\begin{tabular}{c | c | c | c | c | c}
{\bf Method} & {\bf Fl-bg} & {\bf Fl-fg} & {\bf Fl-all} & {\bf Density} & {\bf Runtime}\\ \hline
UberATG-DRISF \cite{Ma2019CVPR} & 3.59 \% & 10.40 \% & 4.73 \% & 100.00 \% & 0.75 s / CPU+GPU \\
RAFT \cite{ECCV2020teedraft} & 4.74 \% & 6.87 \% & 5.10 \% & 100.00 \% & 0.2 s / GPU \\
PRAFlow\_RVC \cite{wan2020praflowrvc} & 5.08 \% & 7.21 \% & 5.43 \% & 100.00 \% & 0.5 s / GPU \\
RAFT-TF\_RVC \cite{sun2020tfraft} & 5.32 \% & 6.75 \% & 5.56 \% & 100.00 \% & 0.7 s / GPU \\
ACOSF \cite{Cong2020ICPR} & 4.56 \% & 12.00 \% & 5.79 \% & 100.00 \% & 5 min / 1 core \\
PPAC-HD3 \cite{Wannenwetsch2020PPA} & 5.78 \% & 7.48 \% & 6.06 \% & 100.00 \% & 0.19 s / \\
MaskFlownet \cite{zhao2020maskflownet} & 5.79 \% & 7.70 \% & 6.11 \% & 100.00 \% & 0.06 s / \\
ISF \cite{Behl2017ICCV} & 5.40 \% & 10.29 \% & 6.22 \% & 100.00 \% & 10 min / 1 core \\
VCN+LCV \cite{Xiao2018ECCV} & 5.75 \% & 8.80 \% & 6.25 \% & 100.00 \% & 0.26 s / 1 core \\
RAFT+LCV \cite{Xiao2018ECCV} & 5.73 \% & 8.90 \% & 6.26 \% & 100.00 \% & 0.1 s / 1 core \\
VCN \cite{yang2019vcn} & 5.83 \% & 8.66 \% & 6.30 \% & 100.00 \% & 0.18 s / \\
Stereo expansion \cite{yang2020upgrading} & 5.83 \% & 8.66 \% & 6.30 \% & 100.00 \% & 2 s / GPU \\
HD^3-Flow \cite{yin2019hd3} & 6.05 \% & 9.02 \% & 6.55 \% & 100.00 \% & 0.10 s / \\
PRSM \cite{Vogel2015IJCV} & 5.33 \% & 13.40 \% & 6.68 \% & 100.00 \% & 300 s / 1 core \\
RichFlow \cite{ERROR: Wrong syntax in BIBTEX file.} & 6.62 \% & 6.98 \% & 6.68 \% & 100.00 \% & 0.13 s / \\
MaskFlownet-S \cite{zhao2020maskflownet} & 6.53 \% & 8.21 \% & 6.81 \% & 100.00 \% & 0.03 s / \\
ScopeFlow \cite{BarHaim2020CVPR} & 6.72 \% & 7.36 \% & 6.82 \% & 100.00 \% & -1 s / \\
OSF+TC \cite{Neoral2017CVWW} & 5.76 \% & 13.31 \% & 7.02 \% & 100.00 \% & 50 min / 1 core \\
SSF \cite{Ren20173DV} & 5.63 \% & 14.71 \% & 7.14 \% & 100.00 \% & 5 min / 1 core \\
MFF \cite{ren2018fusion} & 7.15 \% & 7.25 \% & 7.17 \% & 100.00 \% & 0.05 s / \\
LiteFlowNet3-S \cite{hui20liteflownet3} & 7.27 \% & 6.96 \% & 7.22 \% & 100.00 \% & 0.07s / \\
SwiftFlow \cite{wang2020atg} & 6.85 \% & 9.11 \% & 7.23 \% & 100.00 \% & 0.03 s / GPU \\
LiteFlowNet3 \cite{hui20liteflownet3} & 7.26 \% & 7.75 \% & 7.34 \% & 100.00 \% & 0.07s / \\
OSF 2018 \cite{Menze2018JPRS} & 5.38 \% & 17.61 \% & 7.41 \% & 100.00 \% & 390 s / 1 core \\
LiteFlowNet2 \cite{hui19liteflownet2} & 7.62 \% & 7.64 \% & 7.62 \% & 100.00 \% & 0.0486 s / \\
