https://github.com/ParitoshParmar/Fitness-AQA
공식 코드Domain Knowledge-Informed Self-Supervised Representations for Workout Form Assessment
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/PeizhuoLi/neural-blend-shapes
공식 코드https://github.com/PetarV-/GAT
공식 코드https://github.com/PinzhengWang322/Reveal_Attention_Drift
공식 코드Revealing and Mitigating Over-Attention in Knowledge Editing
https://github.com/Sunnydreamrain/IndRNN_Theano_Lasagne
공식 코드Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN
https://github.com/Sunnydreamrain/IndRNN_pytorch
공식 코드https://github.com/TaeSoo-Kim/TCNActionRecognition
공식 코드Interpretable 3D Human Action Analysis with Temporal Convolutional Networks
https://github.com/Tiiiger/SGC
공식 코드https://github.com/TrustedLLM/UnKE
공식 코드Everything is Editable: Extend Knowledge Editing to Unstructured Data in Large Language Models
https://github.com/Uason-Chen/CTR-GCN
공식 코드Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition
https://github.com/Va6lue/BST-Badminton-Stroke-type-Transformer
공식 코드BST: Badminton Stroke-type Transformer for Skeleton-based Action Recognition in Racket Sports
https://github.com/Walter0807/MotionBERT
공식 코드MotionBERT: A Unified Perspective on Learning Human Motion Representations
https://github.com/XZhang00/LU-LAFNs
공식 코드Multilingual Knowledge Editing with Language-Agnostic Factual Neurons
https://github.com/YangDi666/UNIK
공식 코드UNIK: A Unified Framework for Real-world Skeleton-based Action Recognition
https://github.com/YinxPeng/HA-CM-main
공식 코드https://github.com/Ymm-cll/UniErase
공식 코드UniErase: Unlearning Token as a Universal Erasure Primitive for Language Models
https://github.com/ZhenyueQin/Angular-Skeleton-Encoding
공식 코드Fusing Higher-order Features in Graph Neural Networks for Skeleton-based Action Recognition
https://github.com/ZhouYuxuanYX/Hypergraph-Transformer-for-Skeleton-based-Action-Recognition
공식 코드Hypergraph Transformer for Skeleton-based Action Recognition
https://github.com/Zhow01/S2RKE
공식 코드https://github.com/ZichenMiao/GNN-with-Low-rank-Learnable-Local-Filters
공식 코드https://github.com/ZichenMiao/L3Net
공식 코드https://github.com/ZiweiXU/CapsuleMotion
공식 코드Unsupervised Motion Representation Learning with Capsule Autoencoders
https://github.com/abcyzj/Semantics2Hands
공식 코드Semantics2Hands: Transferring Hand Motion Semantics between Avatars
https://github.com/abcyzj/meshret
공식 코드Skinned Motion Retargeting with Dense Geometric Interaction Perception
https://github.com/abhinanda-punnakkal/BABEL
공식 코드https://github.com/acerkoo/disco
공식 코드Outdated Issue Aware Decoding for Reasoning Questions on Edited Knowledge
https://github.com/adeboissiere/FUSION-human-action-recognition
공식 코드Infrared and 3D skeleton feature fusion for RGB-D action recognition
https://github.com/adityac94/Grad_CAM_plus_plus
공식 코드Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks
https://github.com/aengusl/latent-adversarial-training
공식 코드Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs
https://github.com/againerju/tcg_recognition
공식 코드https://github.com/ai4life-group/splice
공식 코드Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)
https://github.com/aikuniverse/tcte-net
공식 코드Temporal-Channel Topology Enhanced Network for Skeleton-Based Action Recognition
https://github.com/airglow/gimme_signals_action_recognition
공식 코드Gimme Signals: Discriminative signal encoding for multimodal activity recognition
https://github.com/alessiogalatolo/diekae
공식 코드https://github.com/alexrich021/3dvnet
공식 코드3DVNet: Multi-View Depth Prediction and Volumetric Refinement
https://github.com/amodaresi/memllm
공식 코드MemLLM: Finetuning LLMs to Use An Explicit Read-Write Memory
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.