+
−
⇧
i
D
T
relief_2 (high-res multi-view) - Tolerance 1cm
Height profile
Point number
:
-
Visualizations
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (75.61%)
3Dnovator - completeness (71.75%)
3Dnovator+
3Dnovator+ - accuracy (85.82%)
3Dnovator+ - completeness (66.75%)
ACMH
ACMH - accuracy (78.24%)
ACMH - completeness (63.80%)
ACMH+
ACMH+ - accuracy (83.39%)
ACMH+ - completeness (58.85%)
ACMM
ACMM - accuracy (89.42%)
ACMM - completeness (64.63%)
ACMMP
ACMMP - accuracy (89.36%)
ACMMP - completeness (66.46%)
ACMMPR
ACMMPR - accuracy (88.96%)
ACMMPR - completeness (69.12%)
ACMMP_NAP
ACMMP_NAP - accuracy (87.56%)
ACMMP_NAP - completeness (72.17%)
ACMP
ACMP - accuracy (87.43%)
ACMP - completeness (64.49%)
AdaColmap
AdaColmap - accuracy (82.20%)
AdaColmap - completeness (66.83%)
ADS-MVSNet
ADS-MVSNet - accuracy (39.23%)
ADS-MVSNet - completeness (55.19%)
ambc
ambc - accuracy (73.95%)
ambc - completeness (47.79%)
Anonymous20231206
Anonymous20231206 - accuracy (54.28%)
Anonymous20231206 - completeness (55.07%)
Anonymous202405211
Anonymous202405211 - accuracy (69.84%)
Anonymous202405211 - completeness (65.72%)
anonymousdsp
anonymousdsp - accuracy (86.95%)
anonymousdsp - completeness (58.98%)
APD-MVS
APD-MVS - accuracy (83.80%)
APD-MVS - completeness (69.66%)
APDe-MVS
APDe-MVS - accuracy (82.55%)
APDe-MVS - completeness (71.76%)
baseline1
baseline1 - accuracy (60.57%)
baseline1 - completeness (68.03%)
baseline2
baseline2 - accuracy (61.22%)
baseline2 - completeness (67.88%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (68.34%)
Baseline_NR-MVSNet - completeness (63.73%)
CANet
CANet - accuracy (77.64%)
CANet - completeness (69.90%)
CANet_DTU
CANet_DTU - accuracy (70.09%)
CANet_DTU - completeness (65.04%)
canonicalmvs
canonicalmvs - accuracy (71.85%)
canonicalmvs - completeness (69.67%)
casdiffmvs
casdiffmvs - accuracy (62.70%)
casdiffmvs - completeness (69.81%)
CDPH-MVS
CDPH-MVS - accuracy (82.54%)
CDPH-MVS - completeness (71.40%)
CDS-MVSNet
CDS-MVSNet - accuracy (73.02%)
CDS-MVSNet - completeness (61.71%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (59.81%)
CHOSEN 1792x2688 - completeness (77.61%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (55.31%)
CHOSEN 280x420 - completeness (54.00%)
CLD-MVS
CLD-MVS - accuracy (79.01%)
CLD-MVS - completeness (71.34%)
CMPMVS
CMPMVS - accuracy (64.10%)
CMPMVS - completeness (56.07%)
CNLPA
CNLPA - accuracy (83.29%)
CNLPA - completeness (53.66%)
CNVR-MVS
CNVR-MVS - accuracy (83.73%)
CNVR-MVS - completeness (75.75%)
COLMAP_ROB
COLMAP_ROB - accuracy (90.04%)
COLMAP_ROB - completeness (48.55%)
CostFormer
CostFormer - accuracy (51.18%)
CostFormer - completeness (67.79%)
CP-MVS
CP-MVS - accuracy (90.02%)
CP-MVS - completeness (67.57%)
CP-MVSNet
CP-MVSNet - accuracy (84.30%)
CP-MVSNet - completeness (48.82%)
CPTT-MVS
CPTT-MVS - accuracy (87.65%)
CPTT-MVS - completeness (61.26%)
CR-MVSNet
CR-MVSNet - accuracy (59.53%)
CR-MVSNet - completeness (61.11%)
CS-MVS
CS-MVS - accuracy (70.80%)
CS-MVS - completeness (69.49%)
CSCG
CSCG - accuracy (77.26%)
CSCG - completeness (77.18%)
CVMVSNet
CVMVSNet - accuracy (68.34%)
CVMVSNet - completeness (46.94%)
DCV-MVSNet
DCV-MVSNet - accuracy (70.35%)
DCV-MVSNet - completeness (65.17%)
DeepC-MVS
DeepC-MVS - accuracy (87.05%)
DeepC-MVS - completeness (71.33%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (84.37%)
DeepC-MVS_fast - completeness (70.85%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (84.16%)
DeepPCF-MVS - completeness (71.61%)
DELS-MVS
DELS-MVS - accuracy (71.35%)
DELS-MVS - completeness (74.78%)
diffmvs
diffmvs - accuracy (63.20%)
diffmvs - completeness (68.00%)
