+
−
⇧
i
D
T
pipes (high-res multi-view) - Tolerance 1cm
Ground Truth (full)
Ground Truth (dslr eval)
3Dnovator
3Dnovator - accuracy (77.73%)
3Dnovator - completeness (60.73%)
3Dnovator+
3Dnovator+ - accuracy (81.15%)
3Dnovator+ - completeness (61.47%)
9.14
9.14 - accuracy (83.64%)
9.14 - completeness (80.07%)
ACMH
ACMH - accuracy (95.83%)
ACMH - completeness (26.24%)
ACMH+
ACMH+ - accuracy (96.27%)
ACMH+ - completeness (29.46%)
ACMM
ACMM - accuracy (93.50%)
ACMM - completeness (46.07%)
ACMMP
ACMMP - accuracy (93.14%)
ACMMP - completeness (57.84%)
ACMMPR
ACMMPR - accuracy (92.04%)
ACMMPR - completeness (65.68%)
ACMMP_NAP
ACMMP_NAP - accuracy (87.34%)
ACMMP_NAP - completeness (74.61%)
ACMP
ACMP - accuracy (95.08%)
ACMP - completeness (46.31%)
AdaColmap
AdaColmap - accuracy (78.16%)
AdaColmap - completeness (47.64%)
ADS-MVSNet
ADS-MVSNet - accuracy (54.48%)
ADS-MVSNet - completeness (32.06%)
ambc
ambc - accuracy (92.41%)
ambc - completeness (7.54%)
Anonymous20231206
Anonymous20231206 - accuracy (79.80%)
Anonymous20231206 - completeness (27.50%)
Anonymous202405211
Anonymous202405211 - accuracy (86.16%)
Anonymous202405211 - completeness (46.77%)
anonymousdsp
anonymousdsp - accuracy (94.12%)
anonymousdsp - completeness (29.92%)
APD-MVS
APD-MVS - accuracy (89.82%)
APD-MVS - completeness (73.46%)
APDe-MVS
APDe-MVS - accuracy (91.27%)
APDe-MVS - completeness (76.08%)
baseline1
baseline1 - accuracy (58.99%)
baseline1 - completeness (51.09%)
baseline2
baseline2 - accuracy (50.01%)
baseline2 - completeness (44.15%)
Baseline_NR-MVSNet
Baseline_NR-MVSNet - accuracy (92.68%)
Baseline_NR-MVSNet - completeness (32.09%)
CANet
CANet - accuracy (84.37%)
CANet - completeness (66.47%)
CANet_DTU
CANet_DTU - accuracy (80.81%)
CANet_DTU - completeness (50.05%)
canonicalmvs
canonicalmvs - accuracy (86.38%)
canonicalmvs - completeness (61.68%)
casdiffmvs
casdiffmvs - accuracy (89.74%)
casdiffmvs - completeness (56.94%)
CDPH-MVS
CDPH-MVS - accuracy (88.90%)
CDPH-MVS - completeness (64.60%)
CDS-MVSNet
CDS-MVSNet - accuracy (70.53%)
CDS-MVSNet - completeness (42.26%)
CHOSEN 1792x2688
CHOSEN 1792x2688 - accuracy (66.49%)
CHOSEN 1792x2688 - completeness (44.76%)
CHOSEN 280x420
CHOSEN 280x420 - accuracy (48.65%)
CHOSEN 280x420 - completeness (45.59%)
CLD-MVS
CLD-MVS - accuracy (91.54%)
CLD-MVS - completeness (53.94%)
CMPMVS
CMPMVS - accuracy (80.00%)
CMPMVS - completeness (34.64%)
CNLPA
CNLPA - accuracy (86.23%)
CNLPA - completeness (45.42%)
CNVR-MVS
CNVR-MVS - accuracy (86.43%)
CNVR-MVS - completeness (76.48%)
COLMAP_ROB
COLMAP_ROB - accuracy (95.58%)
COLMAP_ROB - completeness (24.25%)
CostFormer
CostFormer - accuracy (51.37%)
CostFormer - completeness (57.89%)
CP-MVS
CP-MVS - accuracy (92.97%)
CP-MVS - completeness (64.96%)
CP-MVSNet
CP-MVSNet - accuracy (95.89%)
CP-MVSNet - completeness (25.82%)
CPTT-MVS
CPTT-MVS - accuracy (92.28%)
CPTT-MVS - completeness (59.90%)
CR-MVSNet
CR-MVSNet - accuracy (46.99%)
CR-MVSNet - completeness (42.53%)
