MVS - accuracy (91.42%)
DVP-MVS - completeness (84.67%)
E-PMN
E-PMN - accuracy (51.98%)
E-PMN - completeness (18.50%)
Effi-MVS+
Effi-MVS+ - accuracy (86.91%)
Effi-MVS+ - completeness (77.06%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (87.76%)
Effi-MVS+-dtu - completeness (66.32%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (86.33%)
EG-PatchMatch MVS - completeness (75.70%)
EIA-MVS
EIA-MVS - accuracy (84.93%)
EIA-MVS - completeness (78.59%)
EMVS
EMVS - accuracy (50.68%)
EMVS - completeness (16.06%)
EPMVS
EPMVS - accuracy (54.82%)
EPMVS - completeness (71.40%)
EPNet
EPNet - accuracy (85.45%)
EPNet - completeness (82.00%)
EPNet_dtu
EPNet_dtu - accuracy (78.01%)
EPNet_dtu - completeness (72.18%)
EPP-MVSNet
EPP-MVSNet - accuracy (90.40%)
EPP-MVSNet - completeness (72.92%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (81.65%)
ET-MVSNet_ETH3D - completeness (80.58%)
ETV-MVS
ETV-MVS - accuracy (86.77%)
ETV-MVS - completeness (81.23%)
EU-MVSNet
EU-MVSNet - accuracy (77.85%)
EU-MVSNet - completeness (55.57%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (85.26%)
Fast-Effi-MVS+ - completeness (76.44%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (81.76%)
Fast-Effi-MVS+-dtu - completeness (71.44%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (85.56%)
FC-MVSNet-test - completeness (61.21%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (86.93%)
FC-MVSNet-train - completeness (75.75%)
FMVSNet1
FMVSNet1 - accuracy (83.39%)
FMVSNet1 - completeness (78.22%)
FMVSNet2
FMVSNet2 - accuracy (79.73%)
FMVSNet2 - completeness (80.99%)
FMVSNet3
FMVSNet3 - accuracy (77.03%)
FMVSNet3 - completeness (82.27%)
FMVSNet5
FMVSNet5 - accuracy (70.77%)
FMVSNet5 - completeness (71.43%)
FPMVS
FPMVS - accuracy (90.21%)
FPMVS - completeness (40.67%)
GA-MVS
GA-MVS - accuracy (76.62%)
GA-MVS - completeness (78.54%)
GBi-Net
GBi-Net - accuracy (83.39%)
GBi-Net - completeness (78.22%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (58.29%)
GG-mvs-BLEND - completeness (79.30%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (73.65%)
gg-mvs-nofinetune - completeness (85.25%)
Gipuma
Gipuma - accuracy (86.86%)
Gipuma - completeness (47.03%)
gm-plane-assit
gm-plane-assit - accuracy (70.24%)
gm-plane-assit - completeness (86.55%)
HFP-MVS
HFP-MVS - accuracy (94.19%)
HFP-MVS - completeness (81.17%)
HPM-MVS++
HPM-MVS++ - accuracy (91.41%)
HPM-MVS++ - completeness (85.26%)
HQP-MVS
HQP-MVS - accuracy (85.89%)
HQP-MVS - completeness (81.78%)
HyFIR lowres test
HyFIR lowres test - accuracy (77.47%)
HyFIR lowres test - completeness (79.14%)
IB-MVS
IB-MVS - accuracy (82.34%)
IB-MVS - completeness (81.88%)
IS_MVSNet
IS_MVSNet - accuracy (89.33%)
IS_MVSNet - completeness (78.52%)
IterMVS
IterMVS - accuracy (71.63%)
IterMVS - completeness (73.71%)
IterMVS-LS
IterMVS-LS - accuracy (80.57%)
IterMVS-LS - completeness (74.42%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (75.50%)
IterMVS-SCA-FT - completeness (72.40%)
LGP-MVS_train
LGP-MVS_train - accuracy (93.41%)
LGP-MVS_train - completeness (76.32%)
LS3D
LS3D - accuracy (92.59%)
LS3D - completeness (68.69%)
LTVRE_ROB
LTVRE_ROB - accuracy (96.27%)
LTVRE_ROB - completeness (63.16%)
MAR-MVS
MAR-MVS - accuracy (86.96%)
MAR-MVS - completeness (83.12%)
MCST-MVS
MCST-MVS - accuracy (84.78%)
MCST-MVS - completeness (87.49%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (77.48%)
MDA-MVSNet-bldmvs - completeness (57.47%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (62.16%)
