+
−
⇧
i
D
T
playground (high-res multi-view) - Tolerance 5cm
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (88.14%)
3Dnovator - completeness (88.98%)
3Dnovator+
3Dnovator+ - accuracy (91.90%)
3Dnovator+ - completeness (89.46%)
ACMH
ACMH - accuracy (93.23%)
ACMH - completeness (77.24%)
ACMH+
ACMH+ - accuracy (94.10%)
ACMH+ - completeness (76.90%)
ACMM
ACMM - accuracy (95.11%)
ACMM - completeness (82.59%)
ACMMP
ACMMP - accuracy (94.51%)
ACMMP - completeness (86.29%)
ACMMPR
ACMMPR - accuracy (94.92%)
ACMMPR - completeness (89.71%)
ACMMP_NAP
ACMMP_NAP - accuracy (92.49%)
ACMMP_NAP - completeness (90.39%)
ACMP
ACMP - accuracy (94.68%)
ACMP - completeness (80.48%)
AdaColmap
AdaColmap - accuracy (90.62%)
AdaColmap - completeness (92.00%)
ADS-MVSNet
ADS-MVSNet - accuracy (68.55%)
ADS-MVSNet - completeness (73.80%)
ambc
ambc - accuracy (91.26%)
ambc - completeness (41.57%)
Anonymous20231206
Anonymous20231206 - accuracy (72.48%)
Anonymous20231206 - completeness (43.90%)
Anonymous202405211
Anonymous202405211 - accuracy (81.74%)
Anonymous202405211 - completeness (84.57%)
anonymousdsp
anonymousdsp - accuracy (96.11%)
anonymousdsp - completeness (62.84%)
APD-MVS
APD-MVS - accuracy (92.97%)
APD-MVS - completeness (92.81%)
APDe-MVS
APDe-MVS - accuracy (93.84%)
APDe-MVS - completeness (92.93%)
baseline1
baseline1 - accuracy (75.79%)
baseline1 - completeness (80.01%)
baseline2
baseline2 - accuracy (80.14%)
baseline2 - completeness (74.67%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (90.64%)
Baseline_NR-MVSNet - completeness (68.45%)
CANet
CANet - accuracy (86.25%)
CANet - completeness (88.42%)
CANet_DTU
CANet_DTU - accuracy (76.27%)
CANet_DTU - completeness (85.62%)
canonicalmvs
canonicalmvs - accuracy (88.80%)
canonicalmvs - completeness (87.80%)
casdiffmvs
casdiffmvs - accuracy (86.60%)
casdiffmvs - completeness (85.57%)
CDPH-MVS
CDPH-MVS - accuracy (91.05%)
CDPH-MVS - completeness (83.82%)
CDS-MVSNet
CDS-MVSNet - accuracy (69.11%)
CDS-MVSNet - completeness (66.91%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (86.92%)
CHOSEN 1792x2688 - completeness (76.52%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (81.19%)
CHOSEN 280x420 - completeness (80.99%)
CLD-MVS
CLD-MVS - accuracy (85.83%)
CLD-MVS - completeness (86.02%)
CMPMVS
CMPMVS - accuracy (82.12%)
CMPMVS - completeness (63.74%)
CNLPA
CNLPA - accuracy (90.35%)
CNLPA - completeness (88.14%)
CNVR-MVS
CNVR-MVS - accuracy (91.20%)
CNVR-MVS - completeness (94.03%)
COLMAP_ROB
COLMAP_ROB - accuracy (95.28%)
COLMAP_ROB - completeness (65.87%)
CostFormer
CostFormer - accuracy (76.62%)
CostFormer - completeness (79.93%)
CP-MVS
CP-MVS - accuracy (94.54%)
CP-MVS - completeness (89.43%)
CP-MVSNet
CP-MVSNet - accuracy (92.83%)
CP-MVSNet - completeness (53.54%)
CPTT-MVS
CPTT-MVS - accuracy (94.98%)
CPTT-MVS - completeness (88.45%)
CR-MVSNet
CR-MVSNet - accuracy (84.86%)
CR-MVSNet - completeness (70.77%)
CS-MVS
CS-MVS - accuracy (90.30%)
CS-MVS - completeness (87.23%)