CS-MVS
CS-MVS - accuracy (62.41%)
CS-MVS - completeness (58.61%)
CSCG
CSCG - accuracy (87.19%)
CSCG - completeness (77.42%)
CVMVSNet
CVMVSNet - accuracy (68.67%)
CVMVSNet - completeness (36.38%)
DCV-MVSNet
DCV-MVSNet - accuracy (88.57%)
DCV-MVSNet - completeness (47.87%)
DeepC-MVS
DeepC-MVS - accuracy (90.54%)
DeepC-MVS - completeness (65.63%)
DeepC-MVS_fast
DeepC-MVS_fast - accuracy (87.32%)
DeepC-MVS_fast - completeness (64.26%)
DeepMVS_CX
DeepMVS_CX - accuracy (19.33%)
DeepMVS_CX - completeness (3.16%)
DeepPCF-MVS
DeepPCF-MVS - accuracy (86.47%)
DeepPCF-MVS - completeness (76.19%)
DELS-MVS
DELS-MVS - accuracy (81.42%)
DELS-MVS - completeness (59.35%)
diffmvs
diffmvs - accuracy (87.55%)
diffmvs - completeness (55.60%)
DPE-MVS
DPE-MVS - accuracy (89.80%)
DPE-MVS - completeness (82.52%)
DPM-MVS
DPM-MVS - accuracy (77.02%)
DPM-MVS - completeness (76.16%)
dps
dps - accuracy (44.27%)
dps - completeness (32.71%)
DTE-MVSNet
DTE-MVSNet - accuracy (96.00%)
DTE-MVSNet - completeness (25.99%)
DU-MVS
DU-MVS - accuracy (93.49%)
DU-MVS - completeness (31.39%)
DVP-MVS
DVP-MVS - accuracy (89.02%)
DVP-MVS - completeness (83.77%)
E-PMN
E-PMN - accuracy (62.47%)
E-PMN - completeness (1.29%)
Effi-MVS+
Effi-MVS+ - accuracy (85.79%)
Effi-MVS+ - completeness (49.93%)
Effi-MVS+-dtu
Effi-MVS+-dtu - accuracy (84.78%)
Effi-MVS+-dtu - completeness (46.18%)
EG-PatchMatch MVS
EG-PatchMatch MVS - accuracy (86.88%)
EG-PatchMatch MVS - completeness (31.45%)
EIA-MVS
EIA-MVS - accuracy (62.23%)
EIA-MVS - completeness (51.93%)
EMVS
EMVS - accuracy (61.14%)
EMVS - completeness (1.36%)
EPMVS
EPMVS - accuracy (46.38%)
EPMVS - completeness (42.55%)
EPNet
EPNet - accuracy (70.91%)
EPNet - completeness (61.60%)
EPNet_dtu
EPNet_dtu - accuracy (72.27%)
EPNet_dtu - completeness (48.38%)
EPP-MVSNet
EPP-MVSNet - accuracy (69.65%)
EPP-MVSNet - completeness (56.19%)
ET-MVSNet_ETH3D
ET-MVSNet_ETH3D - accuracy (49.42%)
ET-MVSNet_ETH3D - completeness (46.20%)
ETV-MVS
ETV-MVS - accuracy (59.91%)
ETV-MVS - completeness (56.56%)
EU-MVSNet
EU-MVSNet - accuracy (83.42%)
EU-MVSNet - completeness (24.43%)
Fast-Effi-MVS+
Fast-Effi-MVS+ - accuracy (86.19%)
Fast-Effi-MVS+ - completeness (41.55%)
Fast-Effi-MVS+-dtu
Fast-Effi-MVS+-dtu - accuracy (78.42%)
Fast-Effi-MVS+-dtu - completeness (41.34%)
FC-MVSNet-test
FC-MVSNet-test - accuracy (77.41%)
FC-MVSNet-test - completeness (28.85%)
FC-MVSNet-train
FC-MVSNet-train - accuracy (88.23%)
FC-MVSNet-train - completeness (41.42%)
FMVSNet1
FMVSNet1 - accuracy (84.94%)
FMVSNet1 - completeness (42.06%)
FMVSNet2
FMVSNet2 - accuracy (75.55%)
FMVSNet2 - completeness (48.18%)
FMVSNet3
FMVSNet3 - accuracy (67.02%)
FMVSNet3 - completeness (51.42%)
FMVSNet5
FMVSNet5 - accuracy (44.57%)
FMVSNet5 - completeness (40.51%)
FPMVS
FPMVS - accuracy (75.07%)
FPMVS - completeness (14.69%)
GA-MVS
GA-MVS - accuracy (69.10%)
GA-MVS - completeness (36.40%)
GBi-Net
GBi-Net - accuracy (67.02%)
GBi-Net - completeness (51.42%)
