activity
20182023
most citedProbabilistic 3D Multi-Object Tracking for Autonomous Driving

45 citations · 45 across the 2 of their papers we have counts for

collaborators

7 papers

cs.CV2023

Collision Avoidance Detour for Multi-Agent Trajectory Forecasting

Hsu-kuang Chiu, Stephen F. Smith

We present our approach, Collision Avoidance Detour (CAD), which won the 3rd place award in the 2023 Waymo Open Dataset Challenge - Sim Agents, held at the 2023 CVPR Workshop on Au…

cs.RO2023

Selective Communication for Cooperative Perception in End-to-End Autonomous Driving

Hsu-kuang Chiu, Stephen F. Smith

The reliability of current autonomous driving systems is often jeopardized in situations when the vehicle's field-of-view is limited by nearby occluding objects. To mitigate this p…

cs.CV2020

Probabilistic 3D Multi-Modal, Multi-Object Tracking for Autonomous Driving

Hsu-kuang Chiu, Jie Li, Rares Ambrus +1

Multi-object tracking is an important ability for an autonomous vehicle to safely navigate a traffic scene. Current state-of-the-art follows the tracking-by-detection paradigm wher…

cs.CV202045 cited

Probabilistic 3D Multi-Object Tracking for Autonomous Driving

Hsu-kuang Chiu, Antonio Prioletti, Jie Li +1

3D multi-object tracking is a key module in autonomous driving applications that provides a reliable dynamic representation of the world to the planning module. In this paper, we p…

cs.CV2019

Imitation Learning for Human Pose Prediction

Borui Wang, Ehsan Adeli, Hsu-kuang Chiu +2

Modeling and prediction of human motion dynamics has long been a challenging problem in computer vision, and most existing methods rely on the end-to-end supervised training of var…

cs.CV2019

Segmenting the Future

Hsu-kuang Chiu, Ehsan Adeli, Juan Carlos Niebles

Predicting the future is an important aspect for decision-making in robotics or autonomous driving systems, which heavily rely upon visual scene understanding. While prior work att…