DPE-MVS
DPE-MVS - accuracy (82.91%)
DPE-MVS - completeness (72.98%)
DPM-MVS
DPM-MVS - accuracy (75.14%)
DPM-MVS - completeness (78.47%)
dps
dps - accuracy (51.97%)
dps - completeness (61.12%)
DTE-MVSNet
DTE-MVSNet - accuracy (82.52%)
DTE-MVSNet - completeness (50.80%)
DU-MVS
DU-MVS - accuracy (77.82%)
DU-MVS - completeness (59.98%)
DVP-MVS
DVP-MVS - accuracy (81.64%)
DVP-MVS - completeness (75.69%)
E-PMN
E-PMN - accuracy (39.51%)
E-PMN - completeness (13.59%)
Effi-MVS+
Effi-MVS+ - accuracy (76.41%)
Effi-MVS+ - completeness (67.06%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (80.38%)
Effi-MVS+-dtu - completeness (57.49%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (75.25%)
EG-PatchMatch MVS - completeness (66.51%)
EIA-MVS
EIA-MVS - accuracy (71.94%)
EIA-MVS - completeness (66.57%)
EMVS
EMVS - accuracy (38.52%)
EMVS - completeness (11.79%)
EPMVS
EPMVS - accuracy (39.47%)
EPMVS - completeness (60.90%)
EPNet
EPNet - accuracy (76.68%)
EPNet - completeness (68.07%)
EPNet_dtu
EPNet_dtu - accuracy (67.72%)
EPNet_dtu - completeness (58.38%)
EPP-MVSNet
EPP-MVSNet - accuracy (79.94%)
EPP-MVSNet - completeness (60.90%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (70.29%)
ET-MVSNet_ETH3D - completeness (66.99%)
ETV-MVS
ETV-MVS - accuracy (74.23%)
ETV-MVS - completeness (68.74%)
EU-MVSNet
EU-MVSNet - accuracy (63.19%)
EU-MVSNet - completeness (41.65%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (73.23%)
Fast-Effi-MVS+ - completeness (65.99%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (71.14%)
Fast-Effi-MVS+-dtu - completeness (62.34%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (73.08%)
FC-MVSNet-test - completeness (43.80%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (74.41%)
FC-MVSNet-train - completeness (63.22%)
FMVSNet1
FMVSNet1 - accuracy (68.45%)
FMVSNet1 - completeness (65.54%)
FMVSNet2
FMVSNet2 - accuracy (64.55%)
FMVSNet2 - completeness (67.95%)
FMVSNet3
FMVSNet3 - accuracy (61.96%)
FMVSNet3 - completeness (68.80%)
FMVSNet5
FMVSNet5 - accuracy (54.23%)
FMVSNet5 - completeness (55.81%)
FPMVS
FPMVS - accuracy (81.54%)
FPMVS - completeness (32.82%)
GA-MVS
GA-MVS - accuracy (63.63%)
GA-MVS - completeness (67.16%)
GBi-Net
GBi-Net - accuracy (68.45%)
GBi-Net - completeness (65.54%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (42.82%)
GG-mvs-BLEND - completeness (64.50%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (57.81%)
gg-mvs-nofinetune - completeness (72.93%)
Gipuma
Gipuma - accuracy (76.76%)
Gipuma - completeness (36.09%)
gm-plane-assit
gm-plane-assit - accuracy (54.71%)
gm-plane-assit - completeness (74.11%)
HFP-MVS
HFP-MVS - accuracy (88.83%)
HFP-MVS - completeness (69.23%)
HPM-MVS++
HPM-MVS++ - accuracy (85.27%)
HPM-MVS++ - completeness (73.31%)
HQP-MVS
HQP-MVS - accuracy (78.44%)
HQP-MVS - completeness (71.88%)
HyFIR lowres test
HyFIR lowres test - accuracy (67.18%)
HyFIR lowres test - completeness (68.71%)
IB-MVS
IB-MVS - accuracy (70.85%)
IB-MVS - completeness (69.81%)
IS_MVSNet
IS_MVSNet - accuracy (77.97%)
IS_MVSNet - completeness (63.84%)
IterMVS
IterMVS - accuracy (60.24%)
IterMVS - completeness (61.35%)
IterMVS-LS
IterMVS-LS - accuracy (69.36%)
IterMVS-LS - completeness (61.77%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (65.27%)
IterMVS-SCA-FT - completeness (58.17%)
LGP-MVS_train
LGP-MVS_train - accuracy (87.19%)
LGP-MVS_train - completeness (64.93%)
LS3D
LS3D - accuracy (82.08%)
LS3D - completeness (55.88%)
LTVRE_ROB
LTVRE_ROB - accuracy (90.29%)
LTVRE_ROB - completeness (48.11%)
MAR-MVS
MAR-MVS - accuracy (76.00%)
MAR-MVS - completeness (73.61%)
MCST-MVS
MCST-MVS - accuracy (74.06%)
