Trajectory Modeling
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Benchmarks
NBA SportVU
Most implemented
SIND: A Drone Dataset at Signalized Intersection in China
Capturing Token Tendencies for Training-Free Token Pruning in Multimodal Large Language Models
Q-value Regularized Transformer for Offline Reinforcement Learning
Papers
Conditional Trajectory Peaks: Single-Pass Multimodal Policies over Action Chunks
Multimodal imitation learning requires diverse executable futures under the same observation and consistent behavior across replanning cycles. We present Conditional Trajectory Peaks (CTP), a single-pass policy framework…
Trajectory ModelingDynin-Robotics: Omnimodal Unified Diffusion Vision-Language-Action Model
Visual goal and dynamics prediction can provide language-conditioned robot policies with both a target outcome and a representation of action-dependent scene changes. We bring these predictions into action generation and…
Trajectory ModelingASPIRE-VINS: Adaptive Spline-based Visual-inertial Navigation System With Robust 3D Measurement Residuals
Visual-inertial navigation systems estimate six-degree-of-freedom motion by fusing visual and inertial data. Modern discrete-time methods with IMU preintegration provide strong accuracy and efficiency, but keyframe-based…
Trajectory ModelingCapturing Token Tendencies for Training-Free Token Pruning in Multimodal Large Language Models
While visual token pruning is essential for efficient Multimodal Large Language Models (MLLMs), existing training-free methods suffer from a critical limitation: they rely on static, instantaneous heuristics to perform i…
Trajectory ModelingBridging the Gap Between Plausibility and Admissibility: Constraint-Aware Flow Maps for Dynamic Graph Systems
Generative models can support decision-making under uncertainty by producing ensembles of plausible future system trajectories, but statistical plausibility does not ensure structural feasibility. This study investigates…
Trajectory ModelingCylindTrack: Depth-Aware Cylindrical Motion Modeling for Panoramic Multi-Object Tracking
Multi-Object Tracking (MOT) is a core capability for embodied perception, and panoramic cameras are attractive for embodied systems because their 360° field of view reduces blind spots and keeps surrounding targets obser…
Multi-Object TrackingTrajectory Modeling