https://github.com/iesymiao/cd-gcn
공식 코드A Central Difference Graph Convolutional Operator for Skeleton-Based Action Recognition
Papers with Code 아카이브
Action Localization
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Action Localization is finding the spatial and temporal co ordinates for an action in a video. An action localization model will identify which frame an action start and ends in video and return the x,y coordinates of an action. Further the co ordinates will change when the object performing action undergoes a displacement.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/iit-pavis/uhar_skeletal_laplacian
공식 코드https://github.com/imj2185/STAR
공식 코드https://github.com/inowlzy/smart
공식 코드SMART: Scene-motion-aware human action recognition framework for mental disorder group
https://github.com/inria-larsen/activity-recognition-prediction-wearable
공식 코드A Variational Time Series Feature Extractor for Action Prediction
https://github.com/intellabs/multimodal_cognitive_ai
공식 코드Analyzing Zero-Shot Abilities of Vision-Language Models on Video Understanding Tasks
https://github.com/interpretml/gam-changer
공식 코드Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values
https://github.com/interpretml/interpret
공식 코드Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values
https://github.com/ioannanti/bmvit
공식 코드https://github.com/irmvlab/egoloc
공식 코드Zero-Shot Temporal Interaction Localization for Egocentric Videos
https://github.com/isee-laboratory/cvpr24_atba
공식 코드https://github.com/isee-laboratory/egoexo-fitness
공식 코드EgoExo-Fitness: Towards Egocentric and Exocentric Full-Body Action Understanding
https://github.com/ispc-lab/ACM-Net
공식 코드ACM-Net: Action Context Modeling Network for Weakly-Supervised Temporal Action Localization
https://github.com/iurada/talos-task-arithmetic
공식 코드Efficient Model Editing with Task-Localized Sparse Fine-tuning
https://github.com/j-h-hwang/temporal_shuffling
공식 코드Temporal Shuffling for Defending Deep Action Recognition Models against Adversarial Attacks
https://github.com/jaakk0f/dstd-gcn
공식 코드Learning Constrained Dynamic Correlations in Spatiotemporal Graphs for Motion Prediction
https://github.com/jackyjsy/CVPR21Chal-SLR
공식 코드https://github.com/jackyjsy/sam-slr-v2
공식 코드Sign Language Recognition via Skeleton-Aware Multi-Model Ensemble
https://github.com/jalayrac/object-states-action
공식 코드https://github.com/jalayrac/weakactionloc
공식 코드A flexible model for training action localization with varying levels of supervision
https://github.com/jarrentwu1031/sc4d
공식 코드SC4D: Sparse-Controlled Video-to-4D Generation and Motion Transfer
https://github.com/jasonforjoy/model-editing-hurt
공식 코드Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue
https://github.com/jasonwang959/stpmp
공식 코드Spatio-Temporal Branching for Motion Prediction using Motion Increments
https://github.com/jemoka/dropfree
공식 코드https://github.com/jfightyr/slowfast-meet-vit
공식 코드https://github.com/jiaangl/elder
공식 코드ELDER: Enhancing Lifelong Model Editing with Mixture-of-LoRA
https://github.com/jiakuan929/superficial-editing
공식 코드Revealing the Deceptiveness of Knowledge Editing: A Mechanistic Analysis of Superficial Editing
https://github.com/jianghoucheng/alphaedit
공식 코드AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models
https://github.com/jianghoucheng/nse
공식 코드https://github.com/jianglongye/cgf
공식 코드Learning Continuous Grasping Function with a Dexterous Hand from Human Demonstrations
https://github.com/jianzhou1212/interaction-safety-aware-motion-planning
공식 코드https://github.com/jiashunwang/MRT
공식 코드Multi-Person 3D Motion Prediction with Multi-Range Transformers
https://github.com/jiayouqin/h-splitter
공식 코드Motor Focus: Fast Ego-Motion Prediction for Assistive Visual Navigation
https://github.com/jiayuzou2020/diffbev
공식 코드DiffBEV: Conditional Diffusion Model for Bird's Eye View Perception
https://github.com/jimmy-dq/dmt
공식 코드A Lightweight and Detector-free 3D Single Object Tracker on Point Clouds
https://github.com/jinglinglingling/x4d
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.