MCST-MVS - completeness (77.43%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (67.40%)
MDA-MVSNet-bldmvs - completeness (48.05%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (49.70%)
MDTV_nov1_ep13 - completeness (62.11%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (54.69%)
MDTV_nov1_ep13_2view - completeness (56.43%)
MIMVSNet
MIMVSNet - accuracy (51.08%)
MIMVSNet - completeness (62.20%)
MIMVSNet1
MIMVSNet1 - accuracy (64.72%)
MIMVSNet1 - completeness (46.32%)
MP-MVS
MP-MVS - accuracy (89.30%)
MP-MVS - completeness (69.13%)
MS-PatchMatch
MS-PatchMatch - accuracy (63.17%)
MS-PatchMatch - completeness (70.65%)
MSDG
MSDG - accuracy (73.95%)
MSDG - completeness (62.55%)
MSLP-MVS++
MSLP-MVS++ - accuracy (85.74%)
MSLP-MVS++ - completeness (59.92%)
MSP-MVS
MSP-MVS - accuracy (81.64%)
MSP-MVS - completeness (75.69%)
MVE
MVE - accuracy (42.15%)
MVE - completeness (23.04%)
MVS-HIRNet
MVS-HIRNet - accuracy (41.08%)
MVS-HIRNet - completeness (55.00%)
MVSTER
MVSTER - accuracy (62.99%)
MVSTER - completeness (70.98%)
MVS_0304
MVS_0304 - accuracy (79.50%)
MVS_0304 - completeness (71.03%)
MVS_111021_LR
MVS_111021_LR - accuracy (77.77%)
MVS_111021_LR - completeness (60.54%)
MVS_Test
MVS_Test - accuracy (62.01%)
MVS_Test - completeness (71.11%)
NCCC
NCCC - accuracy (84.00%)
NCCC - completeness (73.70%)
new-patchmatchnet
new-patchmatchnet - accuracy (40.09%)
new-patchmatchnet - completeness (42.05%)
new_pmnet
new_pmnet - accuracy (44.91%)
new_pmnet - completeness (30.58%)
NR-MVSNet
NR-MVSNet - accuracy (76.75%)
NR-MVSNet - completeness (62.09%)
N_pmnet
N_pmnet - accuracy (36.69%)
N_pmnet - completeness (47.00%)
OMC-MVS
OMC-MVS - accuracy (85.11%)
OMC-MVS - completeness (57.59%)
OpenMVS
OpenMVS - accuracy (68.29%)
OpenMVS - completeness (68.96%)
OPM-MVS
OPM-MVS - accuracy (85.40%)
OPM-MVS - completeness (69.19%)
PatchMatch-RL
PatchMatch-RL - accuracy (72.49%)
PatchMatch-RL - completeness (50.55%)
PatchmatchNet
PatchmatchNet - accuracy (48.50%)
PatchmatchNet - completeness (60.88%)
PatchT
PatchT - accuracy (59.53%)
PatchT - completeness (61.11%)
PCF-MVS
PCF-MVS - accuracy (74.25%)
PCF-MVS - completeness (64.87%)
PEN-MVS
PEN-MVS - accuracy (82.35%)
PEN-MVS - completeness (52.38%)
PGM-MVS
PGM-MVS - accuracy (88.53%)
PGM-MVS - completeness (68.68%)
PHI-MVS
PHI-MVS - accuracy (78.48%)
PHI-MVS - completeness (70.57%)
PLC
PLC - accuracy (82.35%)
PLC - completeness (54.09%)
PM-MVS
PM-MVS - accuracy (74.75%)
PM-MVS - completeness (42.12%)
pm-mvs1
pm-mvs1 - accuracy (67.95%)
pm-mvs1 - completeness (60.42%)
PMMVS
PMMVS - accuracy (55.95%)
PMMVS - completeness (62.49%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (70.45%)
pmmvs-eth3d - completeness (56.62%)
PMMVS2
PMMVS2 - accuracy (38.31%)
PMMVS2 - completeness (21.13%)
pmmvs3
pmmvs3 - accuracy (56.64%)
pmmvs3 - completeness (47.39%)
pmmvs5
pmmvs5 - accuracy (57.07%)
pmmvs5 - completeness (60.28%)
pmmvs6
pmmvs6 - accuracy (71.13%)
pmmvs6 - completeness (56.67%)
pmnet_mix02
pmnet_mix02 - accuracy (41.22%)
pmnet_mix02 - completeness (53.76%)
PMVS
PMVS - accuracy (92.57%)
PMVS - completeness (31.72%)
PS-CasMVS
PS-CasMVS - accuracy (84.46%)
PS-CasMVS - completeness (48.71%)
PVSNet_Blended
PVSNet_Blended - accuracy (63.91%)
PVSNet_Blended - completeness (66.55%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (63.91%)
PVSNet_BlendedMVS - completeness (66.55%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (75.34%)
PVSNet_Blended_VisFu - completeness (65.38%)
QAPM
QAPM - accuracy (72.07%)
QAPM - completeness (70.76%)
RPMNet
RPMNet - accuracy (56.18%)
RPMNet - completeness (52.02%)
RPSCF
RPSCF - accuracy (89.74%)
