#223 · Primary category: Computer Vision

BundleTrack

3d 3d-graphics 3d-reconstruction 6d 6d-object-tracking 6d-pose-estimation 6d-pose-tracking 6dof 6dof-pose 6dof-tracking computer-vision manipulation pose-estimation pose-graph-optimization pose-tracking robotics tracking vision-tracking

[IROS 2021] BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Models

Project last updated:04/13/26

GitHub Stars

686

Forks

72

Contributors

1

License

Apache-2.0

Why we included this project

Most 6D pose trackers assume you have a CAD model of the object, at least at the category level, before you can do anything. BundleTrack drops that requirement: it tracks the full 6D pose of novel objects using only segmentation and feature extraction from deep learning, plus a memory-augmented pose graph optimizer that keeps the estimate consistent over time. The result is long-term, low-drift tracking that holds up under heavy occlusion and fast motion, and the CUDA implementation runs the whole pipeline at about 10Hz, which is fast enough for real-time robotics work. The IROS 2021 paper and code are a solid reference if you are building manipulation or AR systems and do not want to pre-train on the specific object you will be tracking.

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