+
−
⇧
i
D
T
meadow (high-res multi-view) - Tolerance 1cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (57.41%)
3Dnovator - completeness (52.79%)
3Dnovator+
3Dnovator+ - accuracy (72.87%)
3Dnovator+ - completeness (49.06%)
ACMH
ACMH - accuracy (77.99%)
ACMH - completeness (17.74%)
ACMH+
ACMH+ - accuracy (70.86%)
ACMH+ - completeness (23.98%)
ACMM
ACMM - accuracy (76.49%)
ACMM - completeness (42.67%)
ACMMP
ACMMP - accuracy (78.32%)
ACMMP - completeness (43.05%)
ACMMPR
ACMMPR - accuracy (79.45%)
ACMMPR - completeness (46.04%)
ACMMP_NAP
ACMMP_NAP - accuracy (77.74%)
ACMMP_NAP - completeness (54.23%)
ACMP
ACMP - accuracy (75.46%)
ACMP - completeness (44.19%)
AdaColmap
AdaColmap - accuracy (66.64%)
AdaColmap - completeness (50.71%)
ADS-MVSNet
ADS-MVSNet - accuracy (30.87%)
ADS-MVSNet - completeness (27.11%)
ambc
ambc - accuracy (72.34%)
ambc - completeness (14.87%)
Anonymous20231206
Anonymous20231206 - accuracy (24.25%)
Anonymous20231206 - completeness (10.16%)
anonymousdsp
anonymousdsp - accuracy (59.55%)
anonymousdsp - completeness (22.53%)
APD-MVS
APD-MVS - accuracy (67.49%)
APD-MVS - completeness (52.92%)
APDe-MVS
APDe-MVS - accuracy (66.07%)
APDe-MVS - completeness (56.84%)
baseline1
baseline1 - accuracy (29.25%)
baseline1 - completeness (30.00%)
baseline2
baseline2 - accuracy (42.47%)
baseline2 - completeness (40.12%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (43.96%)
Baseline_NR-MVSNet - completeness (11.25%)
CANet
CANet - accuracy (59.81%)
CANet - completeness (50.63%)
CANet_DTU
CANet_DTU - accuracy (47.15%)
CANet_DTU - completeness (31.06%)
canonicalmvs
canonicalmvs - accuracy (46.87%)
canonicalmvs - completeness (47.84%)
casdiffmvs
casdiffmvs - accuracy (54.11%)
casdiffmvs - completeness (44.97%)
CDPH-MVS
CDPH-MVS - accuracy (69.75%)
CDPH-MVS - completeness (42.83%)
CDS-MVSNet
CDS-MVSNet - accuracy (32.75%)
CDS-MVSNet - completeness (26.64%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (36.95%)
CHOSEN 1792x2688 - completeness (39.85%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (18.84%)
CHOSEN 280x420 - completeness (18.03%)
CLD-MVS
CLD-MVS - accuracy (69.32%)
CLD-MVS - completeness (53.98%)
CMPMVS
CMPMVS - accuracy (61.35%)
CMPMVS - completeness (35.14%)
CNLPA
CNLPA - accuracy (74.68%)
CNLPA - completeness (44.85%)
CNVR-MVS
CNVR-MVS - accuracy (70.98%)
CNVR-MVS - completeness (56.70%)
COLMAP_ROB
COLMAP_ROB - accuracy (83.18%)
COLMAP_ROB - completeness (20.54%)
CostFormer
CostFormer - accuracy (43.43%)
CostFormer - completeness (46.00%)
CP-MVS
CP-MVS - accuracy (82.32%)
CP-MVS - completeness (45.76%)
CP-MVSNet
CP-MVSNet - accuracy (50.41%)
CP-MVSNet - completeness (5.93%)
CPTT-MVS
CPTT-MVS - accuracy (75.53%)
CPTT-MVS - completeness (37.74%)
CR-MVSNet
CR-MVSNet - accuracy (52.60%)
CR-MVSNet - completeness (31.74%)
CS-MVS
CS-MVS - accuracy (63.06%)
CS-MVS - completeness (41.28%)
CSCG
CSCG - accuracy (69.82%)
CSCG - completeness (59.06%)
CVMVSNet
CVMVSNet - accuracy (48.03%)
