A Review of Trajectory Prediction Methods for the Vulnerable Road User
Predicting the trajectory of other road users, especially vulnerable road users (VRUs), is an
important aspect of safety and planning efficiency for autonomous vehicles. With recent …
important aspect of safety and planning efficiency for autonomous vehicles. With recent …
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 …
Adversarial Backdoor Attack by Naturalistic Data Poisoning on Trajectory Prediction in Autonomous Driving
M Pourkeshavarz, M Sabokrou… - Proceedings of the …, 2024 - openaccess.thecvf.com
In autonomous driving behavior prediction is fundamental for safe motion planning hence
the security and robustness of prediction models against adversarial attacks are of …
the security and robustness of prediction models against adversarial attacks are of …
[HTML][HTML] Privacy-preserving pedestrian tracking with path image inpainting and 3D point cloud features
Tracking pedestrian flow in large public areas is vital, yet ensuring privacy is paramount.
Traditional visual-based tracking systems are raising concerns for potentially obtaining …
Traditional visual-based tracking systems are raising concerns for potentially obtaining …
CaDeT: a Causal Disentanglement Approach for Robust Trajectory Prediction in Autonomous Driving
M Pourkeshavarz, J Zhang… - Proceedings of the IEEE …, 2024 - openaccess.thecvf.com
For safe motion planning in real-world autonomous vehicles require behavior prediction
models that are reliable and robust to distribution shifts. The recent studies suggest that the …
models that are reliable and robust to distribution shifts. The recent studies suggest that the …
T4P: Test-Time Training of Trajectory Prediction via Masked Autoencoder and Actor-specific Token Memory
Trajectory prediction is a challenging problem that requires considering interactions among
multiple actors and the surrounding environment. While data-driven approaches have been …
multiple actors and the surrounding environment. While data-driven approaches have been …
UniTraj: A Unified Framework for Scalable Vehicle Trajectory Prediction
Vehicle trajectory prediction has increasingly relied on data-driven solutions, but their ability
to scale to different data domains and the impact of larger dataset sizes on their …
to scale to different data domains and the impact of larger dataset sizes on their …
Forecast-PEFT: Parameter-Efficient Fine-Tuning for Pre-trained Motion Forecasting Models
Recent progress in motion forecasting has been substantially driven by self-supervised pre-
training. However, adapting pre-trained models for specific downstream tasks, especially …
training. However, adapting pre-trained models for specific downstream tasks, especially …
TrACT: A Training Dynamics Aware Contrastive Learning Framework for Long-tail Trajectory Prediction
As a safety critical task, autonomous driving requires accurate predictions of road users'
future trajectories for safe motion planning, particularly under challenging conditions. Yet …
future trajectories for safe motion planning, particularly under challenging conditions. Yet …
AMEND: A Mixture of Experts Framework for Long-tailed Trajectory Prediction
RC Mercurius, E Ahmadi, SMA Shabestary… - arXiv preprint arXiv …, 2024 - arxiv.org
Accurate prediction of pedestrians' future motions is critical for intelligent driving systems.
Developing models for this task requires rich datasets containing diverse sets of samples …
Developing models for this task requires rich datasets containing diverse sets of samples …