GG-mvs-BLEND
GG-mvs-BLEND - accuracy (57.94%)
GG-mvs-BLEND - completeness (63.61%)
gg-mvs-nofinetune
gg-mvs-nofinetune - accuracy (53.88%)
gg-mvs-nofinetune - completeness (52.70%)
Gipuma
Gipuma - accuracy (93.07%)
Gipuma - completeness (2.73%)
gm-plane-assit
gm-plane-assit - accuracy (30.91%)
gm-plane-assit - completeness (35.32%)
HFP-MVS
HFP-MVS - accuracy (89.59%)
HFP-MVS - completeness (68.67%)
HPM-MVS++
HPM-MVS++ - accuracy (87.01%)
HPM-MVS++ - completeness (78.49%)
HQP-MVS
HQP-MVS - accuracy (88.07%)
HQP-MVS - completeness (58.75%)
HyFIR lowres test
HyFIR lowres test - accuracy (69.16%)
HyFIR lowres test - completeness (49.16%)
IB-MVS
IB-MVS - accuracy (79.14%)
IB-MVS - completeness (37.61%)
IS_MVSNet
IS_MVSNet - accuracy (74.54%)
IS_MVSNet - completeness (50.28%)
IterMVS
IterMVS - accuracy (70.23%)
IterMVS - completeness (40.05%)
IterMVS-LS
IterMVS-LS - accuracy (77.47%)
IterMVS-LS - completeness (47.05%)
IterMVS-SCA-FT
IterMVS-SCA-FT - accuracy (71.60%)
IterMVS-SCA-FT - completeness (39.88%)
LGP-MVS_train
LGP-MVS_train - accuracy (94.19%)
LGP-MVS_train - completeness (48.34%)
LS3D
LS3D - accuracy (87.44%)
LS3D - completeness (36.81%)
LTVRE_ROB
LTVRE_ROB - accuracy (91.04%)
LTVRE_ROB - completeness (21.34%)
MAR-MVS
MAR-MVS - accuracy (80.79%)
MAR-MVS - completeness (61.60%)
MCST-MVS
MCST-MVS - accuracy (86.20%)
MCST-MVS - completeness (73.30%)
MDA-MVSNet-bldmvs
MDA-MVSNet-bldmvs - accuracy (85.43%)
MDA-MVSNet-bldmvs - completeness (12.68%)
MDTV_nov1_ep13
MDTV_nov1_ep13 - accuracy (52.38%)
MDTV_nov1_ep13 - completeness (43.31%)
MDTV_nov1_ep13_2view
MDTV_nov1_ep13_2view - accuracy (84.10%)
MDTV_nov1_ep13_2view - completeness (27.89%)
MIMVSNet
MIMVSNet - accuracy (71.54%)
MIMVSNet - completeness (35.16%)
MIMVSNet1
MIMVSNet1 - accuracy (91.10%)
MIMVSNet1 - completeness (21.99%)
MP-MVS
MP-MVS - accuracy (90.76%)
MP-MVS - completeness (70.12%)
mPP-MVS
mPP-MVS - accuracy (92.12%)
mPP-MVS - completeness (62.34%)
MS-PatchMatch
MS-PatchMatch - accuracy (62.19%)
MS-PatchMatch - completeness (51.64%)
MSDG
MSDG - accuracy (78.96%)
MSDG - completeness (31.81%)
MSLP-MVS++
MSLP-MVS++ - accuracy (89.50%)
MSLP-MVS++ - completeness (61.66%)
MSP-MVS
MSP-MVS - accuracy (90.92%)
MSP-MVS - completeness (77.08%)
MTAPA
MTAPA - accuracy (90.53%)
MTAPA - completeness (71.98%)
MTMP
MTMP - accuracy (91.00%)
MTMP - completeness (68.31%)
MVE
MVE - accuracy (61.87%)
MVE - completeness (1.75%)
MVS-HIRNet
MVS-HIRNet - accuracy (60.04%)
MVS-HIRNet - completeness (28.39%)
MVSTER
MVSTER - accuracy (46.74%)
MVSTER - completeness (58.86%)
MVS_0304
MVS_0304 - accuracy (87.57%)
MVS_0304 - completeness (67.67%)
MVS_111021_LR
MVS_111021_LR - accuracy (84.98%)
MVS_111021_LR - completeness (49.27%)
MVS_Test
MVS_Test - accuracy (84.49%)
MVS_Test - completeness (56.16%)
NCCC
NCCC - accuracy (87.05%)
NCCC - completeness (71.08%)
new-patchmatchnet
new-patchmatchnet - accuracy (92.14%)
new-patchmatchnet - completeness (16.05%)