CSCG
CSCG - accuracy (93.01%)
CSCG - completeness (84.75%)
CVMVSNet
CVMVSNet - accuracy (89.87%)
CVMVSNet - completeness (54.03%)
DCV-MVSNet
DCV-MVSNet - accuracy (83.90%)
DCV-MVSNet - completeness (80.99%)
DeepC-MVS
DeepC-MVS - accuracy (93.69%)
DeepC-MVS - completeness (88.24%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (90.49%)
DeepC-MVS_fast - completeness (92.42%)
DeepMVS_CX
DeepMVS_CX - accuracy (66.91%)
DeepMVS_CX - completeness (41.60%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (93.21%)
DeepPCF-MVS - completeness (87.29%)
DELS-MVS
DELS-MVS - accuracy (85.71%)
DELS-MVS - completeness (82.84%)
diffmvs
diffmvs - accuracy (83.33%)
diffmvs - completeness (83.84%)
DPE-MVS
DPE-MVS - accuracy (92.98%)
DPE-MVS - completeness (93.56%)
DPM-MVS
DPM-MVS - accuracy (85.75%)
DPM-MVS - completeness (91.21%)
dps
dps - accuracy (80.20%)
dps - completeness (76.81%)
DTE-MVSNet
DTE-MVSNet - accuracy (92.77%)
DTE-MVSNet - completeness (49.48%)
DU-MVS
DU-MVS - accuracy (91.19%)
DU-MVS - completeness (71.61%)
DVP-MVS
DVP-MVS - accuracy (93.89%)
DVP-MVS - completeness (92.93%)
E-PMN
E-PMN - accuracy (78.75%)
E-PMN - completeness (21.77%)
Effi-MVS+
Effi-MVS+ - accuracy (89.99%)
Effi-MVS+ - completeness (83.37%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (89.24%)
Effi-MVS+-dtu - completeness (75.84%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (93.31%)
EG-PatchMatch MVS - completeness (54.04%)
EIA-MVS
EIA-MVS - accuracy (89.93%)
EIA-MVS - completeness (85.16%)
EMVS
EMVS - accuracy (78.22%)
EMVS - completeness (22.03%)
EPMVS
EPMVS - accuracy (72.03%)
EPMVS - completeness (76.97%)
EPNet
EPNet - accuracy (77.79%)
EPNet - completeness (84.45%)
EPNet_dtu
EPNet_dtu - accuracy (75.39%)
EPNet_dtu - completeness (53.98%)
EPP-MVSNet
EPP-MVSNet - accuracy (91.60%)
EPP-MVSNet - completeness (74.33%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (84.29%)
ET-MVSNet_ETH3D - completeness (89.99%)
ETV-MVS
ETV-MVS - accuracy (90.26%)
ETV-MVS - completeness (87.38%)
EU-MVSNet
EU-MVSNet - accuracy (93.26%)
EU-MVSNet - completeness (39.07%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (90.67%)
Fast-Effi-MVS+ - completeness (82.99%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (82.00%)
Fast-Effi-MVS+-dtu - completeness (73.59%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (78.78%)
FC-MVSNet-test - completeness (41.17%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (77.57%)
FC-MVSNet-train - completeness (80.29%)
FMVSNet1
FMVSNet1 - accuracy (81.85%)
FMVSNet1 - completeness (76.98%)
FMVSNet2
FMVSNet2 - accuracy (78.54%)
FMVSNet2 - completeness (80.99%)
FMVSNet3
FMVSNet3 - accuracy (77.07%)
FMVSNet3 - completeness (82.34%)
FMVSNet5
FMVSNet5 - accuracy (63.87%)
FMVSNet5 - completeness (73.85%)
FPMVS
FPMVS - accuracy (86.96%)
FPMVS - completeness (35.94%)
GA-MVS
GA-MVS - accuracy (83.53%)
GA-MVS - completeness (70.07%)
GBi-Net
GBi-Net - accuracy (78.54%)