SENSE \cite{Jiang2019ICCV} & 7.30 \% & 9.33 \% & 7.64 \% & 100.00 \% & 0.32s / \\
IRR-PWC \cite{Hur2019CVPR} & 7.68 \% & 7.52 \% & 7.65 \% & 100.00 \% & 0.18 s / \\
STaRFlow \cite{godet2020starflow} & 7.51 \% & 8.35 \% & 7.65 \% & 100.00 \% & 0.24 s / GPU \\
PWC-Net+ \cite{sun2018models} & 7.69 \% & 7.88 \% & 7.72 \% & 100.00 \% & 0.03 s / \\
OSF \cite{Menze2015CVPR} & 5.62 \% & 18.92 \% & 7.83 \% & 100.00 \% & 50 min / 1 core \\
LSM\_FLOW\_RVC \cite{Tang2020CVPR} & 7.33 \% & 13.06 \% & 8.28 \% & 100.00 \% & 0.2 s / 1 core \\
IRR-PWC\_RVC \cite{Hur2019CVPR} & 7.61 \% & 12.22 \% & 8.38 \% & 100.00 \% & 0.18 s / \\
SelFlow \cite{Liu2019SelFlow} & 7.61 \% & 12.48 \% & 8.42 \% & 100.00 \% & 0.09 s / GPU \\
FDFlowNet \cite{kong2020fdflownet} & 9.31 \% & 9.71 \% & 9.38 \% & 100.00 \% & 0.02 s / \\
LiteFlowNet \cite{hui18liteflownet} & 9.66 \% & 7.99 \% & 9.38 \% & 100.00 \% & 0.0885 s / \\
PWC-Net \cite{Sun2018PWCNet} & 9.66 \% & 9.31 \% & 9.60 \% & 100.00 \% & 0.03 s / \\
ContinualFlow\_ROB \cite{Neoral2018ACCV} & 8.54 \% & 17.48 \% & 10.03 \% & 100.00 \% & 0.15 s / \\
VCN\_RVC \cite{yang2019vcn} & 8.53 \% & 18.30 \% & 10.15 \% & 100.00 \% & 0.36 s / GPU \\
MirrorFlow \cite{Hur2017ICCV} & 8.93 \% & 17.07 \% & 10.29 \% & 100.00 \% & 11 min / 4 core \\
DWARF \cite{AleottiAAAI2020} & 9.80 \% & 13.37 \% & 10.39 \% & 100.00 \% & 0.14s - 1.43s / \\
FlowNet2 \cite{IMSKDB17} & 10.75 \% & 8.75 \% & 10.41 \% & 100.00 \% & 0.1 s / GPU \\
SDF \cite{Bai2016ECCV} & 8.61 \% & 23.01 \% & 11.01 \% & 100.00 \% & TBA / 1 core \\
Flow2Stereo \cite{Liu2020Flow2Stereo} & 9.99 \% & 16.67 \% & 11.10 \% & 100.00 \% & 0.05 s / GPU \\
UnFlow \cite{Meister2018UUL} & 10.15 \% & 15.93 \% & 11.11 \% & 100.00 \% & 0.12 s / GPU \\
UFlow \cite{jonschkowski2020matters} & 9.78 \% & 17.87 \% & 11.13 \% & 100.00 \% & 0.04 s / 1 core \\
FSF+MS \cite{Taniai2017} & 8.48 \% & 25.43 \% & 11.30 \% & 100.00 \% & 2.7 s / 4 cores \\
CNNF+PMBP \cite{PrincipleZhang} & 10.08 \% & 18.56 \% & 11.49 \% & 100.00 \% & 45 min / 1 cores \\
PWC-Net\_RVC \cite{Sun2018PWCNet} & 11.22 \% & 13.69 \% & 11.63 \% & 100.00 \% & 0.03 s / \\
SFF++ \cite{schuster2019sffpp} & 10.63 \% & 17.48 \% & 11.77 \% & 100.00 \% & 78 s / 4 cores \\
SfM-PM \cite{MaurerECCV2018} & 9.66 \% & 22.73 \% & 11.83 \% & 100.00 \% & 69 s / 3 cores \\
