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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 26–50 of 76 papers

TitleStatusHype
Consistency Prototype Module and Motion Compensation for Few-Shot Action Recognition (CLIP-CPM^2C)Code0
Few-Shot Classification of Interactive Activities of Daily Living (InteractADL)Code0
Multi-level Second-order Few-shot LearningCode0
Multi-view Distillation based on Multi-modal Fusion for Few-shot Action Recognition(CLIP-M^2DF)Code0
SOAP: Enhancing Spatio-Temporal Relation and Motion Information Capturing for Few-Shot Action RecognitionCode0
Task-Adapter++: Task-specific Adaptation with Order-aware Alignment for Few-shot Action RecognitionCode0
Task-Specific Alignment and Multiple Level Transformer for Few-Shot Action RecognitionCode0
Uncertainty-DTW for Time Series and SequencesCode0
Learn2Augment: Learning to Composite Videos for Data Augmentation in Action Recognition—0
Learning Causal Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition—0
Learning Graphs for Knowledge Transfer With Limited Labels—0
Manta: Enhancing Mamba for Few-Shot Action Recognition of Long Sub-Sequence—0
Few-Shot Action Recognition with Compromised Metric via Optimal Transport—0
Meet JEANIE: a Similarity Measure for 3D Skeleton Sequences via Temporal-Viewpoint Alignment—0
Few-shot Action Recognition with Captioning Foundation Models—0
Few-shot Action Recognition via Intra- and Inter-Video Information Maximization—0
Motion-Modulated Temporal Fragment Alignment Network for Few-Shot Action Recognition—0
A Comprehensive Review of Few-shot Action Recognition—0
MA-FSAR: Multimodal Adaptation of CLIP for Few-Shot Action Recognition—0
Multimodal Prototype-Enhanced Network for Few-Shot Action Recognition—0
Two-stream joint matching method based on contrastive learning for few-shot action recognition—0
MVP-Shot: Multi-Velocity Progressive-Alignment Framework for Few-Shot Action Recognition—0
3D Skeleton-based Few-shot Action Recognition with JEANIE is not so Naïve—0
On the Importance of Spatial Relations for Few-shot Action Recognition—0
Rethinking matching-based few-shot action recognition—0
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