+
−
⇧
i
D
T
meadow (high-res multi-view) - Tolerance 2cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (76.11%)
3Dnovator - completeness (71.95%)
3Dnovator+
3Dnovator+ - accuracy (85.76%)
3Dnovator+ - completeness (71.83%)
ACMH
ACMH - accuracy (89.74%)
ACMH - completeness (30.98%)
ACMH+
ACMH+ - accuracy (82.66%)
ACMH+ - completeness (38.48%)
ACMM
ACMM - accuracy (86.88%)
ACMM - completeness (60.74%)
ACMMP
ACMMP - accuracy (86.87%)
ACMMP - completeness (62.61%)
ACMMPR
ACMMPR - accuracy (88.53%)
ACMMPR - completeness (68.35%)
ACMMP_NAP
ACMMP_NAP - accuracy (87.73%)
ACMMP_NAP - completeness (73.08%)
ACMP
ACMP - accuracy (85.33%)
ACMP - completeness (60.79%)
AdaColmap
AdaColmap - accuracy (80.41%)
AdaColmap - completeness (71.17%)
ADS-MVSNet
ADS-MVSNet - accuracy (49.19%)
ADS-MVSNet - completeness (38.01%)
ambc
ambc - accuracy (87.93%)
ambc - completeness (23.53%)
Anonymous20231206
Anonymous20231206 - accuracy (42.23%)
Anonymous20231206 - completeness (22.44%)
anonymousdsp
anonymousdsp - accuracy (81.59%)
anonymousdsp - completeness (33.66%)
APD-MVS
APD-MVS - accuracy (79.47%)
APD-MVS - completeness (77.99%)
APDe-MVS
APDe-MVS - accuracy (78.50%)
APDe-MVS - completeness (81.76%)
baseline1
baseline1 - accuracy (47.95%)
baseline1 - completeness (48.66%)
baseline2
baseline2 - accuracy (62.07%)
baseline2 - completeness (52.85%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (66.84%)
Baseline_NR-MVSNet - completeness (26.87%)
CANet
CANet - accuracy (78.73%)
CANet - completeness (69.90%)
CANet_DTU
CANet_DTU - accuracy (68.67%)
CANet_DTU - completeness (43.54%)
canonicalmvs
canonicalmvs - accuracy (67.98%)
canonicalmvs - completeness (66.72%)
casdiffmvs
casdiffmvs - accuracy (68.60%)
casdiffmvs - completeness (63.79%)
CDPH-MVS
CDPH-MVS - accuracy (82.71%)
CDPH-MVS - completeness (56.97%)
CDS-MVSNet
CDS-MVSNet - accuracy (52.52%)
CDS-MVSNet - completeness (46.58%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (56.69%)
CHOSEN 1792x2688 - completeness (52.32%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (36.79%)
CHOSEN 280x420 - completeness (39.57%)
CLD-MVS
CLD-MVS - accuracy (82.11%)
CLD-MVS - completeness (69.62%)
CMPMVS
CMPMVS - accuracy (75.49%)
CMPMVS - completeness (45.42%)
CNLPA
CNLPA - accuracy (84.06%)
CNLPA - completeness (64.80%)
CNVR-MVS
CNVR-MVS - accuracy (82.25%)
CNVR-MVS - completeness (75.93%)
COLMAP_ROB
COLMAP_ROB - accuracy (91.27%)
COLMAP_ROB - completeness (34.39%)
CostFormer
CostFormer - accuracy (62.77%)
CostFormer - completeness (60.40%)
CP-MVS
CP-MVS - accuracy (89.17%)
CP-MVS - completeness (67.39%)
CP-MVSNet
CP-MVSNet - accuracy (75.16%)
CP-MVSNet - completeness (16.59%)
CPTT-MVS
CPTT-MVS - accuracy (85.68%)
CPTT-MVS - completeness (61.39%)
CR-MVSNet
CR-MVSNet - accuracy (72.30%)
CR-MVSNet - completeness (41.40%)
CS-MVS
CS-MVS - accuracy (80.41%)
CS-MVS - completeness (55.73%)
CSCG
CSCG - accuracy (83.45%)
CSCG - completeness (76.14%)
CVMVSNet
CVMVSNet - accuracy (68.76%)
