+
−
⇧
i
D
T
pipes (high-res multi-view) - Tolerance 2cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (85.38%)
3Dnovator - completeness (67.86%)
3Dnovator+
3Dnovator+ - accuracy (86.92%)
3Dnovator+ - completeness (70.68%)
9.14
9.14 - accuracy (89.43%)
9.14 - completeness (84.47%)
ACMH
ACMH - accuracy (98.50%)
ACMH - completeness (34.59%)
ACMH+
ACMH+ - accuracy (98.35%)
ACMH+ - completeness (37.35%)
ACMM
ACMM - accuracy (96.63%)
ACMM - completeness (53.97%)
ACMMP
ACMMP - accuracy (96.46%)
ACMMP - completeness (65.79%)
ACMMPR
ACMMPR - accuracy (95.57%)
ACMMPR - completeness (73.64%)
ACMMP_NAP
ACMMP_NAP - accuracy (91.80%)
ACMMP_NAP - completeness (80.16%)
ACMP
ACMP - accuracy (97.65%)
ACMP - completeness (53.54%)
AdaColmap
AdaColmap - accuracy (84.69%)
AdaColmap - completeness (57.99%)
ADS-MVSNet
ADS-MVSNet - accuracy (65.97%)
ADS-MVSNet - completeness (44.72%)
ambc
ambc - accuracy (94.82%)
ambc - completeness (8.95%)
Anonymous20231206
Anonymous20231206 - accuracy (90.47%)
Anonymous20231206 - completeness (31.42%)
Anonymous202405211
Anonymous202405211 - accuracy (92.58%)
Anonymous202405211 - completeness (53.73%)
anonymousdsp
anonymousdsp - accuracy (97.71%)
anonymousdsp - completeness (36.13%)
APD-MVS
APD-MVS - accuracy (94.85%)
APD-MVS - completeness (80.04%)
APDe-MVS
APDe-MVS - accuracy (95.82%)
APDe-MVS - completeness (81.94%)
baseline1
baseline1 - accuracy (68.19%)
baseline1 - completeness (60.43%)
baseline2
baseline2 - accuracy (60.35%)
baseline2 - completeness (54.31%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (96.46%)
Baseline_NR-MVSNet - completeness (37.62%)
CANet
CANet - accuracy (90.70%)
CANet - completeness (74.80%)
CANet_DTU
CANet_DTU - accuracy (88.37%)
CANet_DTU - completeness (58.46%)
canonicalmvs
canonicalmvs - accuracy (91.51%)
canonicalmvs - completeness (65.09%)
casdiffmvs
casdiffmvs - accuracy (96.03%)
casdiffmvs - completeness (60.32%)
CDPH-MVS
CDPH-MVS - accuracy (93.32%)
CDPH-MVS - completeness (72.24%)
CDS-MVSNet
CDS-MVSNet - accuracy (81.12%)
CDS-MVSNet - completeness (50.76%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (78.39%)
CHOSEN 1792x2688 - completeness (50.74%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (62.59%)
CHOSEN 280x420 - completeness (64.97%)
CLD-MVS
CLD-MVS - accuracy (95.27%)
CLD-MVS - completeness (59.44%)
CMPMVS
CMPMVS - accuracy (85.67%)
CMPMVS - completeness (39.03%)
CNLPA
CNLPA - accuracy (91.34%)
CNLPA - completeness (56.49%)
CNVR-MVS
CNVR-MVS - accuracy (92.15%)
CNVR-MVS - completeness (81.97%)
COLMAP_ROB
COLMAP_ROB - accuracy (97.77%)
COLMAP_ROB - completeness (34.24%)
CostFormer
CostFormer - accuracy (60.09%)
CostFormer - completeness (65.82%)
CP-MVS
CP-MVS - accuracy (96.34%)
CP-MVS - completeness (73.68%)
CP-MVSNet
CP-MVSNet - accuracy (97.68%)
CP-MVSNet - completeness (31.95%)
CPTT-MVS
CPTT-MVS - accuracy (95.74%)
CPTT-MVS - completeness (70.94%)
CR-MVSNet
CR-MVSNet - accuracy (56.77%)
CR-MVSNet - completeness (55.85%)
CS-MVS
CS-MVS - accuracy (75.07%)
CS-MVS - completeness (66.89%)
CSCG
