TARN uses episode-based meta-learning with temporal attention for alignment and segment-level distance learning to outperform prior methods on few-shot action recognition while remaining competitive on zero-shot.
Long-term recurrent convolutional networks for visual recognition and description.IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(4):677–691, April 2017
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
TARN: Temporal Attentive Relation Network for Few-Shot and Zero-Shot Action Recognition
TARN uses episode-based meta-learning with temporal attention for alignment and segment-level distance learning to outperform prior methods on few-shot action recognition while remaining competitive on zero-shot.