https://github.com/Anirudh257/strm
공식 코드Spatio-temporal Relation Modeling for Few-shot Action Recognition
Papers with Code 아카이브
Few Shot Action Recognition
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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.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/R00Kie-Liu/Sampler
공식 코드Task-adaptive Spatial-Temporal Video Sampler for Few-shot Action Recognition
https://github.com/R00Kie-Liu/TA2N
공식 코드TA2N: Two-Stage Action Alignment Network for Few-shot Action Recognition
https://github.com/TJU-YDragonW/TAMT
공식 코드TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition
https://github.com/alibaba-mmai-research/HyRSM
공식 코드Hybrid Relation Guided Set Matching for Few-shot Action Recognition
https://github.com/alibaba-mmai-research/clip-fsar
공식 코드CLIP-guided Prototype Modulating for Few-shot Action Recognition
https://github.com/alibaba-mmai-research/hyrsmplusplus
공식 코드HyRSM++: Hybrid Relation Guided Temporal Set Matching for Few-shot Action Recognition
https://github.com/alibaba-mmai-research/molo
공식 코드MoLo: Motion-augmented Long-short Contrastive Learning for Few-shot Action Recognition
https://github.com/cofly2014/tsa-mlt
공식 코드Task-Specific Alignment and Multiple Level Transformer for Few-Shot Action Recognition
https://github.com/gorjanradevski/revisiting-spatial-temporal-layouts
공식 코드Revisiting spatio-temporal layouts for compositional action recognition
https://github.com/hongguangzhang/mlso-tmm-master
공식 코드https://github.com/jaulin-bage/task-adapter-pp
공식 코드Task-Adapter++: Task-specific Adaptation with Order-aware Alignment for Few-shot Action Recognition
https://github.com/jiazheng-xing/gghm
공식 코드Boosting Few-shot Action Recognition with Graph-guided Hybrid Matching
https://github.com/kini5gowda/TruZe
공식 코드A New Split for Evaluating True Zero-Shot Action Recognition
https://github.com/leesb7426/team
공식 코드Temporal Alignment-Free Video Matching for Few-shot Action Recognition
https://github.com/leiwangr/udtw
공식 코드https://github.com/lovelyqian/AMeFu-Net
공식 코드Depth Guided Adaptive Meta-Fusion Network for Few-shot Video Recognition
https://github.com/nishantrai18/homage
공식 코드Home Action Genome: Cooperative Compositional Action Understanding
https://github.com/qizhongtan/d2st-adapter
공식 코드D$^2$ST-Adapter: Disentangled-and-Deformable Spatio-Temporal Adapter for Few-shot Action Recognition
https://github.com/sarinda251/cdfsl-v
공식 코드https://github.com/tobyperrett/trx
공식 코드Temporal-Relational CrossTransformers for Few-Shot Action Recognition
https://github.com/wenbohuang1002/soap
공식 코드https://github.com/wlin-at/maxi
공식 코드https://github.com/yyuncong/tempclr
공식 코드TempCLR: Temporal Alignment Representation with Contrastive Learning
https://github.com/zanedurante/vlm_benchmark
공식 코드Few-Shot Classification of Interactive Activities of Daily Living (InteractADL)
https://github.com/StanfordVL/moma
https://github.com/Teddy00888/arn_mindspore
Few-shot Action Recognition with Permutation-invariant Attention
https://github.com/eladb3/orvit
https://github.com/mcg-nju/trace
Action Genome: Actions as Composition of Spatio-temporal Scene Graphs
https://github.com/rruschel/bload
Action Genome: Actions as Composition of Spatio-temporal Scene Graphs
https://github.com/tobyperrett/few-shot-action-recognition
Temporal-Relational CrossTransformers for Few-Shot Action Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.