SBF augments 2D skeletons with scale, body, and optical-flow maps predicted by SFSNet to raise accuracy in video-based human action recognition.
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset.2017 IEEE Conference on Computer Vision and Pattern Recogni- tion (CVPR), pages 4724–4733
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
SBF: An Effective Representation to Augment Skeleton for Video-based Human Action Recognition
SBF augments 2D skeletons with scale, body, and optical-flow maps predicted by SFSNet to raise accuracy in video-based human action recognition.