GBi-Net - completeness (80.99%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (0.62%)
GG-mvs-BLEND - completeness (0.19%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (68.05%)
gg-mvs-nofinetune - completeness (76.37%)
Gipuma
Gipuma - accuracy (94.71%)
Gipuma - completeness (26.44%)
gm-plane-assit
gm-plane-assit - accuracy (78.60%)
gm-plane-assit - completeness (71.97%)
HFP-MVS
HFP-MVS - accuracy (93.89%)
HFP-MVS - completeness (91.19%)
HPM-MVS++
HPM-MVS++ - accuracy (92.94%)
HPM-MVS++ - completeness (92.29%)
HQP-MVS
HQP-MVS - accuracy (89.47%)
HQP-MVS - completeness (84.80%)
HyFIR lowres test
HyFIR lowres test - accuracy (88.64%)
HyFIR lowres test - completeness (78.97%)
IB-MVS
IB-MVS - accuracy (83.96%)
IB-MVS - completeness (58.37%)
IS_MVSNet
IS_MVSNet - accuracy (88.86%)
IS_MVSNet - completeness (67.39%)
IterMVS
IterMVS - accuracy (87.01%)
IterMVS - completeness (65.03%)
IterMVS-LS
IterMVS-LS - accuracy (87.76%)
IterMVS-LS - completeness (74.88%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (91.36%)
IterMVS-SCA-FT - completeness (63.95%)
LGP-MVS_train
LGP-MVS_train - accuracy (95.01%)
LGP-MVS_train - completeness (79.59%)
LS3D
LS3D - accuracy (91.52%)
LS3D - completeness (83.72%)
LTVRE_ROB
LTVRE_ROB - accuracy (95.74%)
LTVRE_ROB - completeness (70.57%)
MAR-MVS
MAR-MVS - accuracy (86.86%)
MAR-MVS - completeness (88.55%)
MCST-MVS
MCST-MVS - accuracy (91.69%)
MCST-MVS - completeness (92.24%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (89.10%)
MDA-MVSNet-bldmvs - completeness (54.11%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (78.41%)
MDTV_nov1_ep13 - completeness (73.05%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (83.70%)
MDTV_nov1_ep13_2view - completeness (59.87%)
MIMVSNet
MIMVSNet - accuracy (64.85%)
MIMVSNet - completeness (67.48%)
MIMVSNet1
MIMVSNet1 - accuracy (78.44%)
MIMVSNet1 - completeness (34.47%)
MP-MVS
MP-MVS - accuracy (94.59%)
MP-MVS - completeness (88.27%)
MS-PatchMatch
MS-PatchMatch - accuracy (84.93%)
MS-PatchMatch - completeness (70.66%)
MSDG
MSDG - accuracy (88.48%)
MSDG - completeness (77.61%)
MSLP-MVS++
MSLP-MVS++ - accuracy (93.27%)
MSLP-MVS++ - completeness (89.71%)
MSP-MVS
MSP-MVS - accuracy (90.73%)
MSP-MVS - completeness (94.76%)
MVE
MVE - accuracy (80.66%)
MVE - completeness (14.38%)
MVS-HIRNet
MVS-HIRNet - accuracy (77.74%)
MVS-HIRNet - completeness (66.97%)
MVSTER
MVSTER - accuracy (76.84%)
MVSTER - completeness (84.89%)
MVS_0304
MVS_0304 - accuracy (88.12%)
MVS_0304 - completeness (87.03%)
MVS_111021_LR
MVS_111021_LR - accuracy (90.64%)
MVS_111021_LR - completeness (85.49%)
MVS_Test
MVS_Test - accuracy (83.97%)
MVS_Test - completeness (86.99%)
NCCC
NCCC - accuracy (91.84%)
NCCC - completeness (92.53%)
new-patchmatchnet
new-patchmatchnet - accuracy (58.61%)
new-patchmatchnet - completeness (36.69%)
new_pmnet
new_pmnet - accuracy (56.16%)
new_pmnet - completeness (44.89%)
NR-MVSNet
NR-MVSNet - accuracy (82.85%)
NR-MVSNet - completeness (64.27%)
N_pmnet