CVMVSNet - completeness (8.95%)
DCV-MVSNet
DCV-MVSNet - accuracy (41.34%)
DCV-MVSNet - completeness (36.81%)
DeepC-MVS
DeepC-MVS - accuracy (71.30%)
DeepC-MVS - completeness (53.50%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (68.91%)
DeepC-MVS_fast - completeness (51.03%)
DeepMVS_CX
DeepMVS_CX - accuracy (5.02%)
DeepMVS_CX - completeness (1.30%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (71.58%)
DeepPCF-MVS - completeness (49.07%)
DELS-MVS
DELS-MVS - accuracy (49.27%)
DELS-MVS - completeness (48.83%)
diffmvs
diffmvs - accuracy (50.58%)
diffmvs - completeness (43.37%)
DPE-MVS
DPE-MVS - accuracy (73.45%)
DPE-MVS - completeness (55.44%)
DPM-MVS
DPM-MVS - accuracy (67.06%)
DPM-MVS - completeness (57.75%)
dps
dps - accuracy (41.23%)
dps - completeness (39.53%)
DTE-MVSNet
DTE-MVSNet - accuracy (51.40%)
DTE-MVSNet - completeness (4.32%)
DU-MVS
DU-MVS - accuracy (46.77%)
DU-MVS - completeness (16.42%)
DVP-MVS
DVP-MVS - accuracy (71.32%)
DVP-MVS - completeness (62.54%)
E-PMN
E-PMN - accuracy (25.53%)
E-PMN - completeness (1.70%)
Effi-MVS+
Effi-MVS+ - accuracy (60.90%)
Effi-MVS+ - completeness (37.79%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (54.34%)
Effi-MVS+-dtu - completeness (34.22%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (59.11%)
EG-PatchMatch MVS - completeness (31.91%)
EIA-MVS
EIA-MVS - accuracy (51.50%)
EIA-MVS - completeness (41.01%)
EMVS
EMVS - accuracy (26.62%)
EMVS - completeness (1.67%)
EPMVS
EPMVS - accuracy (24.83%)
EPMVS - completeness (36.59%)
EPNet
EPNet - accuracy (53.41%)
EPNet - completeness (40.73%)
EPNet_dtu
EPNet_dtu - accuracy (47.64%)
EPNet_dtu - completeness (19.24%)
EPP-MVSNet
EPP-MVSNet - accuracy (41.79%)
EPP-MVSNet - completeness (20.20%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (51.10%)
ET-MVSNet_ETH3D - completeness (36.14%)
ETV-MVS
ETV-MVS - accuracy (50.88%)
ETV-MVS - completeness (42.37%)
EU-MVSNet
EU-MVSNet - accuracy (47.10%)
EU-MVSNet - completeness (5.83%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (54.29%)
Fast-Effi-MVS+ - completeness (38.96%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (49.67%)
Fast-Effi-MVS+-dtu - completeness (27.07%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (23.73%)
FC-MVSNet-test - completeness (1.67%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (32.62%)
FC-MVSNet-train - completeness (37.67%)
FMVSNet1
FMVSNet1 - accuracy (34.72%)
FMVSNet1 - completeness (25.37%)
FMVSNet2
FMVSNet2 - accuracy (33.19%)
FMVSNet2 - completeness (28.04%)
FMVSNet3
FMVSNet3 - accuracy (32.37%)
FMVSNet3 - completeness (28.77%)
FMVSNet5
FMVSNet5 - accuracy (24.55%)
FMVSNet5 - completeness (19.32%)
FPMVS
FPMVS - accuracy (53.53%)
FPMVS - completeness (11.33%)
GA-MVS
GA-MVS - accuracy (58.17%)
GA-MVS - completeness (27.15%)
GBi-Net
GBi-Net - accuracy (32.37%)
GBi-Net - completeness (28.77%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (1.21%)
GG-mvs-BLEND - completeness (0.01%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (46.93%)
