Constraint-aware decoding refines TAS predictions by embedding data-derived structural priors into modified Viterbi inference for error correction without model changes.
Weakly supervised action learning with rnn based fine-to-coarse modeling.2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 1273–1282
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
-
Improving Temporal Action Segmentation via Constraint-Aware Decoding
Constraint-aware decoding refines TAS predictions by embedding data-derived structural priors into modified Viterbi inference for error correction without model changes.