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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 1–50 of 76 papers

TitleStatusHype
HyRSM++: Hybrid Relation Guided Temporal Set Matching for Few-shot Action RecognitionCode1
Few-shot Action Recognition with Prototype-centered Attentive LearningCode1
Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence ClassificationCode1
Hybrid Relation Guided Set Matching for Few-shot Action RecognitionCode1
Home Action Genome: Cooperative Compositional Action UnderstandingCode1
Temporal Alignment-Free Video Matching for Few-shot Action RecognitionCode1
TempCLR: Temporal Alignment Representation with Contrastive LearningCode1
Task-adaptive Spatial-Temporal Video Sampler for Few-shot Action RecognitionCode1
TA2N: Two-Stage Action Alignment Network for Few-shot Action RecognitionCode1
Action Genome: Actions as Composition of Spatio-temporal Scene GraphsCode1
CDFSL-V: Cross-Domain Few-Shot Learning for VideosCode1
CLIP-guided Prototype Modulating for Few-shot Action RecognitionCode1
TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action RecognitionCode1
Spatio-temporal Relation Modeling for Few-shot Action RecognitionCode1
Temporal-Relational CrossTransformers for Few-Shot Action RecognitionCode1
D^2ST-Adapter: Disentangled-and-Deformable Spatio-Temporal Adapter for Few-shot Action RecognitionCode1
Depth Guided Adaptive Meta-Fusion Network for Few-shot Video RecognitionCode1
Revisiting spatio-temporal layouts for compositional action recognitionCode1
Object-Region Video TransformersCode1
MOMA-LRG: Language-Refined Graphs for Multi-Object Multi-Actor Activity ParsingCode1
MoLo: Motion-augmented Long-short Contrastive Learning for Few-shot Action RecognitionCode1
MAtch, eXpand and Improve: Unsupervised Finetuning for Zero-Shot Action Recognition with Language KnowledgeCode1
Few-shot Action Recognition with Permutation-invariant AttentionCode0
A New Split for Evaluating True Zero-Shot Action RecognitionCode0
Boosting Few-shot Action Recognition with Graph-guided Hybrid MatchingCode0
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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