Papers Trajectory Forecasting
“Trajectory Forecasting” 태그가 달린 논문 254편 · 필터 해제
Towards Surgical World-Action Modeling: A Preliminary Joint Visual-Trajectory Forecasting for Surgical Motion Planning
Reliable surgical planning requires models to anticipate not only how instruments will move, but also how the operative visual state will evolve together with such motion. Existing approaches typically treat future scene…
Trajectory ForecastingTrajectory PredictionMotion ForecastingScene GenerationExPhy: A Benchmark for Explicit Physical Property Learning in Multi-Object Trajectory Forecasting
Understanding object dynamics requires not only predicting future trajectories but also examining whether a model captures the physical properties that govern motion. However, existing benchmarks rarely expose object-lev…
Trajectory ForecastingG-MARK: Grounded Multi-Agent Reasoning for Cooperative Driving via Knowledge Graphs
Autonomous driving systems must operate under partial observability, where safety-critical objects may be occluded or visible only to neighboring connected vehicles. Vehicle-to-vehicle cooperation can reduce this uncerta…
Trajectory ForecastingAutonomous DrivingKnowledge GraphsMedical world models in healthcare: foundations, applications, and challenges for trustworthy clinical translation
Medical world models offer a framework for extending medical artificial intelligence beyond static prediction by representing evolving patient states and modelling how they change over time and in response to clinical in…
Trajectory ForecastingLLM-Empowered Multimodal Fusion Framework for Autonomous Driving: Semantic Enhancement and Channel-Adaptive Design
Vision-radar fusion is central to robust autonomous driving, combining dense visual semantics with precise range and velocity measurements from radar. However, real-world fusion quality is fundamentally challenged by dyn…
Trajectory ForecastingImage ReconstructionAutonomous DrivingTowards Metric-Agnostic Trajectory Forecasting
Accurate trajectory forecasting of surrounding traffic participants is a core capability for autonomous driving, enabling vehicles to anticipate behavior and plan safe maneuvers. We observe that current state-of-the-art …
Trajectory ForecastingAutonomous DrivingDiffusion-based 4D Trajectory Prediction and Distributed Control for UAV Swarms
Accurate 4D trajectory prediction and closed-loop tracking are essential for Unmanned Aerial Vehicle (UAV) swarms to achieve safe and efficient operations in complex low-altitude environments such as urban airspaces, ind…
Trajectory ForecastingTrajectory PredictionPhysics-Grounded Disentangled Flow Modeling for Brain Disease Progression Trajectory
Forecasting longitudinal brain lesion evolution is critical for disease monitoring and treatment planning. Existing approaches typically learn a direct mapping from a baseline image to a future observation, without expli…
Trajectory ForecastingRethinking Training & Inference for Forecasting: Linking Winner-Take-All back to GMMs
Trajectory forecasting for autonomous driving has advanced rapidly, yet representative models often produce uninformative posteriors over forecast modes, causing problems for mode pruning. We trace this to a modeling-tra…
Trajectory ForecastingAutonomous DrivingNavWM: A Unified Navigation World Model for Foresight-Driven Planning
Conventional visual navigation policies often struggle with myopic decision-making and mode collapse in complex environments. While world models offer a promising alternative, existing paradigms typically isolate percept…
Trajectory ForecastingVisual NavigationContinuous-Time Probabilistic Correctors for Uncertainty-Aware Physics-Based Spacecraft Trajectory Forecasting
Long-horizon spacecraft trajectory forecasting suffers from error accumulation due to the absence of corrective observations in the forecast regime, making reliable uncertainty estimation crucial for safety-critical deci…
Trajectory ForecastingEventDrive: Event Cameras for Vision-Language Driving Intelligence
Event cameras sense the world through asynchronous brightness changes with microsecond latency and high dynamic range, offering motion fidelity far beyond frame-based sensors and capturing temporal structure that convent…
Trajectory ForecastingAutonomous DrivingEnvShip-Bench: An Environment-Enhanced Benchmark for Short-Term Vessel Trajectory Prediction
Vessel trajectory prediction is important for intelligent shipping, maritime surveillance, and navigation safety. However, existing public maritime AIS resources are often limited by inconsistent forecasting protocols, u…
Trajectory ForecastingTrajectory PredictionTransition-Based Digital Twin Modelling for Alzheimer's Disease under Sparse Longitudinal Data
Alzheimer's disease (AD) progression is highly heterogeneous and is typically observed through sparse and irregular longitudinal data, posing challenges for prediction and personalised monitoring. Existing machine learni…
Trajectory ForecastingValidation-Gated Multi-Agent Governance for Online Adaptation of Thermal-Hydraulic Surrogate Models under Operating-Regime Shift
Artificial-intelligence surrogates can support second-by-second thermal-hydraulic forecasting, but models selected and frozen offline may become condition-locked once deployed outside their pretraining envelope. This stu…
Trajectory ForecastingGraph Neural NetworkMUSCLE-NET: Predicted-Multiscale-Aware Network for Pedestrian Trajectory Forecasting
Accurate pedestrian trajectory prediction is essential for safe navigation in autonomous driving and intelligent transportation systems. Despite substantial progress made by recent methods, most existing approaches are l…
Trajectory ForecastingTrajectory PredictionAutonomous DrivingBatteryMFormer: Multi-level Learning for Battery Degradation Trajectory Forecasting
Early battery degradation trajectory forecasting (BDTF), which predicts the full-life state-of-health trajectory from early operational data, is critical for battery optimization, manufacturing, and deployment. Battery d…
Trajectory ForecastingPEDESTRIANQA: A Benchmark for Vision-Language Models on Pedestrian Intention and Trajectory Prediction
Pedestrian intention and trajectory prediction are critical for the safe deployment of autonomous driving systems, directly influencing navigation decisions in complex traffic environments. Recent advances in large visio…
Trajectory ForecastingTrajectory PredictionAutonomous DrivingChronoMedicalWorld: A Medical World Model for Learning Patient Trajectories from Longitudinal Care Data
Long-horizon clinical simulation -- predicting how a patient's physiology evolves over years under specified interventions -- is central to chronic-disease care, yet existing electronic health record (EHR) models are pre…
Trajectory ForecastingHierarchical Two-Stage Framework for Environment-Aware Long-Horizon Vessel Trajectory Prediction
Long-horizon vessel trajectory forecasting under real ocean conditions is critical for collision avoidance, traffic management, and route planning. However, achieving accurate predictions is challenging due to long-range…
Trajectory ForecastingTrajectory PredictionCollision Avoidance