MDTV_nov1_ep13 - completeness (73.37%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (66.83%)
MDTV_nov1_ep13_2view - completeness (66.21%)
MIMVSNet
MIMVSNet - accuracy (67.32%)
MIMVSNet - completeness (76.58%)
MIMVSNet1
MIMVSNet1 - accuracy (79.32%)
MIMVSNet1 - completeness (61.12%)
MP-MVS
MP-MVS - accuracy (94.34%)
MP-MVS - completeness (80.96%)
MS-PatchMatch
MS-PatchMatch - accuracy (75.97%)
MS-PatchMatch - completeness (78.29%)
MSDG
MSDG - accuracy (84.98%)
MSDG - completeness (72.94%)
MSLP-MVS++
MSLP-MVS++ - accuracy (91.88%)
MSLP-MVS++ - completeness (78.88%)
MSP-MVS
MSP-MVS - accuracy (91.42%)
MSP-MVS - completeness (84.67%)
MVE
MVE - accuracy (61.51%)
MVE - completeness (31.46%)
MVS-HIRNet
MVS-HIRNet - accuracy (53.74%)
MVS-HIRNet - completeness (67.16%)
MVSTER
MVSTER - accuracy (76.03%)
MVSTER - completeness (83.73%)
MVS_0304
MVS_0304 - accuracy (87.69%)
MVS_0304 - completeness (85.03%)
MVS_111021_LR
MVS_111021_LR - accuracy (85.90%)
MVS_111021_LR - completeness (77.15%)
MVS_Test
MVS_Test - accuracy (75.74%)
MVS_Test - completeness (83.60%)
NCCC
NCCC - accuracy (90.68%)
NCCC - completeness (84.88%)
new-patchmatchnet
new-patchmatchnet - accuracy (53.66%)
new-patchmatchnet - completeness (56.04%)
new_pmnet
new_pmnet - accuracy (62.28%)
new_pmnet - completeness (45.98%)
NR-MVSNet
NR-MVSNet - accuracy (88.68%)
NR-MVSNet - completeness (74.05%)
N_pmnet
N_pmnet - accuracy (51.76%)
N_pmnet - completeness (59.01%)
OMC-MVS
OMC-MVS - accuracy (90.84%)
OMC-MVS - completeness (74.07%)
OpenMVS
OpenMVS - accuracy (81.95%)
OpenMVS - completeness (80.88%)
OPM-MVS
OPM-MVS - accuracy (91.99%)
OPM-MVS - completeness (79.43%)
PatchMatch-RL
PatchMatch-RL - accuracy (83.44%)
PatchMatch-RL - completeness (67.22%)
PatchmatchNet
PatchmatchNet - accuracy (61.47%)
PatchmatchNet - completeness (71.38%)
PatchT
PatchT - accuracy (72.91%)
PatchT - completeness (73.27%)
PCF-MVS
PCF-MVS - accuracy (83.88%)
PCF-MVS - completeness (77.65%)
PEN-MVS
PEN-MVS - accuracy (92.43%)
PEN-MVS - completeness (66.37%)
PGM-MVS
PGM-MVS - accuracy (93.94%)
PGM-MVS - completeness (80.55%)
PHI-MVS
PHI-MVS - accuracy (89.70%)
PHI-MVS - completeness (84.00%)
PLC
PLC - accuracy (89.66%)
PLC - completeness (70.67%)
PM-MVS
PM-MVS - accuracy (85.12%)
PM-MVS - completeness (55.42%)
pm-mvs1
pm-mvs1 - accuracy (82.98%)
pm-mvs1 - completeness (73.30%)
PMMVS
PMMVS - accuracy (71.56%)
PMMVS - completeness (75.63%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (81.64%)
pmmvs-eth3d - completeness (67.28%)
PMMVS2
PMMVS2 - accuracy (55.91%)
PMMVS2 - completeness (32.87%)
pmmvs3
pmmvs3 - accuracy (69.43%)
pmmvs3 - completeness (58.79%)
pmmvs5
pmmvs5 - accuracy (74.23%)
pmmvs5 - completeness (72.74%)
pmmvs6
pmmvs6 - accuracy (85.61%)
pmmvs6 - completeness (68.76%)
pmnet_mix02
pmnet_mix02 - accuracy (57.09%)
pmnet_mix02 - completeness (63.71%)
PMVS
PMVS - accuracy (96.79%)
PMVS - completeness (38.06%)
PS-CasMVS
PS-CasMVS - accuracy (93.32%)
PS-CasMVS - completeness (63.54%)
PVSNet_Blended
PVSNet_Blended - accuracy (77.66%)
PVSNet_Blended - completeness (81.70%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (77.66%)
PVSNet_BlendedMVS - completeness (81.70%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (84.93%)
PVSNet_Blended_VisFu - completeness (78.90%)
QAPM
QAPM - accuracy (84.71%)
QAPM - completeness (82.04%)
RPMNet
RPMNet - accuracy (69.64%)
RPMNet - completeness (67.38%)
RPSCF
RPSCF - accuracy (94.90%)
RPSCF - completeness (53.53%)
SCA
SCA - accuracy (65.67%)
SCA - completeness (70.80%)
SD-MVS
SD-MVS - accuracy (92.69%)
