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Object Tracking

jdt3d

Paper         Code

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.png

Paper         Code

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_arch_new.png

Paper         Code

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.PNG

Paper        Video

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.png

Paper       Video       Dataset

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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