Trajectory unified transformer for pedestrian trajectory prediction
Pedestrian trajectory prediction is an essentially connecting link to understanding human
behavior. Recent works achieve state-of-the-art performance gained from the hand …
behavior. Recent works achieve state-of-the-art performance gained from the hand …
Eigentrajectory: Low-rank descriptors for multi-modal trajectory forecasting
Capturing high-dimensional social interactions and feasible futures is essential for
predicting trajectories. To address this complex nature, several attempts have been devoted …
predicting trajectories. To address this complex nature, several attempts have been devoted …
Unsupervised sampling promoting for stochastic human trajectory prediction
The indeterminate nature of human motion requires trajectory prediction systems to use a
probabilistic model to formulate the multi-modality phenomenon and infer a finite set of …
probabilistic model to formulate the multi-modality phenomenon and infer a finite set of …
Uncovering the missing pattern: Unified framework towards trajectory imputation and prediction
Trajectory prediction is a crucial undertaking in understanding entity movement or human
behavior from observed sequences. However, current methods often assume that the …
behavior from observed sequences. However, current methods often assume that the …
Bcdiff: Bidirectional consistent diffusion for instantaneous trajectory prediction
The objective of pedestrian trajectory prediction is to estimate the future paths of pedestrians
by leveraging historical observations, which plays a vital role in ensuring the safety of self …
by leveraging historical observations, which plays a vital role in ensuring the safety of self …
A set of control points conditioned pedestrian trajectory prediction
Predicting the trajectories of pedestrians in crowded conditions is an important task for
applications like autonomous navigation systems. Previous studies have tackled this …
applications like autonomous navigation systems. Previous studies have tackled this …
Adapting to length shift: Flexilength network for trajectory prediction
Trajectory prediction plays an important role in various applications including autonomous
driving robotics and scene understanding. Existing approaches mainly focus on develo** …
driving robotics and scene understanding. Existing approaches mainly focus on develo** …
Multimodal trajectory prediction: A survey
Trajectory prediction is an important task to support safe and intelligent behaviours in
autonomous systems. Many advanced approaches have been proposed over the years with …
autonomous systems. Many advanced approaches have been proposed over the years with …
Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory Prediction
Abstract Language models have demonstrated impressive ability in context understanding
and generative performance. Inspired by the recent success of language foundation models …
and generative performance. Inspired by the recent success of language foundation models …
Progressive pretext task learning for human trajectory prediction
Human trajectory prediction is a practical task of predicting the future positions of
pedestrians on the road, which typically covers all temporal ranges from short-term to long …
pedestrians on the road, which typically covers all temporal ranges from short-term to long …