gg-mvs-nofinetune - completeness (6.93%)
Gipuma
Gipuma - accuracy (71.78%)
Gipuma - completeness (4.86%)
gm-plane-assit
gm-plane-assit - accuracy (56.04%)
gm-plane-assit - completeness (6.59%)
HFP-MVS
HFP-MVS - accuracy (71.81%)
HFP-MVS - completeness (58.17%)
HPM-MVS++
HPM-MVS++ - accuracy (77.90%)
HPM-MVS++ - completeness (53.59%)
HQP-MVS
HQP-MVS - accuracy (73.32%)
HQP-MVS - completeness (43.85%)
HyFIR lowres test
HyFIR lowres test - accuracy (41.92%)
HyFIR lowres test - completeness (33.93%)
IB-MVS
IB-MVS - accuracy (45.37%)
IB-MVS - completeness (42.82%)
IS_MVSNet
IS_MVSNet - accuracy (43.30%)
IS_MVSNet - completeness (19.09%)
IterMVS
IterMVS - accuracy (46.31%)
IterMVS - completeness (25.89%)
IterMVS-LS
IterMVS-LS - accuracy (51.05%)
IterMVS-LS - completeness (33.22%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (53.62%)
IterMVS-SCA-FT - completeness (23.68%)
LGP-MVS_train
LGP-MVS_train - accuracy (80.44%)
LGP-MVS_train - completeness (38.47%)
LS3D
LS3D - accuracy (76.01%)
LS3D - completeness (28.32%)
LTVRE_ROB
LTVRE_ROB - accuracy (80.32%)
LTVRE_ROB - completeness (8.18%)
MAR-MVS
MAR-MVS - accuracy (69.03%)
MAR-MVS - completeness (46.44%)
MCST-MVS
MCST-MVS - accuracy (69.16%)
MCST-MVS - completeness (52.96%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (49.50%)
MDA-MVSNet-bldmvs - completeness (11.10%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (50.20%)
MDTV_nov1_ep13 - completeness (30.19%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (58.77%)
MDTV_nov1_ep13_2view - completeness (19.95%)
MIMVSNet
MIMVSNet - accuracy (24.53%)
MIMVSNet - completeness (20.06%)
MIMVSNet1
MIMVSNet1 - accuracy (32.00%)
MIMVSNet1 - completeness (3.79%)
MP-MVS
MP-MVS - accuracy (80.21%)
MP-MVS - completeness (48.81%)
MS-PatchMatch
MS-PatchMatch - accuracy (37.44%)
MS-PatchMatch - completeness (48.28%)
MSDG
MSDG - accuracy (64.89%)
MSDG - completeness (32.92%)
MSLP-MVS++
MSLP-MVS++ - accuracy (63.09%)
MSLP-MVS++ - completeness (57.51%)
MSP-MVS
MSP-MVS - accuracy (70.05%)
MSP-MVS - completeness (60.25%)
MTAPA
MTAPA - accuracy (80.26%)
MTAPA - completeness (54.82%)
MTMP
MTMP - accuracy (82.07%)
MTMP - completeness (50.64%)
MVE
MVE - accuracy (10.48%)
MVE - completeness (1.76%)
MVS-HIRNet
MVS-HIRNet - accuracy (44.37%)
MVS-HIRNet - completeness (33.75%)
MVSTER
MVSTER - accuracy (38.97%)
MVSTER - completeness (43.95%)
MVS_0304
MVS_0304 - accuracy (67.27%)
MVS_0304 - completeness (45.23%)
MVS_111021_LR
MVS_111021_LR - accuracy (66.80%)
MVS_111021_LR - completeness (44.89%)
MVS_Test
MVS_Test - accuracy (56.55%)
MVS_Test - completeness (43.74%)
NCCC
NCCC - accuracy (73.22%)
NCCC - completeness (54.19%)
new-patchmatchnet
new-patchmatchnet - accuracy (14.33%)
new-patchmatchnet - completeness (4.06%)
new_pmnet
new_pmnet - accuracy (9.01%)
new_pmnet - completeness (2.93%)
NR-MVSNet
NR-MVSNet - accuracy (45.38%)
NR-MVSNet - completeness (13.31%)
N_pmnet
N_pmnet - accuracy (7.98%)
