AI RESEARCH
Hierarchical Relation-augmented Representation Generalization for Few-shot Action Recognition
arXiv CS.CV
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ArXi:2504.10079v4 Announce Type: replace Few-shot action recognition (FSAR) aims to recognize novel action categories with few exemplars. Existing methods typically learn frame-level representations for each video by designing inter-frame temporal modeling strategies or inter-video interaction at the coarse video-level granularity. However, they treat each episode task in isolation and neglect fine-grained temporal relation modeling between videos, thus failing to capture shared fine-grained temporal patterns across videos and reuse temporal knowledge from historical tasks.