CVMVSNet - completeness (21.45%)
DCV-MVSNet
DCV-MVSNet - accuracy (62.53%)
DCV-MVSNet - completeness (55.34%)
DeepC-MVS
DeepC-MVS - accuracy (84.61%)
DeepC-MVS - completeness (71.01%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (82.16%)
DeepC-MVS_fast - completeness (71.09%)
DeepMVS_CX
DeepMVS_CX - accuracy (9.80%)
DeepMVS_CX - completeness (5.85%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (83.89%)
DeepPCF-MVS - completeness (65.84%)
DELS-MVS
DELS-MVS - accuracy (69.09%)
DELS-MVS - completeness (69.60%)
diffmvs
diffmvs - accuracy (67.62%)
diffmvs - completeness (61.89%)
DPE-MVS
DPE-MVS - accuracy (83.43%)
DPE-MVS - completeness (80.80%)
DPM-MVS
DPM-MVS - accuracy (79.15%)
DPM-MVS - completeness (73.95%)
dps
dps - accuracy (61.43%)
dps - completeness (55.67%)
DTE-MVSNet
DTE-MVSNet - accuracy (76.21%)
DTE-MVSNet - completeness (12.79%)
DU-MVS
DU-MVS - accuracy (70.49%)
DU-MVS - completeness (31.17%)
DVP-MVS
DVP-MVS - accuracy (80.49%)
DVP-MVS - completeness (85.15%)
E-PMN
E-PMN - accuracy (44.63%)
E-PMN - completeness (3.63%)
Effi-MVS+
Effi-MVS+ - accuracy (79.67%)
Effi-MVS+ - completeness (48.47%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (73.13%)
Effi-MVS+-dtu - completeness (44.71%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (78.17%)
EG-PatchMatch MVS - completeness (38.31%)
EIA-MVS
EIA-MVS - accuracy (73.49%)
EIA-MVS - completeness (55.56%)
EMVS
EMVS - accuracy (46.00%)
EMVS - completeness (3.56%)
EPMVS
EPMVS - accuracy (41.80%)
EPMVS - completeness (48.07%)
EPNet
EPNet - accuracy (74.29%)
EPNet - completeness (61.26%)
EPNet_dtu
EPNet_dtu - accuracy (69.74%)
EPNet_dtu - completeness (33.51%)
EPP-MVSNet
EPP-MVSNet - accuracy (62.97%)
EPP-MVSNet - completeness (41.15%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (70.96%)
ET-MVSNet_ETH3D - completeness (48.36%)
ETV-MVS
ETV-MVS - accuracy (71.56%)
ETV-MVS - completeness (57.73%)
EU-MVSNet
EU-MVSNet - accuracy (71.01%)
EU-MVSNet - completeness (13.82%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (74.75%)
Fast-Effi-MVS+ - completeness (50.61%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (68.75%)
Fast-Effi-MVS+-dtu - completeness (35.34%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (41.95%)
FC-MVSNet-test - completeness (6.66%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (52.22%)
FC-MVSNet-train - completeness (54.51%)
FMVSNet1
FMVSNet1 - accuracy (55.10%)
FMVSNet1 - completeness (45.66%)
FMVSNet2
FMVSNet2 - accuracy (52.97%)
FMVSNet2 - completeness (49.64%)
FMVSNet3
FMVSNet3 - accuracy (51.83%)
FMVSNet3 - completeness (51.06%)
FMVSNet5
FMVSNet5 - accuracy (41.33%)
FMVSNet5 - completeness (37.92%)
FPMVS
FPMVS - accuracy (71.47%)
FPMVS - completeness (22.61%)
GA-MVS
GA-MVS - accuracy (75.85%)
GA-MVS - completeness (35.58%)
GBi-Net
GBi-Net - accuracy (51.83%)
GBi-Net - completeness (51.06%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (2.42%)
GG-mvs-BLEND - completeness (0.05%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (67.80%)