CSCG - accuracy (95.14%)
CSCG - completeness (82.49%)
CVMVSNet
CVMVSNet - accuracy (78.93%)
CVMVSNet - completeness (46.10%)
DCV-MVSNet
DCV-MVSNet - accuracy (94.43%)
DCV-MVSNet - completeness (55.56%)
DeepC-MVS
DeepC-MVS - accuracy (94.22%)
DeepC-MVS - completeness (69.93%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (91.99%)
DeepC-MVS_fast - completeness (72.44%)
DeepMVS_CX
DeepMVS_CX - accuracy (34.88%)
DeepMVS_CX - completeness (8.03%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (90.84%)
DeepPCF-MVS - completeness (81.55%)
DELS-MVS
DELS-MVS - accuracy (89.38%)
DELS-MVS - completeness (66.50%)
diffmvs
diffmvs - accuracy (93.94%)
diffmvs - completeness (59.84%)
DPE-MVS
DPE-MVS - accuracy (95.19%)
DPE-MVS - completeness (86.70%)
DPM-MVS
DPM-MVS - accuracy (83.29%)
DPM-MVS - completeness (82.01%)
dps
dps - accuracy (52.70%)
dps - completeness (43.63%)
DTE-MVSNet
DTE-MVSNet - accuracy (98.04%)
DTE-MVSNet - completeness (31.93%)
DU-MVS
DU-MVS - accuracy (96.91%)
DU-MVS - completeness (36.95%)
DVP-MVS
DVP-MVS - accuracy (94.87%)
DVP-MVS - completeness (86.90%)
E-PMN
E-PMN - accuracy (73.17%)
E-PMN - completeness (2.22%)
Effi-MVS+
Effi-MVS+ - accuracy (92.31%)
Effi-MVS+ - completeness (54.94%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (91.11%)
Effi-MVS+-dtu - completeness (51.10%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (95.03%)
EG-PatchMatch MVS - completeness (37.22%)
EIA-MVS
EIA-MVS - accuracy (76.12%)
EIA-MVS - completeness (60.69%)
EMVS
EMVS - accuracy (71.66%)
EMVS - completeness (2.27%)
EPMVS
EPMVS - accuracy (57.28%)
EPMVS - completeness (54.87%)
EPNet
EPNet - accuracy (79.22%)
EPNet - completeness (70.08%)
EPNet_dtu
EPNet_dtu - accuracy (82.41%)
EPNet_dtu - completeness (56.22%)
EPP-MVSNet
EPP-MVSNet - accuracy (76.84%)
EPP-MVSNet - completeness (67.89%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (57.70%)
ET-MVSNet_ETH3D - completeness (60.67%)
ETV-MVS
ETV-MVS - accuracy (73.63%)
ETV-MVS - completeness (66.60%)
EU-MVSNet
EU-MVSNet - accuracy (93.17%)
EU-MVSNet - completeness (30.99%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (92.70%)
Fast-Effi-MVS+ - completeness (47.05%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (86.57%)
Fast-Effi-MVS+-dtu - completeness (46.36%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (87.04%)
FC-MVSNet-test - completeness (42.02%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (93.69%)
FC-MVSNet-train - completeness (47.91%)
FMVSNet1
FMVSNet1 - accuracy (93.18%)
FMVSNet1 - completeness (49.43%)
FMVSNet2
FMVSNet2 - accuracy (85.61%)
FMVSNet2 - completeness (57.08%)
FMVSNet3
FMVSNet3 - accuracy (77.76%)
FMVSNet3 - completeness (62.05%)
FMVSNet5
FMVSNet5 - accuracy (54.68%)
FMVSNet5 - completeness (52.22%)
FPMVS
FPMVS - accuracy (83.22%)
FPMVS - completeness (19.82%)
GA-MVS
GA-MVS - accuracy (76.14%)
GA-MVS - completeness (41.82%)
GBi-Net
GBi-Net - accuracy (77.76%)
GBi-Net - completeness (62.05%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (69.42%)