MR-Flow \cite{WulffCVPR2017} & 10.13 \% & 22.51 \% & 12.19 \% & 100.00 \% & 8 min / 1 core \\
Mono-SF \cite{brickwedde2019monosf} & 11.40 \% & 19.64 \% & 12.77 \% & 100.00 \% & 41 s / 1 core \\
SceneFFields \cite{schuster2018sceneflowfields} & 10.58 \% & 24.41 \% & 12.88 \% & 100.00 \% & 65 s / 4 cores \\
CSF \cite{Lv2016ECCV} & 10.40 \% & 25.78 \% & 12.96 \% & 100.00 \% & 80 s / 1 core \\
PWOC-3D \cite{saxena2019pwoc} & 12.40 \% & 15.78 \% & 12.96 \% & 100.00 \% & 0.13 s / \\
UnsupSimFlow \cite{Im2020ECCV} & 12.60 \% & 17.27 \% & 13.38 \% & 100.00 \% & 0.03 s / 8 cores \\
PR-Sceneflow \cite{Vogel2013ICCV} & 11.73 \% & 24.33 \% & 13.83 \% & 100.00 \% & 150 s / 4 core \\
DDFlow+LCV \cite{Xiao2018ECCV} & 12.98 \% & 19.83 \% & 14.12 \% & 100.00 \% & 0.1 s / GPU \\
SelFlow \cite{Liu2019SelFlow} & 12.68 \% & 21.74 \% & 14.19 \% & 100.00 \% & 0.09 s / GPU \\
DDFlow \cite{Liu2019DDFlow} & 13.08 \% & 20.40 \% & 14.29 \% & 100.00 \% & 0.06 s / GPU \\
DCFlow \cite{xu2017dcflow} & 13.10 \% & 23.70 \% & 14.86 \% & 100.00 \% & 8.6 s / GPU \\
ProFlow \cite{MaurerBMVC2018Proflow} & 13.86 \% & 20.91 \% & 15.04 \% & 100.00 \% & 112 s / GPU+CPU \\
FlowFields++ \cite{schuster2018flowfields++} & 14.82 \% & 17.77 \% & 15.31 \% & 100.00 \% & 29 s / 1 core \\
ProFlow\_ROB \cite{MaurerBMVC2018Proflow} & 14.15 \% & 21.82 \% & 15.42 \% & 100.00 \% & 112 s / GPU+CPU \\
Self-Mono-SF-ft \cite{Hur2020CVPR} & 15.51 \% & 17.96 \% & 15.91 \% & 100.00 \% & 0.09 s / \\
FF++\_ROB \cite{schuster2018flowfields++} & 15.32 \% & 19.27 \% & 15.97 \% & 100.00 \% & 29 s / 1 core \\
SOF \cite{Sevilla2016CVPR} & 14.63 \% & 22.83 \% & 15.99 \% & 100.00 \% & 6 min / 1 core \\
DIP-Flow-DF \cite{MaurerBMVC2018DIPFlow} & 14.93 \% & 23.37 \% & 16.33 \% & 100.00 \% & 104s / 2 cores \\
JFS \cite{Hur2016ECCVWORK} & 15.90 \% & 19.31 \% & 16.47 \% & 100.00 \% & 13 min / 1 core \\
DF+OIR \cite{MaurerBMVC2017} & 15.11 \% & 23.45 \% & 16.50 \% & 100.00 \% & 3 min / 1 core \\
SPS+FF++ \cite{schuster2018dense} & 15.91 \% & 20.27 \% & 16.64 \% & 100.00 \% & 36 s / 1 core \\
DIP-Flow-CPM \cite{MaurerBMVC2018DIPFlow} & 15.57 \% & 23.84 \% & 16.95 \% & 100.00 \% & 52 s / 2 core \\
ImpPB+SPCI \cite{Schuster2017Multiple} & 17.25 \% & 20.44 \% & 17.78 \% & 100.00 \% & 60 s / GPU \\
PCOF-LDOF \cite{Derome2016GCPR} & 14.34 \% & 38.32 \% & 18.33 \% & 100.00 \% & 50 s / 1 core \\
FlowFieldCNN \cite{Bailer2017CNN} & 18.33 \% & 20.42 \% & 18.68 \% & 100.00 \% & 23 s / GPU/CPU 4 core \\
