https://github.com/Cogito2012/CarCrashDataset
공식 코드Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Temporal Action Localization aims to detect activities in the video stream and output beginning and end timestamps. It is closely related to Temporal Action Proposal Generation.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning
Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning
Task-Oriented Hand Motion Retargeting for Dexterous Manipulation Imitation
Cross-task weakly supervised learning from instructional videos
DeepSOCIAL: Social Distancing Monitoring and Infection Risk Assessment in COVID-19 Pandemic
Diverse Human Motion Prediction via Gumbel-Softmax Sampling from an Auxiliary Space
MSR-GCN: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction
Multi-Semantic Fusion Model for Generalized Zero-Shot Skeleton-Based Action Recognition
"Flex Tape Can't Fix That": Bias and Misinformation in Edited Language Models
Advancing Compressed Video Action Recognition through Progressive Knowledge Distillation
Self-supervised Temporal Discriminative Learning for Video Representation Learning
SF-Net: Single-Frame Supervision for Temporal Action Localization
TM2D: Bimodality Driven 3D Dance Generation via Music-Text Integration
Revisiting hand-crafted feature for action recognition: a set of improved dense trajectories
Action Recognition in Real-World Ambient Assisted Living Environment
ScaleFlow++: Robust and Accurate Estimation of 3D Motion from Video
RefineLoc: Iterative Refinement for Weakly-Supervised Action Localization
TSP: Temporally-Sensitive Pretraining of Video Encoders for Localization Tasks
Action Search: Spotting Actions in Videos and Its Application to Temporal Action Localization
Deep Analysis of CNN-based Spatio-temporal Representations for Action Recognition
Subspace Clustering for Action Recognition with Covariance Representations and Temporal Pruning
The IKEA ASM Dataset: Understanding People Assembling Furniture through Actions, Objects and Pose
Shap-Mix: Shapley Value Guided Mixing for Long-Tailed Skeleton Based Action Recognition
Hierarchically Decomposed Graph Convolutional Networks for Skeleton-Based Action Recognition
Leveraging Spatio-Temporal Dependency for Skeleton-Based Action Recognition
ReLER@ZJU Submission to the Ego4D Moment Queries Challenge 2022
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.