new_pmnet
new_pmnet - accuracy (64.73%)
new_pmnet - completeness (11.27%)
NR-MVSNet
NR-MVSNet - accuracy (91.13%)
NR-MVSNet - completeness (29.64%)
N_pmnet
N_pmnet - accuracy (76.67%)
N_pmnet - completeness (19.38%)
OMC-MVS
OMC-MVS - accuracy (92.49%)
OMC-MVS - completeness (54.15%)
OpenMVS
OpenMVS - accuracy (74.89%)
OpenMVS - completeness (56.51%)
OPM-MVS
OPM-MVS - accuracy (92.88%)
OPM-MVS - completeness (54.84%)
PatchMatch-RL
PatchMatch-RL - accuracy (69.77%)
PatchMatch-RL - completeness (27.43%)
PatchmatchNet
PatchmatchNet - accuracy (48.45%)
PatchmatchNet - completeness (42.54%)
PatchT
PatchT - accuracy (43.54%)
PatchT - completeness (36.93%)
PCF-MVS
PCF-MVS - accuracy (85.36%)
PCF-MVS - completeness (63.48%)
PEN-MVS
PEN-MVS - accuracy (96.59%)
PEN-MVS - completeness (26.67%)
PGM-MVS
PGM-MVS - accuracy (91.44%)
PGM-MVS - completeness (64.04%)
PHI-MVS
PHI-MVS - accuracy (87.50%)
PHI-MVS - completeness (65.39%)
PLC
PLC - accuracy (84.82%)
PLC - completeness (41.45%)
PM-MVS
PM-MVS - accuracy (86.97%)
PM-MVS - completeness (21.43%)
pm-mvs1
pm-mvs1 - accuracy (89.86%)
pm-mvs1 - completeness (34.96%)
PMMVS
PMMVS - accuracy (61.29%)
PMMVS - completeness (47.41%)
pmmvs-eth3d
pmmvs-eth3d - accuracy (85.78%)
pmmvs-eth3d - completeness (25.27%)
PMMVS2
PMMVS2 - accuracy (78.40%)
PMMVS2 - completeness (6.19%)
pmmvs3
pmmvs3 - accuracy (74.40%)
pmmvs3 - completeness (16.26%)
pmmvs5
pmmvs5 - accuracy (76.16%)
pmmvs5 - completeness (30.43%)
pmmvs6
pmmvs6 - accuracy (93.18%)
pmmvs6 - completeness (31.33%)
pmnet_mix02
pmnet_mix02 - accuracy (82.30%)
pmnet_mix02 - completeness (23.96%)
PMVS
PMVS - accuracy (87.94%)
PMVS - completeness (13.91%)
PS-CasMVS
PS-CasMVS - accuracy (96.76%)
PS-CasMVS - completeness (25.48%)
PVSNet_Blended
PVSNet_Blended - accuracy (78.84%)
PVSNet_Blended - completeness (49.39%)
PVSNet_BlendedMVS
PVSNet_BlendedMVS - accuracy (78.84%)
PVSNet_BlendedMVS - completeness (49.39%)
PVSNet_Blended_VisFu
PVSNet_Blended_VisFu - accuracy (73.46%)
PVSNet_Blended_VisFu - completeness (51.06%)
QAPM
QAPM - accuracy (77.78%)
QAPM - completeness (65.38%)
RPMNet
RPMNet - accuracy (37.23%)
RPMNet - completeness (37.61%)
RPSCF
RPSCF - accuracy (90.67%)
RPSCF - completeness (40.09%)
SCA
SCA - accuracy (49.97%)
SCA - completeness (43.82%)
SD-MVS
SD-MVS - accuracy (91.40%)
SD-MVS - completeness (75.37%)
SED-MVS
SED-MVS - accuracy (88.38%)
SED-MVS - completeness (84.02%)
SF-MVS
SF-MVS - accuracy (92.22%)
SF-MVS - completeness (77.90%)
SMA-MVS
SMA-MVS - accuracy (86.96%)
SMA-MVS - completeness (80.23%)
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 (91.11%)
SR-MVS - completeness (73.80%)
SteuartSystems-ACMMP
SteuartSystems-ACMMP - accuracy (90.71%)
SteuartSystems-ACMMP - completeness (69.10%)
TAMVS
TAMVS - accuracy (61.80%)
TAMVS - completeness (39.94%)
TAPA-MVS
TAPA-MVS - accuracy (88.04%)
TAPA-MVS - completeness (49.67%)
TDRefinement
TDRefinement - accuracy (93.01%)
TDRefinement - completeness (17.82%)