N_pmnet - completeness (10.60%)
OMC-MVS
OMC-MVS - accuracy (79.42%)
OMC-MVS - completeness (42.30%)
OpenMVS
OpenMVS - accuracy (55.71%)
OpenMVS - completeness (45.67%)
OPM-MVS
OPM-MVS - accuracy (76.26%)
OPM-MVS - completeness (41.57%)
PatchMatch-RL
PatchMatch-RL - accuracy (48.16%)
PatchMatch-RL - completeness (30.71%)
PatchmatchNet
PatchmatchNet - accuracy (45.15%)
PatchmatchNet - completeness (37.26%)
Patchmtry
Patchmtry - accuracy (52.60%)
Patchmtry - completeness (31.74%)
PatchT
PatchT - accuracy (52.60%)
PatchT - completeness (31.74%)
PCF-MVS
PCF-MVS - accuracy (74.50%)
PCF-MVS - completeness (42.83%)
PEN-MVS
PEN-MVS - accuracy (50.08%)
PEN-MVS - completeness (5.54%)
PGM-MVS
PGM-MVS - accuracy (80.21%)
PGM-MVS - completeness (45.37%)
PHI-MVS
PHI-MVS - accuracy (79.05%)
PHI-MVS - completeness (37.56%)
PLC
PLC - accuracy (70.85%)
PLC - completeness (32.47%)
PM-MVS
PM-MVS - accuracy (49.91%)
PM-MVS - completeness (21.43%)
pm-mvs1
pm-mvs1 - accuracy (33.63%)
pm-mvs1 - completeness (20.76%)
PMMVS
PMMVS - accuracy (35.78%)
PMMVS - completeness (34.11%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (51.45%)
pmmvs-eth3d - completeness (29.13%)
PMMVS2
PMMVS2 - accuracy (4.16%)
PMMVS2 - completeness (0.19%)
pmmvs3
pmmvs3 - accuracy (36.34%)
pmmvs3 - completeness (10.99%)
pmmvs5
pmmvs5 - accuracy (33.83%)
pmmvs5 - completeness (24.80%)
pmmvs6
pmmvs6 - accuracy (34.69%)
pmmvs6 - completeness (19.08%)
pmnet_mix02
pmnet_mix02 - accuracy (24.89%)
pmnet_mix02 - completeness (23.39%)
PMVS
PMVS - accuracy (67.18%)
PMVS - completeness (11.32%)
PS-CasMVS
PS-CasMVS - accuracy (50.53%)
PS-CasMVS - completeness (5.89%)
PVSNet_Blended
PVSNet_Blended - accuracy (54.08%)
PVSNet_Blended - completeness (50.93%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (54.08%)
PVSNet_BlendedMVS - completeness (50.93%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (62.66%)
PVSNet_Blended_VisFu - completeness (42.73%)
QAPM
QAPM - accuracy (56.82%)
QAPM - completeness (43.29%)
RE-MVS-def
RE-MVS-def - accuracy (70.04%)
RE-MVS-def - completeness (21.59%)
RPMNet
RPMNet - accuracy (42.39%)
RPMNet - completeness (25.47%)
RPSCF
RPSCF - accuracy (72.89%)
RPSCF - completeness (23.12%)
SCA
SCA - accuracy (46.71%)
SCA - completeness (37.14%)
SD-MVS
SD-MVS - accuracy (67.55%)
SD-MVS - completeness (58.52%)
SED-MVS
SED-MVS - accuracy (69.45%)
SED-MVS - completeness (65.96%)
SF-MVS
SF-MVS - accuracy (70.65%)
SF-MVS - completeness (59.82%)
SMA-MVS
SMA-MVS - accuracy (78.61%)
SMA-MVS - completeness (54.48%)
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 (77.00%)
SteuartSystems-ACMMP - completeness (48.93%)
TAMVS
TAMVS - accuracy (22.55%)
TAMVS - completeness (18.34%)
TAPA-MVS
TAPA-MVS - accuracy (80.83%)
TAPA-MVS - completeness (34.97%)
TDRefinement
TDRefinement - accuracy (86.19%)
TDRefinement - completeness (19.04%)
test-mter
test-mter - accuracy (36.63%)
test-mter - completeness (22.67%)
test1
test1 - accuracy (32.37%)
test1 - completeness (28.77%)
