https://github.com/yysijie/st-gcn
공식 코드Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
Papers with Code 아카이브
3D Action Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/yzqin/dexmv-sim
공식 코드DexMV: Imitation Learning for Dexterous Manipulation from Human Videos
https://github.com/zahrag/gg3dhar
공식 코드Hierarchical growing grid networks for skeleton based action recognition
https://github.com/zce1112zslx/ike
공식 코드https://github.com/zepingyu0512/arithmetic-mechanism
공식 코드Interpreting Arithmetic Mechanism in Large Language Models through Comparative Neuron Analysis
https://github.com/zepingyu0512/neuron-attribution
공식 코드https://github.com/zeroyuhuang/transformer-patcher
공식 코드https://github.com/zhang-yihao/adversarial-representation-engineering
공식 코드Adversarial Representation Engineering: A General Model Editing Framework for Large Language Models
https://github.com/zhaozetong/dualedit
공식 코드Mitigating Safety Fallback in Editing-based Backdoor Injection on LLMs
https://github.com/zhenfeiz/cimd
공식 코드A New Benchmark and Model for Challenging Image Manipulation Detection
https://github.com/zhimengj0326/gradient_rewiring_editing
공식 코드Gradient Rewiring for Editable Graph Neural Network Training
https://github.com/zhouyuxuanyx/blockgcn
공식 코드https://github.com/zhrli324/rledit
공식 코드https://github.com/zhysora/fr-head
공식 코드Learning Discriminative Representations for Skeleton Based Action Recognition
https://github.com/zjunlp/BiasEdit
공식 코드BiasEdit: Debiasing Stereotyped Language Models via Model Editing
https://github.com/zjunlp/PromptKG/tree/main/deltaKG
공식 코드https://github.com/zjunlp/cake
공식 코드CaKE: Circuit-aware Editing Enables Generalizable Knowledge Learners
https://github.com/zjunlp/easyedit
공식 코드Editing Large Language Models: Problems, Methods, and Opportunities
https://github.com/zjunlp/knowledgecircuits
공식 코드https://github.com/zjunlp/knowledgeeditingpapers
공식 코드A Comprehensive Study of Knowledge Editing for Large Language Models
https://github.com/zjunlp/knowlm
공식 코드EasyEdit: An Easy-to-use Knowledge Editing Framework for Large Language Models
https://github.com/zjunlp/oneedit
공식 코드OneEdit: A Neural-Symbolic Collaboratively Knowledge Editing System
https://github.com/zjunlp/pitfallsknowledgeediting
공식 코드Unveiling the Pitfalls of Knowledge Editing for Large Language Models
https://github.com/zjunlp/promptkg
공식 코드https://github.com/zongkaiz/fleke
공식 코드https://github.com/zzhao71/ripplecot
공식 코드https://github.com/zzysteve/skeletonx
공식 코드SkeletonX: Data-Efficient Skeleton-based Action Recognition via Cross-sample Feature Aggregation
https://gitlab.com/MISLgit/forensic-similarity-for-digital-images
공식 코드https://huggingface.co/datasets/SoftMINER-Group/NicheHazardQA
공식 코드Sowing the Wind, Reaping the Whirlwind: The Impact of Editing Language Models
https://huggingface.co/datasets/SoftMINER-Group/TechHazardQA
공식 코드https://gitee.com/gai-shaoyan/mind3d
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://gitee.com/zhengkeli/zkl-knowedit-rome
https://github.com/1075225782/GCN
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/1zgh/st-gcn
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/2023-MindSpore-1/ms-code-11/tree/main/gcn
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/flownet2
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.