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Few Shot Action Recognition

Few-shot (FS) action recognition is a challenging com- puter vision problem, where the task is to classify an unlabelled query video into one of the action categories in the support set having limited samples per action class.

Papers

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Showing 31–40 of 76 papers

TitleStatusHype
Few-shot Action Recognition via Intra- and Inter-Video Information Maximization—0
MoLo: Motion-augmented Long-short Contrastive Learning for Few-shot Action RecognitionCode1
Rethinking matching-based few-shot action recognition—0
MAtch, eXpand and Improve: Unsupervised Finetuning for Zero-Shot Action Recognition with Language KnowledgeCode1
CLIP-guided Prototype Modulating for Few-shot Action RecognitionCode1
Revisiting the Spatial and Temporal Modeling for Few-shot Action Recognition—0
HyRSM++: Hybrid Relation Guided Temporal Set Matching for Few-shot Action RecognitionCode1
Active Exploration of Multimodal Complementarity for Few-Shot Action Recognition—0
TempCLR: Temporal Alignment Representation with Contrastive LearningCode1
SMAM: Self and Mutual Adaptive Matching for Skeleton-Based Few-Shot Action Recognition—0
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