https://github.com/oliviazwy/dcgcn
공식 코드Dynamic Compositional Graph Convolutional Network for Efficient Composite Human Motion Prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Dynamic Compositional Graph Convolutional Network for Efficient Composite Human Motion Prediction
Video BagNet: short temporal receptive fields increase robustness in long-term action recognition
Precise Localization of Memories: A Fine-grained Neuron-level Knowledge Editing Technique for LLMs
Finding and Editing Multi-Modal Neurons in Pre-Trained Transformers
SmartRefine: A Scenario-Adaptive Refinement Framework for Efficient Motion Prediction
Hulk: A Universal Knowledge Translator for Human-Centric Tasks
Hulk: A Universal Knowledge Translator for Human-Centric Tasks
InternVideo: General Video Foundation Models via Generative and Discriminative Learning
InternVideo2: Scaling Foundation Models for Multimodal Video Understanding
Unmasked Teacher: Towards Training-Efficient Video Foundation Models
Video Mamba Suite: State Space Model as a Versatile Alternative for Video Understanding
Challenges in Video-Based Infant Action Recognition: A Critical Examination of the State of the Art
Ske2Grid: Skeleton-to-Grid Representation Learning for Action Recognition
Real-Time Hand Gesture Recognition: Integrating Skeleton-Based Data Fusion and Multi-Stream CNN
SPEED: Scalable, Precise, and Efficient Concept Erasure for Diffusion Models
Predicting Long-Term Skeletal Motions by a Spatio-Temporal Hierarchical Recurrent Network
A Survey on Video Action Recognition in Sports: Datasets, Methods and Applications
Cost-Sensitive Learning for Long-Tailed Temporal Action Segmentation
Long-Tail Temporal Action Segmentation with Group-wise Temporal Logit Adjustment
HYperbolic Self-Paced Learning for Self-Supervised Skeleton-based Action Representations
KP-RNN: A Deep Learning Pipeline for Human Motion Prediction and Synthesis of Performance Art
AGAR: Attention Graph-RNN for Adaptative Motion Prediction of Point Clouds of Deformable Objects
Efficient Temporal Action Segmentation via Boundary-aware Query Voting
UncAD: Towards Safe End-to-end Autonomous Driving via Online Map Uncertainty
Action Transformer: A Self-Attention Model for Short-Time Pose-Based Human Action Recognition
Action Transformer: A Self-Attention Model for Short-Time Pose-Based Human Action Recognition
Action Transformer: A Self-Attention Model for Short-Time Pose-Based Human Action Recognition
HR-Pro: Point-supervised Temporal Action Localization via Hierarchical Reliability Propagation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.