RicFlow \cite{Hu2017CVPR} & 18.73 \% & 19.09 \% & 18.79 \% & 100.00 \% & 5 s / 1 core \\
HCSH \cite{FAN20181} & 18.05 \% & 26.23 \% & 19.41 \% & 100.00 \% & 3.5 s / 1 core \\
OmegaNet \cite{tosi2020distilled} & 17.43 \% & 29.69 \% & 19.47 \% & 100.00 \% & 0.01 s / GPU \\
PGM-G \cite{DBLPjournalscorrLi17n} & 18.90 \% & 23.43 \% & 19.66 \% & 100.00 \% & 5.05 s / 1 core \\
FlowFields+ \cite{1508.05151} & 19.51 \% & 21.26 \% & 19.80 \% & 100.00 \% & 28s / 1 core \\
EPC++ (stereo) \cite{Luo2019EveryPC} & 19.24 \% & 26.93 \% & 20.52 \% & 100.00 \% & 0.05 s / GPU \\
L0-norm Flow2 \cite{ERROR: Wrong syntax in BIBTEX file.} & 20.24 \% & 24.64 \% & 20.98 \% & 100.00 \% & 28 s / 1 core \\
PatchBatch \cite{Gadot2016CVPR} & 19.98 \% & 26.50 \% & 21.07 \% & 100.00 \% & 50 s / GPU \\
DDF \cite{Guney2016ACCV} & 20.36 \% & 25.19 \% & 21.17 \% & 100.00 \% & ~1 min / GPU \\
SODA-Flow \cite{MaurerSSVM2017} & 20.01 \% & 29.14 \% & 21.53 \% & 100.00 \% & 96 s / 2 cores \\
DiscreteFlow \cite{Menze2015GCPR} & 21.53 \% & 21.76 \% & 21.57 \% & 100.00 \% & 3 min / 1 core \\
SGM+SF \cite{Hirschmueller2008PAMI} & 20.91 \% & 25.50 \% & 21.67 \% & 100.00 \% & 45 min / 16 core \\
OAR-Flow \cite{MaurerSSVM20172} & 20.62 \% & 27.67 \% & 21.79 \% & 100.00 \% & 100 s / 2 cores \\
CPM-Flow \cite{Hu2016CVPR} & 22.32 \% & 22.81 \% & 22.40 \% & 100.00 \% & 4.2 s / 1 core \\
TV-Wavelet-Flow \cite{ERROR: Wrong syntax in BIBTEX file.} & 21.82 \% & 25.33 \% & 22.41 \% & 100.00 \% & 117 s / 1 core \\
PCOF + ACTF \cite{Derome2016GCPR} & 14.89 \% & 60.15 \% & 22.43 \% & 100.00 \% & 0.08 s / GPU \\
SegFlow(d0=3) \cite{3DFlow} & 22.21 \% & 23.72 \% & 22.46 \% & 100.00 \% & 6.6 s / 1 core \\
SegPM+Interpolation \cite{ERROR: Wrong syntax in BIBTEX file.} & 21.98 \% & 25.42 \% & 22.55 \% & 100.00 \% & 5.7 s / 1 core \\
IntrpNt-df \cite{Zweig2017CVPR} & 22.15 \% & 26.03 \% & 22.80 \% & 100.00 \% & 3 min / GPU \\
SGM&FlowFie+ \cite{Schuster2018Combining} & 22.83 \% & 22.75 \% & 22.82 \% & 81.24 \% & 29 s / 1 core \\
Back2FutureFlow(UFO) \cite{Janai2018ECCV} & 22.67 \% & 24.27 \% & 22.94 \% & 100.00 \% & 0.12 s / GPU \\
MotionSLIC \cite{Yamaguchi2013CVPR} & 14.86 \% & 64.44 \% & 23.11 \% & 100.00 \% & 30 s / 4 cores \\
IntrpNt-cpm \cite{Zweig2017CVPR} & 22.51 \% & 26.54 \% & 23.18 \% & 100.00 \% & 5.6 s / GPU \\
FullFlow \cite{Chen2016CVPR} & 23.09 \% & 24.79 \% & 23.37 \% & 100.00 \% & 4 min / 4 cores \\
