https://github.com/1xbq1/a2mc
공식 코드Attack-Augmentation Mixing-Contrastive Skeletal Representation Learning
Papers with Code 아카이브
3D Action Recognition
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Image: Rahmani et al
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/1xbq1/psp-learning
공식 코드Pyramid Self-attention Polymerization Learning for Semi-supervised Skeleton-based Action Recognition
https://github.com/3huo/3DV-Action
공식 코드https://github.com/99eren99/dirfiaf
공식 코드https://github.com/99eren99/dis25k
공식 코드https://github.com/ABi-dot/Kedkg
공식 코드Knowledge Editing with Dynamic Knowledge Graphs for Multi-Hop Question Answering
https://github.com/ActionR-G/ActionHSIC
공식 코드https://github.com/Aries-chen/MedEditBench
공식 코드Beyond Memorization: A Rigorous Evaluation Framework for Medical Knowledge Editing
https://github.com/BUPTSJZhang/SiT-MLP
공식 코드https://github.com/Betswish/Cross-Lingual-Consistency
공식 코드Cross-Lingual Consistency of Factual Knowledge in Multilingual Language Models
https://github.com/BobXWu/AKEW
공식 코드https://github.com/CV-Lehigh/Bias_IMD
공식 코드https://github.com/Chiaraplizz/ST-TR
공식 코드Skeleton-based Action Recognition via Spatial and Temporal Transformer Networks
https://github.com/DaphneAntotsiou/task-oriented-hand-retargeting
공식 코드Task-Oriented Hand Motion Retargeting for Dexterous Manipulation Imitation
https://github.com/EHZ9NIWI7/MSF-GZSSAR
공식 코드Multi-Semantic Fusion Model for Generalized Zero-Shot Skeleton-Based Action Recognition
https://github.com/ENSCMA2/flextape
공식 코드"Flex Tape Can't Fix That": Bias and Misinformation in Edited Language Models
https://github.com/Gbouna/RE-TCN
공식 코드Action Recognition in Real-World Ambient Assisted Living Environment
https://github.com/HuCui2022/DSTSA-GCN_Gesture
공식 코드https://github.com/IIT-PAVIS/subspace-clustering-action-recognition
공식 코드Subspace Clustering for Action Recognition with Covariance Representations and Temporal Pruning
https://github.com/JHang2020/HiCLR
공식 코드https://github.com/JHang2020/Shap-Mix
공식 코드Shap-Mix: Shapley Value Guided Mixing for Long-Tailed Skeleton Based Action Recognition
https://github.com/Jho-Yonsei/HD-GCN
공식 코드Hierarchically Decomposed Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/Jho-Yonsei/STC-Net
공식 코드Leveraging Spatio-Temporal Dependency for Skeleton-Based Action Recognition
https://github.com/KAIST-VICLab/SkateFormer
공식 코드SkateFormer: Skeletal-Temporal Transformer for Human Action Recognition
https://github.com/KAIST-VICLab/TDSM
공식 코드TDSM: Triplet Diffusion for Skeleton-Text Matching in Zero-Shot Action Recognition
https://github.com/LanglandsLin/MS2L
공식 코드MS$^2$L: Multi-Task Self-Supervised Learning for Skeleton Based Action Recognition
https://github.com/LeiWangR/HDG
공식 코드A Comparative Review of Recent Kinect-based Action Recognition Algorithms
https://github.com/Levigty/CMCS
공식 코드Cross-Model Cross-Stream Learning for Self-Supervised Human Action Recognition
https://github.com/Lyz1213/BadEdit
공식 코드https://github.com/MIT-HAN-LAB/temporal-shift-module
공식 코드TSM: Temporal Shift Module for Efficient Video Understanding
https://github.com/MMKE-Bench-ICLR/MMKE-Bench
공식 코드MMKE-Bench: A Multimodal Editing Benchmark for Diverse Visual Knowledge
https://github.com/Maghoumi/DeepGRU
공식 코드https://github.com/Mikexu007/PCRP
공식 코드Prototypical Contrast and Reverse Prediction: Unsupervised Skeleton Based Action Recognition
https://github.com/Necolizer/CHASE
공식 코드CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action Recognition
https://github.com/Necolizer/ISTA-Net
공식 코드https://github.com/OrdinaryQin/TCA-GCN
공식 코드Skeleton-based Action Recognition via Temporal-Channel Aggregation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.