gg-mvs-nofinetune - completeness (13.16%)
Gipuma
Gipuma - accuracy (89.03%)
Gipuma - completeness (10.03%)
gm-plane-assit
gm-plane-assit - accuracy (76.00%)
gm-plane-assit - completeness (13.71%)
HFP-MVS
HFP-MVS - accuracy (83.50%)
HFP-MVS - completeness (77.95%)
HPM-MVS++
HPM-MVS++ - accuracy (87.66%)
HPM-MVS++ - completeness (75.63%)
HQP-MVS
HQP-MVS - accuracy (83.48%)
HQP-MVS - completeness (55.83%)
HyFIR lowres test
HyFIR lowres test - accuracy (62.13%)
HyFIR lowres test - completeness (47.80%)
IB-MVS
IB-MVS - accuracy (64.31%)
IB-MVS - completeness (62.59%)
IS_MVSNet
IS_MVSNet - accuracy (63.52%)
IS_MVSNet - completeness (39.22%)
IterMVS
IterMVS - accuracy (66.62%)
IterMVS - completeness (37.86%)
IterMVS-LS
IterMVS-LS - accuracy (71.21%)
IterMVS-LS - completeness (48.32%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (73.79%)
IterMVS-SCA-FT - completeness (36.77%)
LGP-MVS_train
LGP-MVS_train - accuracy (87.23%)
LGP-MVS_train - completeness (51.98%)
LS3D
LS3D - accuracy (87.24%)
LS3D - completeness (44.35%)
LTVRE_ROB
LTVRE_ROB - accuracy (91.79%)
LTVRE_ROB - completeness (16.52%)
MAR-MVS
MAR-MVS - accuracy (82.25%)
MAR-MVS - completeness (58.33%)
MCST-MVS
MCST-MVS - accuracy (82.21%)
MCST-MVS - completeness (70.72%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (71.16%)
MDA-MVSNet-bldmvs - completeness (20.98%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (69.74%)
MDTV_nov1_ep13 - completeness (43.94%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (78.32%)
MDTV_nov1_ep13_2view - completeness (32.51%)
MIMVSNet
MIMVSNet - accuracy (41.26%)
MIMVSNet - completeness (36.79%)
MIMVSNet1
MIMVSNet1 - accuracy (53.92%)
MIMVSNet1 - completeness (11.29%)
MP-MVS
MP-MVS - accuracy (88.75%)
MP-MVS - completeness (69.67%)
MS-PatchMatch
MS-PatchMatch - accuracy (55.04%)
MS-PatchMatch - completeness (55.40%)
MSDG
MSDG - accuracy (80.26%)
MSDG - completeness (50.33%)
MSLP-MVS++
MSLP-MVS++ - accuracy (78.92%)
MSLP-MVS++ - completeness (78.40%)
MSP-MVS
MSP-MVS - accuracy (80.21%)
MSP-MVS - completeness (82.28%)
MTAPA
MTAPA - accuracy (89.37%)
MTAPA - completeness (78.32%)
MTMP
MTMP - accuracy (90.54%)
MTMP - completeness (76.04%)
MVE
MVE - accuracy (19.53%)
MVE - completeness (3.92%)
MVS-HIRNet
MVS-HIRNet - accuracy (65.17%)
MVS-HIRNet - completeness (43.47%)
MVSTER
MVSTER - accuracy (58.64%)
MVSTER - completeness (64.41%)
MVS_0304
MVS_0304 - accuracy (82.88%)
MVS_0304 - completeness (61.71%)
MVS_111021_LR
MVS_111021_LR - accuracy (81.19%)
MVS_111021_LR - completeness (63.58%)
MVS_Test
MVS_Test - accuracy (72.44%)
MVS_Test - completeness (57.50%)
NCCC
NCCC - accuracy (83.72%)
NCCC - completeness (72.91%)
new-patchmatchnet
new-patchmatchnet - accuracy (28.81%)
new-patchmatchnet - completeness (12.10%)
new_pmnet
new_pmnet - accuracy (17.85%)
new_pmnet - completeness (9.88%)
NR-MVSNet
NR-MVSNet - accuracy (68.85%)
NR-MVSNet - completeness (27.95%)
N_pmnet
N_pmnet - accuracy (17.24%)
