https://github.com/AlbertoSabater/Skeleton-based-One-shot-Action-Recognition
공식 코드One-shot action recognition in challenging therapy scenarios
Papers with Code 아카이브
One-Shot 3D Action Recognition
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Walter0807/MotionBERT
공식 코드MotionBERT: A Unified Perspective on Learning Human Motion Representations
https://github.com/kaai520/PGFA
공식 코드Zero-shot Skeleton-based Action Recognition with Prototype-guided Feature Alignment
https://github.com/raphaelmemmesheimer/skeleton-dml
공식 코드Skeleton-DML: Deep Metric Learning for Skeleton-Based One-Shot Action Recognition
https://github.com/raphaelmemmesheimer/sl-dml
공식 코드SL-DML: Signal Level Deep Metric Learning for Multimodal One-Shot Action Recognition
https://github.com/zzysteve/skeletonx
공식 코드SkeletonX: Data-Efficient Skeleton-based Action Recognition via Cross-sample Feature Aggregation
https://github.com/LinguoLi/CrosSCLR
NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding
https://github.com/czhaneva/skelemixclr
NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding
https://github.com/shahroudy/NTURGB-D
NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.