RPSCF - completeness (37.05%)
SCA
SCA - accuracy (52.98%)
SCA - completeness (60.02%)
SD-MVS
SD-MVS - accuracy (88.32%)
SD-MVS - completeness (63.56%)
SED-MVS
SED-MVS - accuracy (81.28%)
SED-MVS - completeness (76.17%)
SF-MVS
SF-MVS - accuracy (80.28%)
SF-MVS - completeness (70.75%)
SMA-MVS
SMA-MVS - accuracy (87.59%)
SMA-MVS - completeness (74.09%)
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 (87.94%)
SteuartSystems-ACMMP - completeness (72.98%)
TAMVS
TAMVS - accuracy (58.33%)
TAMVS - completeness (57.58%)
TAPA-MVS
TAPA-MVS - accuracy (80.12%)
TAPA-MVS - completeness (54.64%)
TDRefinement
TDRefinement - accuracy (92.72%)
TDRefinement - completeness (47.24%)
test-mter
test-mter - accuracy (50.91%)
test-mter - completeness (61.68%)
test1
test1 - accuracy (68.45%)
test1 - completeness (65.54%)
test123
test123 - accuracy (0.61%)
test123 - completeness (0.01%)
testgi
testgi - accuracy (54.32%)
testgi - completeness (52.65%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (48.53%)
TESTMET0.1,1 - completeness (64.43%)
testmvs
testmvs - accuracy (0.54%)
testmvs - completeness (0.01%)
test_part1
test_part1 - accuracy (77.98%)
test_part1 - completeness (64.59%)
thisisatest0515
thisisatest0515 - accuracy (73.02%)
thisisatest0515 - completeness (61.71%)
thisisatest0530
thisisatest0530 - accuracy (71.10%)
thisisatest0530 - completeness (64.86%)
TinyColmap
TinyColmap - accuracy (70.42%)
TinyColmap - completeness (51.57%)
tmp_tt
tmp_tt - accuracy (21.51%)
tmp_tt - completeness (12.11%)
tpm
tpm - accuracy (42.76%)
tpm - completeness (61.67%)
tpm cat1
tpm cat1 - accuracy (47.49%)
tpm cat1 - completeness (62.64%)
tpmrst
tpmrst - accuracy (40.55%)
tpmrst - completeness (62.82%)
train_agg
train_agg - accuracy (81.85%)
train_agg - completeness (70.94%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (77.03%)
TranMVSNet+NR-MVSNet - completeness (62.53%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (67.98%)
TransMVSNet (Re) - completeness (62.70%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (88.10%)
TSAR-MVS + ACMM - completeness (63.42%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (79.61%)
TSAR-MVS + COLMAP - completeness (57.33%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (83.14%)
TSAR-MVS + GP. - completeness (66.66%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (83.10%)
TSAR-MVS + MP. - completeness (69.45%)
tttt0517
tttt0517 - accuracy (71.10%)
tttt0517 - completeness (64.86%)
UA-Net
UA-Net - accuracy (90.93%)
UA-Net - completeness (53.40%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (77.99%)
UGNet - completeness (59.62%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (78.33%)
UniMVSNet (Re) - completeness (59.90%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (77.30%)
UniMVSNet_ETH3D - completeness (56.30%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (76.32%)
UniMVSNet_NR-MVSNet - completeness (62.70%)
USDC
USDC - accuracy (65.62%)
USDC - completeness (57.16%)
Vis-MVSNet
Vis-MVSNet - accuracy (80.11%)
Vis-MVSNet - completeness (61.80%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (71.28%)
Vis-MVSNet (Re-imp) - completeness (57.03%)
WR-MVS_H
WR-MVS_H - accuracy (84.37%)
WR-MVS_H - completeness (47.99%)
X-MVS
X-MVS - accuracy (88.87%)
X-MVS - completeness (68.50%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (80.28%)
xxxxxxxxxxxxxcwj - completeness (70.75%)
zzz-MVS
zzz-MVS - accuracy (89.71%)
zzz-MVS - completeness (68.63%)
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
:
-5.79 to 68.90
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
:
62.8
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