N_pmnet - completeness (26.09%)
OMC-MVS
OMC-MVS - accuracy (87.40%)
OMC-MVS - completeness (61.83%)
OpenMVS
OpenMVS - accuracy (73.85%)
OpenMVS - completeness (62.80%)
OPM-MVS
OPM-MVS - accuracy (86.87%)
OPM-MVS - completeness (55.39%)
PatchMatch-RL
PatchMatch-RL - accuracy (68.34%)
PatchMatch-RL - completeness (53.80%)
PatchmatchNet
PatchmatchNet - accuracy (66.19%)
PatchmatchNet - completeness (45.27%)
Patchmtry
Patchmtry - accuracy (72.30%)
Patchmtry - completeness (41.40%)
PatchT
PatchT - accuracy (72.30%)
PatchT - completeness (41.40%)
PCF-MVS
PCF-MVS - accuracy (84.45%)
PCF-MVS - completeness (57.52%)
PEN-MVS
PEN-MVS - accuracy (74.83%)
PEN-MVS - completeness (15.36%)
PGM-MVS
PGM-MVS - accuracy (87.67%)
PGM-MVS - completeness (64.94%)
PHI-MVS
PHI-MVS - accuracy (89.65%)
PHI-MVS - completeness (51.81%)
PLC
PLC - accuracy (83.60%)
PLC - completeness (55.71%)
PM-MVS
PM-MVS - accuracy (71.75%)
PM-MVS - completeness (36.10%)
pm-mvs1
pm-mvs1 - accuracy (54.47%)
pm-mvs1 - completeness (36.86%)
PMMVS
PMMVS - accuracy (55.32%)
PMMVS - completeness (46.69%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (73.50%)
pmmvs-eth3d - completeness (41.09%)
PMMVS2
PMMVS2 - accuracy (8.90%)
PMMVS2 - completeness (0.79%)
pmmvs3
pmmvs3 - accuracy (57.39%)
pmmvs3 - completeness (20.22%)
pmmvs5
pmmvs5 - accuracy (56.25%)
pmmvs5 - completeness (37.23%)
pmmvs6
pmmvs6 - accuracy (55.92%)
pmmvs6 - completeness (34.30%)
pmnet_mix02
pmnet_mix02 - accuracy (43.76%)
pmnet_mix02 - completeness (34.65%)
PMVS
PMVS - accuracy (83.70%)
PMVS - completeness (22.50%)
PS-CasMVS
PS-CasMVS - accuracy (75.31%)
PS-CasMVS - completeness (16.42%)
PVSNet_Blended
PVSNet_Blended - accuracy (73.15%)
PVSNet_Blended - completeness (70.66%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (73.15%)
PVSNet_BlendedMVS - completeness (70.66%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (79.54%)
PVSNet_Blended_VisFu - completeness (59.66%)
QAPM
QAPM - accuracy (74.73%)
QAPM - completeness (58.05%)
RE-MVS-def
RE-MVS-def - accuracy (87.10%)
RE-MVS-def - completeness (31.47%)
RPMNet
RPMNet - accuracy (63.24%)
RPMNet - completeness (35.70%)
RPSCF
RPSCF - accuracy (82.29%)
RPSCF - completeness (45.88%)
SCA
SCA - accuracy (67.86%)
SCA - completeness (45.03%)
SD-MVS
SD-MVS - accuracy (81.79%)
SD-MVS - completeness (79.63%)
SED-MVS
SED-MVS - accuracy (80.15%)
SED-MVS - completeness (86.57%)
SF-MVS
SF-MVS - accuracy (82.70%)
SF-MVS - completeness (79.85%)
SMA-MVS
SMA-MVS - accuracy (87.80%)
SMA-MVS - completeness (74.33%)
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 (85.32%)
SteuartSystems-ACMMP - completeness (68.32%)
TAMVS
TAMVS - accuracy (38.00%)
TAMVS - completeness (36.17%)
TAPA-MVS
TAPA-MVS - accuracy (88.05%)
TAPA-MVS - completeness (51.28%)
TDRefinement
TDRefinement - accuracy (93.00%)
TDRefinement - completeness (33.93%)
test-mter
test-mter - accuracy (56.31%)
test-mter - completeness (39.18%)
test1
test1 - accuracy (51.83%)
test1 - completeness (51.06%)