SD-MVS - completeness (81.60%)
SED-MVS
SED-MVS - accuracy (91.17%)
SED-MVS - completeness (85.08%)
SF-MVS
SF-MVS - accuracy (90.04%)
SF-MVS - completeness (82.72%)
SMA-MVS
SMA-MVS - accuracy (93.59%)
SMA-MVS - completeness (85.58%)
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 (93.88%)
SteuartSystems-ACMMP - completeness (83.64%)
TAMVS
TAMVS - accuracy (72.81%)
TAMVS - completeness (70.79%)
TAPA-MVS
TAPA-MVS - accuracy (88.22%)
TAPA-MVS - completeness (72.42%)
TDRefinement
TDRefinement - accuracy (96.81%)
TDRefinement - completeness (62.48%)
test-mter
test-mter - accuracy (64.27%)
test-mter - completeness (76.00%)
test1
test1 - accuracy (83.39%)
test1 - completeness (78.22%)
test123
test123 - accuracy (1.27%)
test123 - completeness (0.05%)
testgi
testgi - accuracy (70.40%)
testgi - completeness (67.00%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (62.34%)
TESTMET0.1,1 - completeness (78.09%)
testmvs
testmvs - accuracy (1.08%)
testmvs - completeness (0.05%)
test_part1
test_part1 - accuracy (90.92%)
test_part1 - completeness (74.65%)
thisisatest0515
thisisatest0515 - accuracy (84.78%)
thisisatest0515 - completeness (73.79%)
thisisatest0530
thisisatest0530 - accuracy (83.08%)
thisisatest0530 - completeness (77.47%)
TinyColmap
TinyColmap - accuracy (81.94%)
TinyColmap - completeness (65.15%)
tmp_tt
tmp_tt - accuracy (36.26%)
tmp_tt - completeness (25.25%)
tpm
tpm - accuracy (58.54%)
tpm - completeness (71.30%)
tpm cat1
tpm cat1 - accuracy (58.16%)
tpm cat1 - completeness (71.50%)
tpmrst
tpmrst - accuracy (55.55%)
tpmrst - completeness (71.77%)
train_agg
train_agg - accuracy (88.47%)
train_agg - completeness (82.64%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (89.13%)
TranMVSNet+NR-MVSNet - completeness (74.59%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (83.22%)
TransMVSNet (Re) - completeness (72.84%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (92.45%)
TSAR-MVS + ACMM - completeness (81.33%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (86.84%)
TSAR-MVS + COLMAP - completeness (75.52%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (90.41%)
TSAR-MVS + GP. - completeness (81.47%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (92.25%)
TSAR-MVS + MP. - completeness (80.92%)
tttt0517
tttt0517 - accuracy (83.08%)
tttt0517 - completeness (77.47%)
UA-Net
UA-Net - accuracy (95.45%)
UA-Net - completeness (72.25%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (87.35%)
UGNet - completeness (74.99%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (89.60%)
UniMVSNet (Re) - completeness (73.27%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (89.74%)
UniMVSNet_ETH3D - completeness (69.81%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (88.47%)
UniMVSNet_NR-MVSNet - completeness (74.81%)
USDC
USDC - accuracy (77.97%)
USDC - completeness (71.33%)
Vis-MVSNet
Vis-MVSNet - accuracy (89.37%)
Vis-MVSNet - completeness (76.24%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (84.56%)
Vis-MVSNet (Re-imp) - completeness (74.90%)
WR-MVS_H
WR-MVS_H - accuracy (93.19%)
WR-MVS_H - completeness (62.76%)
X-MVS
X-MVS - accuracy (94.28%)
X-MVS - completeness (80.52%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (90.04%)
xxxxxxxxxxxxxcwj - completeness (82.72%)
zzz-MVS
zzz-MVS - accuracy (94.83%)
zzz-MVS - completeness (81.15%)
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
:
-19.32 to 65.70
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
:
58.9
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