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Trajectory Prediction
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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
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Dual LiDAR-Based Traffic Movement Count Estimation at a Signalized Intersection: Deployment, Data Collection, and Preliminary Analysis
ILNet: Trajectory Prediction with Inverse Learning Attention for Enhancing Intention Capture
Temporal Continual Learning with Prior Compensation for Human Motion Prediction
Stochastic Human Motion Prediction with Memory of Action Transition and Action Characteristic
GoIRL: Graph-Oriented Inverse Reinforcement Learning for Multimodal Trajectory Prediction
AnchorDP3: 3D Affordance Guided Sparse Diffusion Policy for Robotic Manipulation
FlightKooba: A Fast Interpretable FTP Model
SceneAware: Scene-Constrained Pedestrian Trajectory Prediction with LLM-Guided Walkability
Recent Advances in Multi-Agent Human Trajectory Prediction: A Comprehensive Review
ECAM: A Contrastive Learning Approach to Avoid Environmental Collision in Trajectory Forecasting
TrajFlow: Multi-modal Motion Prediction via Flow Matching
IntTrajSim: Trajectory Prediction for Simulating Multi-Vehicle driving at Signalized Intersections
Evaluating Generative Vehicle Trajectory Models for Traffic Intersection Dynamics
Egocentric Event-Based Vision for Ping Pong Ball Trajectory Prediction
Mobility-Aware Asynchronous Federated Learning with Dynamic Sparsification
Trajectory Entropy: Modeling Game State Stability from Multimodality Trajectory Prediction
Learning dissection trajectories from expert surgical videos via imitation learning with equivariant diffusion
FRED: The Florence RGB-Event Drone Dataset
Joint Routing and Control Optimization in VANET
Trajectory Prediction Meets Large Language Models: A Survey
Towards Predicting Any Human Trajectory In Context
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation
Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models
Towards Human-Like Trajectory Prediction for Autonomous Driving: A Behavior-Centric Approach
Echo Planning for Autonomous Driving: From Current Observations to Future Trajectories and Back
SOLVE: Synergy of Language-Vision and End-to-End Networks for Autonomous Driving
Generative AI for Autonomous Driving: A Review
UPTor: Unified 3D Human Pose Dynamics and Trajectory Prediction for Human-Robot Interaction
Multi-Resolution Haar Network: Enhancing human motion prediction via Haar transform
CacheFlow: Fast Human Motion Prediction by Cached Normalizing Flow
EgoDex: Learning Dexterous Manipulation from Large-Scale Egocentric Video
MambaControl: Anatomy Graph-Enhanced Mamba ControlNet with Fourier Refinement for Diffusion-Based Disease Trajectory Prediction
Quantum-Enhanced Parameter-Efficient Learning for Typhoon Trajectory Forecasting
Towards Accurate State Estimation: Kalman Filter Incorporating Motion Dynamics for 3D Multi-Object Tracking
Human Motion Prediction via Test-domain-aware Adaptation with Easily-available Human Motions Estimated from Videos
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