test123
test123 - accuracy (1.37%)
test123 - completeness (0.00%)
testgi
testgi - accuracy (39.36%)
testgi - completeness (17.03%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (53.81%)
TESTMET0.1,1 - completeness (42.96%)
testmvs
testmvs - accuracy (0.18%)
testmvs - completeness (0.00%)
test_part1
test_part1 - accuracy (76.74%)
test_part1 - completeness (62.15%)
thisisatest0515
thisisatest0515 - accuracy (73.95%)
thisisatest0515 - completeness (42.12%)
thisisatest0530
thisisatest0530 - accuracy (69.32%)
thisisatest0530 - completeness (50.80%)
TinyColmap
TinyColmap - accuracy (89.46%)
TinyColmap - completeness (32.51%)
tmp_tt
tmp_tt - accuracy (27.44%)
tmp_tt - completeness (30.10%)
tpm
tpm - accuracy (76.70%)
tpm - completeness (43.28%)
tpm cat1
tpm cat1 - accuracy (66.41%)
tpm cat1 - completeness (61.12%)
tpmrst
tpmrst - accuracy (57.68%)
tpmrst - completeness (50.63%)
train_agg
train_agg - accuracy (81.54%)
train_agg - completeness (66.58%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (68.99%)
TranMVSNet+NR-MVSNet - completeness (27.73%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (55.84%)
TransMVSNet (Re) - completeness (32.65%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (79.80%)
TSAR-MVS + ACMM - completeness (65.43%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (82.33%)
TSAR-MVS + COLMAP - completeness (49.31%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (74.52%)
TSAR-MVS + GP. - completeness (73.31%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (81.83%)
TSAR-MVS + MP. - completeness (79.24%)
tttt0517
tttt0517 - accuracy (70.24%)
tttt0517 - completeness (49.90%)
UA-Net
UA-Net - accuracy (74.79%)
UA-Net - completeness (44.75%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (62.57%)
UGNet - completeness (51.87%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (69.29%)
UniMVSNet (Re) - completeness (29.80%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (64.43%)
UniMVSNet_ETH3D - completeness (36.84%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (70.49%)
UniMVSNet_NR-MVSNet - completeness (31.17%)
USDC
USDC - accuracy (90.73%)
USDC - completeness (35.02%)
Vis-MVSNet
Vis-MVSNet - accuracy (67.10%)
Vis-MVSNet - completeness (40.62%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (46.94%)
Vis-MVSNet (Re-imp) - completeness (26.86%)
WR-MVS_H
WR-MVS_H - accuracy (71.92%)
WR-MVS_H - completeness (13.63%)
X-MVS
X-MVS - accuracy (87.14%)
X-MVS - completeness (61.07%)
X-MVStestdata
X-MVStestdata - accuracy (87.14%)
X-MVStestdata - completeness (61.07%)
XVS
XVS - accuracy (87.14%)
XVS - completeness (61.07%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (82.70%)
xxxxxxxxxxxxxcwj - completeness (79.85%)
zzz-MVS
zzz-MVS - accuracy (89.30%)
zzz-MVS - completeness (77.67%)
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
:
-12.63 to 132.08
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
:
100.3
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