N_pmnet - accuracy (59.14%)
N_pmnet - completeness (52.25%)
OMC-MVS
OMC-MVS - accuracy (91.34%)
OMC-MVS - completeness (86.59%)
OpenMVS
OpenMVS - accuracy (86.69%)
OpenMVS - completeness (84.45%)
OPM-MVS
OPM-MVS - accuracy (92.89%)
OPM-MVS - completeness (85.03%)
PatchMatch-RL
PatchMatch-RL - accuracy (89.85%)
PatchMatch-RL - completeness (82.55%)
PatchmatchNet
PatchmatchNet - accuracy (81.90%)
PatchmatchNet - completeness (74.56%)
PatchT
PatchT - accuracy (84.86%)
PatchT - completeness (70.77%)
PCF-MVS
PCF-MVS - accuracy (89.24%)
PCF-MVS - completeness (85.55%)
PEN-MVS
PEN-MVS - accuracy (92.27%)
PEN-MVS - completeness (52.36%)
PGM-MVS
PGM-MVS - accuracy (94.63%)
PGM-MVS - completeness (88.93%)
PHI-MVS
PHI-MVS - accuracy (90.67%)
PHI-MVS - completeness (84.89%)
PLC
PLC - accuracy (91.61%)
PLC - completeness (88.41%)
PM-MVS
PM-MVS - accuracy (92.35%)
PM-MVS - completeness (62.89%)
pm-mvs1
pm-mvs1 - accuracy (82.80%)
pm-mvs1 - completeness (61.81%)
PMMVS
PMMVS - accuracy (79.70%)
PMMVS - completeness (84.70%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (88.29%)
pmmvs-eth3d - completeness (62.43%)
PMMVS2
PMMVS2 - accuracy (25.43%)
PMMVS2 - completeness (12.45%)
pmmvs3
pmmvs3 - accuracy (77.69%)
pmmvs3 - completeness (53.02%)
pmmvs5
pmmvs5 - accuracy (79.87%)
pmmvs5 - completeness (67.61%)
pmmvs6
pmmvs6 - accuracy (84.40%)
pmmvs6 - completeness (58.75%)
pmnet_mix02
pmnet_mix02 - accuracy (75.42%)
pmnet_mix02 - completeness (53.97%)
PMVS
PMVS - accuracy (92.39%)
PMVS - completeness (25.29%)
PS-CasMVS
PS-CasMVS - accuracy (92.91%)
PS-CasMVS - completeness (52.56%)
PVSNet_Blended
PVSNet_Blended - accuracy (84.69%)
PVSNet_Blended - completeness (80.73%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (84.69%)
PVSNet_BlendedMVS - completeness (80.73%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (90.72%)
PVSNet_Blended_VisFu - completeness (70.35%)
QAPM
QAPM - accuracy (88.74%)
QAPM - completeness (87.01%)
RPMNet
RPMNet - accuracy (82.79%)
RPMNet - completeness (66.31%)
RPSCF
RPSCF - accuracy (93.63%)
RPSCF - completeness (73.89%)
SCA
SCA - accuracy (85.80%)
SCA - completeness (73.73%)
SD-MVS
SD-MVS - accuracy (93.91%)
SD-MVS - completeness (89.78%)
SED-MVS
SED-MVS - accuracy (90.69%)
SED-MVS - completeness (95.08%)
SF-MVS
SF-MVS - accuracy (91.11%)
SF-MVS - completeness (92.76%)
SMA-MVS
SMA-MVS - accuracy (92.28%)
SMA-MVS - completeness (91.49%)
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 (94.99%)
SteuartSystems-ACMMP - completeness (88.95%)
TAMVS
TAMVS - accuracy (69.11%)
TAMVS - completeness (66.91%)
TAPA-MVS
TAPA-MVS - accuracy (91.05%)
TAPA-MVS - completeness (85.47%)
TDRefinement
TDRefinement - accuracy (96.06%)
TDRefinement - completeness (60.87%)
test-mter
test-mter - accuracy (76.44%)
test-mter - completeness (71.36%)
test1
test1 - accuracy (78.54%)
test1 - completeness (80.99%)
test123
test123 - accuracy (1.64%)
test123 - completeness (0.61%)
testgi
testgi - accuracy (60.66%)
