https://github.com/jingyaojade/SpSt-GCN
공식 코드Skeleton-Based Action Recognition with Spatial-Structural Graph Convolution
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/jiyanggao/CTAP
공식 코드https://github.com/jiyanggao/TURN-TAP
공식 코드TURN TAP: Temporal Unit Regression Network for Temporal Action Proposals
https://github.com/john-hewitt/model-editing-canonical-examples
공식 코드https://github.com/johnnychanv/JailbreakEdit
공식 코드Injecting Universal Jailbreak Backdoors into LLMs in Minutes
https://github.com/joker3993/rlhgnn
공식 코드https://github.com/jometeorie/multihopshortcuts
공식 코드Investigating Multi-Hop Factual Shortcuts in Knowledge Editing of Large Language Models
https://github.com/jonghyeonk/kb-modulation
공식 코드Knowledge-Driven Modulation of Neural Networks with Attention Mechanism for Next Activity Prediction
https://github.com/joslefaure/hit
공식 코드Holistic Interaction Transformer Network for Action Detection
https://github.com/jsun57/comusion
공식 코드CoMusion: Towards Consistent Stochastic Human Motion Prediction via Motion Diffusion
https://github.com/june01/wfsal-icmr21
공식 코드https://github.com/junweiliang/multitrain
공식 코드Multi-dataset Training of Transformers for Robust Action Recognition
https://github.com/junwenchen/GAP_SRAM
공식 코드Group Activity Prediction with Sequential Relational Anticipation Model
https://github.com/jx-zhong-for-academic-purpose/kinet
공식 코드https://github.com/kaai520/PGFA
공식 코드Zero-shot Skeleton-based Action Recognition with Prototype-guided Feature Alignment
https://github.com/kaanakan/slamp
공식 코드https://github.com/kaiyoo/precondition-and-effect-reasoning-for-action-recognition
공식 코드https://github.com/kakaobrain/flame
공식 코드https://github.com/kakashiz/nedb-net
공식 코드Noise and Edge Based Dual Branch Image Manipulation Detection
https://github.com/kalpitthakkar/pb-gcn
공식 코드Part-based Graph Convolutional Network for Action Recognition
https://github.com/kathpra/lshr_lsht
공식 코드Local Spherical Harmonics Improve Skeleton-Based Hand Action Recognition
https://github.com/kawakera-lab/crossmodeltransfer
공식 코드Cross-Model Transfer of Task Vectors via Few-Shot Orthogonal Alignment
https://github.com/kay1794/mmvp-motion-matrix-based-video-prediction
공식 코드https://github.com/kebii/r2et
공식 코드Skinned Motion Retargeting with Residual Perception of Motion Semantics & Geometry
https://github.com/keltin13/concept-rot
공식 코드Concept-ROT: Poisoning Concepts in Large Language Models with Model Editing
https://github.com/kennymckormick/pyskl
공식 코드PYSKL: Towards Good Practices for Skeleton Action Recognition
https://github.com/kenshohara/3D-ResNets
공식 코드Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition
https://github.com/kenziyuliu/ms-g3d
공식 코드Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition
https://github.com/kevin-ssy/Optical-Flow-Guided-Feature
공식 코드Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition
https://github.com/khadidja-delloul/rgb-d-theatre-scenes-dataset
공식 코드TS-RGBD Dataset: a Novel Dataset for Theatre Scenes Description for People with Visual Impairments
https://github.com/khu-vll/devias
공식 코드DEVIAS: Learning Disentangled Video Representations of Action and Scene
https://github.com/kimihiroh/promqa
공식 코드ProMQA: Question Answering Dataset for Multimodal Procedural Activity Understanding
https://github.com/kit-mrt/future-motion
공식 코드https://github.com/kit-mrt/red-motion
공식 코드https://github.com/kit-mrt/road-barlow-twins
공식 코드https://github.com/kiyoon/video-adversarial-augmentation
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.