GG-mvs-BLEND - completeness (73.33%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (64.67%)
gg-mvs-nofinetune - completeness (63.97%)
Gipuma
Gipuma - accuracy (96.32%)
Gipuma - completeness (4.25%)
gm-plane-assit
gm-plane-assit - accuracy (37.09%)
gm-plane-assit - completeness (43.84%)
HFP-MVS
HFP-MVS - accuracy (94.44%)
HFP-MVS - completeness (75.94%)
HPM-MVS++
HPM-MVS++ - accuracy (92.07%)
HPM-MVS++ - completeness (84.15%)
HQP-MVS
HQP-MVS - accuracy (93.54%)
HQP-MVS - completeness (64.90%)
HyFIR lowres test
HyFIR lowres test - accuracy (78.50%)
HyFIR lowres test - completeness (55.80%)
IB-MVS
IB-MVS - accuracy (87.57%)
IB-MVS - completeness (45.23%)
IS_MVSNet
IS_MVSNet - accuracy (81.18%)
IS_MVSNet - completeness (62.47%)
IterMVS
IterMVS - accuracy (78.96%)
IterMVS - completeness (48.27%)
IterMVS-LS
IterMVS-LS - accuracy (85.20%)
IterMVS-LS - completeness (55.66%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (79.61%)
IterMVS-SCA-FT - completeness (48.21%)
LGP-MVS_train
LGP-MVS_train - accuracy (97.35%)
LGP-MVS_train - completeness (55.62%)
LS3D
LS3D - accuracy (92.07%)
LS3D - completeness (45.95%)
LTVRE_ROB
LTVRE_ROB - accuracy (97.21%)
LTVRE_ROB - completeness (26.96%)
MAR-MVS
MAR-MVS - accuracy (88.89%)
MAR-MVS - completeness (67.98%)
MCST-MVS
MCST-MVS - accuracy (92.14%)
MCST-MVS - completeness (80.45%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (91.58%)
MDA-MVSNet-bldmvs - completeness (16.45%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (62.65%)
MDTV_nov1_ep13 - completeness (56.02%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (91.58%)
MDTV_nov1_ep13_2view - completeness (34.05%)
MIMVSNet
MIMVSNet - accuracy (82.38%)
MIMVSNet - completeness (40.77%)
MIMVSNet1
MIMVSNet1 - accuracy (96.10%)
MIMVSNet1 - completeness (26.53%)
MP-MVS
MP-MVS - accuracy (94.38%)
MP-MVS - completeness (77.13%)
mPP-MVS
mPP-MVS - accuracy (95.77%)
mPP-MVS - completeness (70.61%)
MS-PatchMatch
MS-PatchMatch - accuracy (75.70%)
MS-PatchMatch - completeness (58.34%)
MSDG
MSDG - accuracy (88.27%)
MSDG - completeness (41.10%)
MSLP-MVS++
MSLP-MVS++ - accuracy (93.57%)
MSLP-MVS++ - completeness (71.47%)
MSP-MVS
MSP-MVS - accuracy (96.08%)
MSP-MVS - completeness (83.21%)
MTAPA
MTAPA - accuracy (94.85%)
MTAPA - completeness (79.42%)
MTMP
MTMP - accuracy (95.16%)
MTMP - completeness (76.65%)
MVE
MVE - accuracy (73.80%)
MVE - completeness (2.42%)
MVS-HIRNet
MVS-HIRNet - accuracy (71.66%)
MVS-HIRNet - completeness (34.00%)
MVSTER
MVSTER - accuracy (56.72%)
MVSTER - completeness (72.80%)
MVS_0304
MVS_0304 - accuracy (93.35%)
MVS_0304 - completeness (75.52%)
MVS_111021_LR
MVS_111021_LR - accuracy (92.04%)
MVS_111021_LR - completeness (60.31%)
MVS_Test
MVS_Test - accuracy (90.78%)
MVS_Test - completeness (61.35%)
NCCC
NCCC - accuracy (92.39%)
NCCC - completeness (78.69%)
new-patchmatchnet
new-patchmatchnet - accuracy (96.41%)
new-patchmatchnet - completeness (21.54%)
new_pmnet
new_pmnet - accuracy (80.00%)
new_pmnet - completeness (17.64%)
NR-MVSNet
NR-MVSNet - accuracy (96.50%)
NR-MVSNet - completeness (33.85%)
