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 …
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 …
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 …
Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review
J Belter, M Hering, P Weichbroth - Applied Sciences, 2023 - mdpi.com
Background: In the context of Warehouse Management Systems, knowledge related to
motion trajectory prediction methods utilizing machine learning techniques seems to be …
motion trajectory prediction methods utilizing machine learning techniques seems to be …
Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey
H Cao, W Zou, Y Wang, T Song, M Liu - arXiv preprint arXiv:2210.11237, 2022 - arxiv.org
Since the 2004 DARPA Grand Challenge, the autonomous driving technology has
witnessed nearly two decades of rapid development. Particularly, in recent years, with the …
witnessed nearly two decades of rapid development. Particularly, in recent years, with the …
THÖR-MAGNI: A large-scale indoor motion capture recording of human movement and robot interaction
T Schreiter, T Rodrigues de Almeida… - … Journal of Robotics …, 2024 - journals.sagepub.com
We present a new large dataset of indoor human and robot navigation and interaction,
called THÖR-MAGNI, that is designed to facilitate research on social human navigation: for …
called THÖR-MAGNI, that is designed to facilitate research on social human navigation: for …
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 …