testgi - completeness (40.95%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (73.88%)
TESTMET0.1,1 - completeness (73.10%)
testmvs
testmvs - accuracy (1.55%)
testmvs - completeness (0.60%)
test_part1
test_part1 - accuracy (90.49%)
test_part1 - completeness (75.29%)
thisisatest0515
thisisatest0515 - accuracy (90.62%)
thisisatest0515 - completeness (58.10%)
thisisatest0530
thisisatest0530 - accuracy (88.21%)
thisisatest0530 - completeness (73.02%)
TinyColmap
TinyColmap - accuracy (88.37%)
TinyColmap - completeness (74.45%)
tmp_tt
tmp_tt - accuracy (9.55%)
tmp_tt - completeness (15.28%)
tpm
tpm - accuracy (74.54%)
tpm - completeness (72.31%)
tpm cat1
tpm cat1 - accuracy (77.37%)
tpm cat1 - completeness (75.74%)
tpmrst
tpmrst - accuracy (74.54%)
tpmrst - completeness (77.25%)
train_agg
train_agg - accuracy (92.31%)
train_agg - completeness (88.38%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (90.82%)
TranMVSNet+NR-MVSNet - completeness (67.55%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (82.21%)
TransMVSNet (Re) - completeness (55.97%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (93.55%)
TSAR-MVS + ACMM - completeness (84.40%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (88.60%)
TSAR-MVS + COLMAP - completeness (86.71%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (92.85%)
TSAR-MVS + GP. - completeness (90.07%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (93.92%)
TSAR-MVS + MP. - completeness (92.15%)
tttt0517
tttt0517 - accuracy (88.21%)
tttt0517 - completeness (73.02%)
UA-Net
UA-Net - accuracy (94.31%)
UA-Net - completeness (57.54%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (76.84%)
UGNet - completeness (58.93%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (91.38%)
UniMVSNet (Re) - completeness (63.85%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (88.01%)
UniMVSNet_ETH3D - completeness (71.38%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (91.19%)
UniMVSNet_NR-MVSNet - completeness (71.61%)
USDC
USDC - accuracy (86.46%)
USDC - completeness (76.47%)
Vis-MVSNet
Vis-MVSNet - accuracy (90.60%)
Vis-MVSNet - completeness (57.00%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (82.72%)
Vis-MVSNet (Re-imp) - completeness (54.28%)
WR-MVS_H
WR-MVS_H - accuracy (92.97%)
WR-MVS_H - completeness (43.99%)
X-MVS
X-MVS - accuracy (91.87%)
X-MVS - completeness (86.51%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (91.11%)
xxxxxxxxxxxxxcwj - completeness (92.76%)
zzz-MVS
zzz-MVS - accuracy (94.30%)
zzz-MVS - completeness (89.89%)
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
:
0.00 to 1.00
Transition
transition:
Intensity
Range:
0 to 300
Gamma:
1.00
Brightness:
0.00
Contrast:
0.00
:
1,000,000
:
1.00
:
60
:
1.00
Point Sizing
Fixed
Attenuated
Adaptive
Adaptive
Squares
Circles
Interpolation
Squares
Eye-Dome-Lighting
:
1.4
:
1.0
Background
Gradient
Black
White
Navigation
:
0.4
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