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ResearchFormerly WizWand

Video Object Segmentation on FBMS-59 (test)

0.758Avg IoUDyStaB (Supervised)
0.432480.516990.60150.68601Sep 4, 2018May 8, 2019Jan 9, 2020Sep 11, 2020May 15, 2021Jan 16, 2022Sep 19, 2022
Updated 8mo ago

Evaluation results

MethodLinks
DyStaB (Supervised)Training on videos=true, Optical flow=PWCNet [71]2022.090.758
DyStaB (Unsupervised)Optical flow=PWCNet [71]2022.090.732
DSTraining on videos=true, Optical flow=RAFT [73]2022.090.718
OursTraining on videos=true, Optical flow=ARFlow [46], Fully unsupervised=true2022.090.7
FSEGTraining on videos=true2022.090.684
LVOTraining on videos=true, Optical flow=MP-Net [74]2022.090.651
CISTraining on videos=true, Optical flow=PWCNet [71]2022.090.635
Motion Saliency-Guided Spatio-Temporal Propagation2018.090.608
MSgStP2022.090.608
ARP2018.090.598
ARPOptical flow=CPMFlow [32]2022.090.598
CUTOptical flow=LDOF [3], Fully unsupervised=true2022.090.572
FST2018.090.555
POS2018.090.542
MoSegTraining on videos=true, Optical flow=RAFT [73]2022.090.531
NLCOptical flow=SIFTFlow [45]2022.090.515
FTSOptical flow=LDOF [72], Fully unsupervised=true2022.090.477
AMDFully unsupervised=true2022.090.475
POR2018.090.473
NLC2018.090.445