test123
test123 - accuracy (1.37%)
test123 - completeness (0.00%)
testgi
testgi - accuracy (22.64%)
testgi - completeness (5.64%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (34.45%)
TESTMET0.1,1 - completeness (29.84%)
testmvs
testmvs - accuracy (0.18%)
testmvs - completeness (0.00%)
test_part1
test_part1 - accuracy (56.65%)
test_part1 - completeness (44.13%)
thisisatest0515
thisisatest0515 - accuracy (53.26%)
thisisatest0515 - completeness (29.73%)
thisisatest0530
thisisatest0530 - accuracy (49.06%)
thisisatest0530 - completeness (35.31%)
TinyColmap
TinyColmap - accuracy (75.93%)
TinyColmap - completeness (20.20%)
tmp_tt
tmp_tt - accuracy (15.76%)
tmp_tt - completeness (9.81%)
tpm
tpm - accuracy (58.05%)
tpm - completeness (34.41%)
tpm cat1
tpm cat1 - accuracy (47.61%)
tpm cat1 - completeness (46.36%)
tpmrst
tpmrst - accuracy (37.26%)
tpmrst - completeness (42.58%)
train_agg
train_agg - accuracy (71.03%)
train_agg - completeness (50.41%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (45.50%)
TranMVSNet+NR-MVSNet - completeness (13.25%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (34.80%)
TransMVSNet (Re) - completeness (19.33%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (64.03%)
TSAR-MVS + ACMM - completeness (48.69%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (70.13%)
TSAR-MVS + COLMAP - completeness (34.57%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (58.65%)
TSAR-MVS + GP. - completeness (56.32%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (67.62%)
TSAR-MVS + MP. - completeness (58.36%)
tttt0517
tttt0517 - accuracy (50.01%)
tttt0517 - completeness (33.88%)
UA-Net
UA-Net - accuracy (53.14%)
UA-Net - completeness (22.47%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (41.67%)
UGNet - completeness (27.30%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (46.20%)
UniMVSNet (Re) - completeness (13.55%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (41.87%)
UniMVSNet_ETH3D - completeness (19.88%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (46.77%)
UniMVSNet_NR-MVSNet - completeness (16.42%)
USDC
USDC - accuracy (76.58%)
USDC - completeness (23.65%)
Vis-MVSNet
Vis-MVSNet - accuracy (45.78%)
Vis-MVSNet - completeness (22.57%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (28.00%)
Vis-MVSNet (Re-imp) - completeness (8.84%)
WR-MVS_H
WR-MVS_H - accuracy (47.46%)
WR-MVS_H - completeness (4.14%)
X-MVS
X-MVS - accuracy (77.45%)
X-MVS - completeness (42.02%)
X-MVStestdata
X-MVStestdata - accuracy (77.45%)
X-MVStestdata - completeness (42.02%)
XVS
XVS - accuracy (77.45%)
XVS - completeness (42.02%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (70.65%)
xxxxxxxxxxxxxcwj - completeness (59.82%)
zzz-MVS
zzz-MVS - accuracy (80.21%)
zzz-MVS - completeness (54.61%)
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
:
-70.65 to 211.20
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
:
195.3
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