https://github.com/RoboticExplorationLab/LUCIDGames.jl
공식 코드LUCIDGames: onLine UnsCented Inverse Dynamic Games forAdaptive Trajectory Prediction and Planning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Trajectory Prediction is the problem of predicting the short-term (1-3 seconds) and long-term (3-5 seconds) spatial coordinates of various road-agents such as cars, buses, pedestrians, rickshaws, and animals, etc. These road-agents have different dynamic behaviors that may correspond to aggressive or conservative driving styles.
Source: Forecasting Trajectory and Behavior of Road-Agents Using Spectral Clustering in Graph-LSTMs
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
LUCIDGames: onLine UnsCented Inverse Dynamic Games forAdaptive Trajectory Prediction and Planning
Robust Conformal Prediction for STL Runtime Verification under Distribution Shift
Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph
InterDiff: Generating 3D Human-Object Interactions with Physics-Informed Diffusion
Mitigating Traffic Oscillations in Mixed Traffic Flow with Scalable Deep Koopman Predictive Control
MATS: An Interpretable Trajectory Forecasting Representation for Planning and Control
The Trajectron: Probabilistic Multi-Agent Trajectory Modeling With Dynamic Spatiotemporal Graphs
Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data
Pishgu: Universal Path Prediction Network Architecture for Real-time Cyber-physical Edge Systems
DenseTNT: Waymo Open Dataset Motion Prediction Challenge 1st Place Solution
ViP3D: End-to-end Visual Trajectory Prediction via 3D Agent Queries
QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction
Context-aware Multi-task Learning for Pedestrian Intent and Trajectory Prediction
Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks
Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models
TrajEvo: Designing Trajectory Prediction Heuristics via LLM-driven Evolution
Trajectory Forecasting through Low-Rank Adaptation of Discrete Latent Codes
BiPOCO: Bi-Directional Trajectory Prediction with Pose Constraints for Pedestrian Anomaly Detection
Leveraging Trajectory Prediction for Pedestrian Video Anomaly Detection
Hierarchical Light Transformer Ensembles for Multimodal Trajectory Forecasting
AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction
DAG-Net: Double Attentive Graph Neural Network for Trajectory Forecasting
Accelerating Online Mapping and Behavior Prediction via Direct BEV Feature Attention
Producing and Leveraging Online Map Uncertainty in Trajectory Prediction
Direct multi-modal inversion of geophysical logs using deep learning
TrajLearn: Trajectory Prediction Learning using Deep Generative Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.