N_pmnet
N_pmnet - accuracy (87.91%)
N_pmnet - completeness (25.93%)
OMC-MVS
OMC-MVS - accuracy (96.35%)
OMC-MVS - completeness (66.89%)
OpenMVS
OpenMVS - accuracy (82.33%)
OpenMVS - completeness (64.55%)
OPM-MVS
OPM-MVS - accuracy (97.29%)
OPM-MVS - completeness (60.14%)
PatchMatch-RL
PatchMatch-RL - accuracy (81.76%)
PatchMatch-RL - completeness (36.45%)
PatchmatchNet
PatchmatchNet - accuracy (59.09%)
PatchmatchNet - completeness (57.60%)
PatchT
PatchT - accuracy (54.12%)
PatchT - completeness (50.30%)
PCF-MVS
PCF-MVS - accuracy (90.40%)
PCF-MVS - completeness (69.18%)
PEN-MVS
PEN-MVS - accuracy (98.47%)
PEN-MVS - completeness (32.72%)
PGM-MVS
PGM-MVS - accuracy (95.26%)
PGM-MVS - completeness (72.11%)
PHI-MVS
PHI-MVS - accuracy (92.40%)
PHI-MVS - completeness (74.28%)
PLC
PLC - accuracy (90.05%)
PLC - completeness (55.31%)
PM-MVS
PM-MVS - accuracy (93.92%)
PM-MVS - completeness (26.05%)
pm-mvs1
pm-mvs1 - accuracy (95.99%)
pm-mvs1 - completeness (40.54%)
PMMVS
PMMVS - accuracy (78.39%)
PMMVS - completeness (58.56%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (93.20%)
pmmvs-eth3d - completeness (29.10%)
PMMVS2
PMMVS2 - accuracy (91.24%)
PMMVS2 - completeness (9.10%)
pmmvs3
pmmvs3 - accuracy (85.73%)
pmmvs3 - completeness (20.84%)
pmmvs5
pmmvs5 - accuracy (88.59%)
pmmvs5 - completeness (35.99%)
pmmvs6
pmmvs6 - accuracy (98.03%)
pmmvs6 - completeness (36.23%)
pmnet_mix02
pmnet_mix02 - accuracy (90.75%)
pmnet_mix02 - completeness (30.68%)
PMVS
PMVS - accuracy (92.22%)
PMVS - completeness (18.64%)
PS-CasMVS
PS-CasMVS - accuracy (98.37%)
PS-CasMVS - completeness (31.33%)
PVSNet_Blended
PVSNet_Blended - accuracy (88.96%)
PVSNet_Blended - completeness (58.27%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (88.96%)
PVSNet_BlendedMVS - completeness (58.27%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (83.44%)
PVSNet_Blended_VisFu - completeness (62.48%)
QAPM
QAPM - accuracy (85.44%)
QAPM - completeness (71.79%)
RPMNet
RPMNet - accuracy (47.51%)
RPMNet - completeness (53.04%)
RPSCF
RPSCF - accuracy (96.01%)
RPSCF - completeness (54.26%)
SCA
SCA - accuracy (60.96%)
SCA - completeness (59.45%)
SD-MVS
SD-MVS - accuracy (95.08%)
SD-MVS - completeness (84.84%)
SED-MVS
SED-MVS - accuracy (94.51%)
SED-MVS - completeness (87.07%)
SF-MVS
SF-MVS - accuracy (95.37%)
SF-MVS - completeness (83.29%)
SMA-MVS
SMA-MVS - accuracy (92.05%)
SMA-MVS - completeness (85.88%)
sosnet
sosnet - accuracy (0.00%)
sosnet - completeness (0.00%)
sosnet-low-res
sosnet-low-res - accuracy (0.00%)
sosnet-low-res - completeness (0.00%)
SR-MVS
SR-MVS - accuracy (95.53%)
SR-MVS - completeness (80.78%)
SteuartSystems-ACMMP
SteuartSystems-ACMMP - accuracy (94.67%)
SteuartSystems-ACMMP - completeness (77.19%)
TAMVS
TAMVS - accuracy (75.15%)
TAMVS - completeness (47.94%)
TAPA-MVS
TAPA-MVS - accuracy (93.71%)
TAPA-MVS - completeness (63.80%)
TDRefinement
TDRefinement - accuracy (96.01%)
TDRefinement - completeness (27.57%)
test-mter
test-mter - accuracy (60.47%)
test-mter - completeness (58.54%)