test-mter
test-mter - accuracy (49.52%)
test-mter - completeness (44.40%)
test1
test1 - accuracy (67.02%)
test1 - completeness (51.42%)
test123
test123 - accuracy (0.00%)
test123 - completeness (0.00%)
testgi
testgi - accuracy (87.59%)
testgi - completeness (26.55%)
TESTMET0.1,1
TESTMET0.1,1 - accuracy (47.02%)
TESTMET0.1,1 - completeness (48.87%)
testmvs
testmvs - accuracy (0.99%)
testmvs - completeness (0.00%)
test_part1
test_part1 - accuracy (95.21%)
test_part1 - completeness (49.96%)
thisisatest0515
thisisatest0515 - accuracy (79.79%)
thisisatest0515 - completeness (31.63%)
thisisatest0530
thisisatest0530 - accuracy (48.69%)
thisisatest0530 - completeness (44.14%)
TinyColmap
TinyColmap - accuracy (87.74%)
TinyColmap - completeness (13.72%)
tmp_tt
tmp_tt - accuracy (5.90%)
tmp_tt - completeness (9.04%)
tpm
tpm - accuracy (47.96%)
tpm - completeness (47.14%)
tpm cat1
tpm cat1 - accuracy (44.51%)
tpm cat1 - completeness (43.50%)
tpmrst
tpmrst - accuracy (47.04%)
tpmrst - completeness (45.45%)
train_agg
train_agg - accuracy (87.68%)
train_agg - completeness (73.15%)
TranMVSNet+NR-MVSNet
TranMVSNet+NR-MVSNet - accuracy (94.25%)
TranMVSNet+NR-MVSNet - completeness (31.60%)
TransMVSNet (Re)
TransMVSNet (Re) - accuracy (90.63%)
TransMVSNet (Re) - completeness (31.28%)
TSAR-MVS + ACMM
TSAR-MVS + ACMM - accuracy (89.17%)
TSAR-MVS + ACMM - completeness (75.03%)
TSAR-MVS + COLMAP
TSAR-MVS + COLMAP - accuracy (87.00%)
TSAR-MVS + COLMAP - completeness (42.03%)
TSAR-MVS + GP.
TSAR-MVS + GP. - accuracy (78.77%)
TSAR-MVS + GP. - completeness (72.33%)
TSAR-MVS + MP.
TSAR-MVS + MP. - accuracy (92.38%)
TSAR-MVS + MP. - completeness (75.22%)
tttt0517
tttt0517 - accuracy (48.90%)
tttt0517 - completeness (43.49%)
UA-Net
UA-Net - accuracy (82.09%)
UA-Net - completeness (58.72%)
uanet_test
uanet_test - accuracy (0.00%)
uanet_test - completeness (0.00%)
UGNet
UGNet - accuracy (80.65%)
UGNet - completeness (52.03%)
UniMVSNet (Re)
UniMVSNet (Re) - accuracy (93.21%)
UniMVSNet (Re) - completeness (34.54%)
UniMVSNet_ETH3D
UniMVSNet_ETH3D - accuracy (96.02%)
UniMVSNet_ETH3D - completeness (30.20%)
UniMVSNet_NR-MVSNet
UniMVSNet_NR-MVSNet - accuracy (91.54%)
UniMVSNet_NR-MVSNet - completeness (34.91%)
USDC
USDC - accuracy (86.88%)
USDC - completeness (20.87%)
Vis-MVSNet
Vis-MVSNet - accuracy (83.58%)
Vis-MVSNet - completeness (48.78%)
Vis-MVSNet (Re-imp)
Vis-MVSNet (Re-imp) - accuracy (71.41%)
Vis-MVSNet (Re-imp) - completeness (46.63%)
WR-MVS_H
WR-MVS_H - accuracy (95.84%)
WR-MVS_H - completeness (28.85%)
X-MVS
X-MVS - accuracy (90.19%)
X-MVS - completeness (63.42%)
X-MVStestdata
X-MVStestdata - accuracy (90.19%)
X-MVStestdata - completeness (63.42%)
XVS
XVS - accuracy (90.19%)
XVS - completeness (63.42%)
xxxxxxxxxxxxxcwj
xxxxxxxxxxxxxcwj - accuracy (95.06%)
xxxxxxxxxxxxxcwj - completeness (35.82%)
zzz-MVS
zzz-MVS - accuracy (90.74%)
zzz-MVS - completeness (71.51%)
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