HiLM \cite{Fathy2018ECCV} & 23.73 \% & 21.79 \% & 23.41 \% & 100.00 \% & 8 sec / \\
Self-Mono-SF \cite{Hur2020CVPR} & 23.26 \% & 24.93 \% & 23.54 \% & 100.00 \% & 0.09 s / \\
IntrpNt-dm \cite{Zweig2017CVPR} & 23.46 \% & 26.27 \% & 23.93 \% & 100.00 \% & 15 s / GPU \\
SPM-BP \cite{Li2015ICCV} & 24.06 \% & 24.97 \% & 24.21 \% & 100.00 \% & 10 s / 2 cores \\
PPM \cite{kuang} & 25.87 \% & 23.67 \% & 25.50 \% & 100.00 \% & 17.3 s / 1 core \\
3DFlow \cite{3DFlow} & 25.56 \% & 29.33 \% & 26.19 \% & 100.00 \% & 448s / \\
EpicFlow \cite{Revaud2015CVPR} & 25.81 \% & 28.69 \% & 26.29 \% & 100.00 \% & 15 s / 1 core \\
SegFlow(d0=11) \cite{3DFlow} & 28.97 \% & 22.64 \% & 27.91 \% & 100.00 \% & 4.5 s / 1 core \\
DeepFlow \cite{Weinzaepfel2013ICCV} & 27.96 \% & 31.06 \% & 28.48 \% & 100.00 \% & 17 s / 1 core \\
CPNFlow \cite{yang2018conditional} & 31.05 \% & 27.16 \% & 30.40 \% & 100.00 \% & 0.1 s / GPU \\
IIOF-NLDP \cite{TBDicip2017} & 30.23 \% & 32.44 \% & 30.60 \% & 100.00 \% & 350 s / 4 cores \\
DMF\_ROB \cite{weinzaepfelhal00873592} & 30.74 \% & 30.07 \% & 30.63 \% & 100.00 \% & 150 s / 1 core \\
SPyNet \cite{spynet2017} & 33.36 \% & 43.62 \% & 35.07 \% & 100.00 \% & 0.16 s / 1 core \\
SGM+C+NL \cite{Hirschmueller2008PAMI} & 34.24 \% & 42.46 \% & 35.61 \% & 93.83 \% & 4.5 min / 1 core \\
DWBSF \cite{Richardt2016THREEDV} & 40.74 \% & 31.16 \% & 39.14 \% & 100.00 \% & 7 min / 4 cores \\
SGM+LDOF \cite{Hirschmueller2008PAMI} & 40.81 \% & 31.92 \% & 39.33 \% & 95.89 \% & 86 s / 1 core \\
HS \cite{Sun2014IJCV} & 39.90 \% & 51.39 \% & 41.81 \% & 100.00 \% & 2.6 min / 1 core \\
GCSF \cite{Cech2011CVPR} & 47.38 \% & 41.50 \% & 46.40 \% & 100.00 \% & 2.4 s / 1 core \\
DB-TV-L1 \cite{Zach2007GCPR} & 47.52 \% & 48.27 \% & 47.64 \% & 100.00 \% & 16 s / 1 core \\
VSF \cite{Huguet2007ICCV} & 50.06 \% & 45.40 \% & 49.28 \% & 100.00 \% & 125 min / 1 core \\
HAOF \cite{Brox2004ECCV} & 49.89 \% & 50.74 \% & 50.04 \% & 100.00 \% & 16.2 s / 1 core \\
TVL1\_ROB \cite{ipol.2013.26} & 51.15 \% & 51.12 \% & 51.14 \% & 100.00 \% & 3 s / 4 cores \\
PolyExpand \cite{Farneback2003SCIA} & 52.00 \% & 58.56 \% & 53.09 \% & 100.00 \% & 1 s / 1 core \\
H+S\_ROB \cite{ipol.2013.20} & 68.22 \% & 76.49 \% & 69.60 \% & 100.00 \% & 8 s / 4 cores \\
Pyramid-LK \cite{Bouguet2000} & 71.84 \% & 76.82 \% & 72.67 \% & 100.00 \% & 1.5 min / 1 core
\end{tabular}