test1
test1 - accuracy (77.76%)
test1 - completeness (62.05%)
test123
test123 - accuracy (1.98%)
test123 - completeness (0.00%)
testgi
testgi - accuracy (95.19%)
testgi - completeness (31.98%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (58.91%)
TESTMET0.1,1 - completeness (61.65%)
testmvs
testmvs - accuracy (1.31%)
testmvs - completeness (0.01%)
test_part1
test_part1 - accuracy (98.62%)
test_part1 - completeness (53.91%)
thisisatest0515
thisisatest0515 - accuracy (89.25%)
thisisatest0515 - completeness (39.59%)
thisisatest0530
thisisatest0530 - accuracy (58.78%)
thisisatest0530 - completeness (58.48%)
TinyColmap
TinyColmap - accuracy (92.72%)
TinyColmap - completeness (20.97%)
tmp_tt
tmp_tt - accuracy (13.51%)
tmp_tt - completeness (22.83%)
tpm
tpm - accuracy (56.40%)
tpm - completeness (53.18%)
tpm cat1
tpm cat1 - accuracy (53.56%)
tpm cat1 - completeness (53.02%)
tpmrst
tpmrst - accuracy (56.49%)
tpmrst - completeness (54.15%)
train_agg
train_agg - accuracy (92.87%)
train_agg - completeness (82.24%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (97.55%)
TranMVSNet+NR-MVSNet - completeness (36.84%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (96.06%)
TransMVSNet (Re) - completeness (35.96%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (93.53%)
TSAR-MVS + ACMM - completeness (82.29%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (92.52%)
TSAR-MVS + COLMAP - completeness (51.62%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (87.67%)
TSAR-MVS + GP. - completeness (83.68%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (95.15%)
TSAR-MVS + MP. - completeness (82.99%)
tttt0517
tttt0517 - accuracy (58.79%)
tttt0517 - completeness (57.98%)
UA-Net
UA-Net - accuracy (88.90%)
UA-Net - completeness (71.32%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (89.63%)
UGNet - completeness (62.01%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (96.83%)
UniMVSNet (Re) - completeness (40.62%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (98.76%)
UniMVSNet_ETH3D - completeness (35.14%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (95.56%)
UniMVSNet_NR-MVSNet - completeness (41.12%)
USDC
USDC - accuracy (93.65%)
USDC - completeness (29.79%)
Vis-MVSNet
Vis-MVSNet - accuracy (91.48%)
Vis-MVSNet - completeness (58.43%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (80.63%)
Vis-MVSNet (Re-imp) - completeness (61.35%)
WR-MVS_H
WR-MVS_H - accuracy (98.01%)
WR-MVS_H - completeness (35.67%)
X-MVS
X-MVS - accuracy (94.53%)
X-MVS - completeness (72.27%)
X-MVStestdata
X-MVStestdata - accuracy (94.53%)
X-MVStestdata - completeness (72.27%)
XVS
XVS - accuracy (94.53%)
XVS - completeness (72.27%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (97.72%)
xxxxxxxxxxxxxcwj - completeness (44.71%)
zzz-MVS
zzz-MVS - accuracy (94.97%)
zzz-MVS - completeness (78.74%)
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
:
-1.39 to 15.61
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
:
11.8
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