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Object Tracking
JDT3D: Addressing the Gaps in LiDAR-Based Tracking-by-Attention
Brian Cheong, Jiachen (Jason) Zhou and Steven Waslander
European Conference on Computer Vision (ECCV), 2024.
We propose a novel LiDAR-based joint detection and tracking model that leverages transformer-based decoders to propagate object queries over time, implicitly performing object tracking without an association step at inference.
UncertaintyTrack: Exploiting Detection and Localization Uncertainty in Multi-Object Tracking
Chang Won (John) Lee and Steven Waslander
International Conference on Robotics and Automation (ICRA), 2024.
We introduce a collection of extensions that can be applied to tracking-by-detection trackers to account for localization uncertainty estimates from probabilistic object detectors.
SWTrack: Multiple Hypothesis Sliding Window 3D Multi-Object Tracking
Sandro Papais, Robert Ren, and Steven Waslander
International Conference on Robotics and Automation (ICRA), 2024.
We develop a novel multidimensional graph optimization formulation of multiple hypothesis sliding window tracking for mobile robotics applications.
InterTrack: Interaction Transformer for 3D Multi-Object Tracking
John Willes, Cody Reading, Steven L. Waslander
20th Conference on Robots and Vision (CRV). IEEE, 2023.
Our proposed solution, InterTrack, introduces the Interaction Transformer for 3D MOT to generate discriminative object representations for data association.
aUToTrack: A Lightweight Object Detection and Tracking System for the SAE AutoDrive Challenge
Keenan Burnett, Sepehr Samavi, Steven L. Waslander, Timothy D. Barfoot, Angela P. Schoellig
Conference on Robots and Vision (CRV), 2019
We present a new object tracking dataset (UofTPed50), and propose a lightweight object detection and tracking system (aUToTrack) that achieves SOTA performance on the KITTI Object Tracking benchmark.
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