Papers › A Fast Unified System for 3D Object Detection and Tracking
A Fast Unified System for 3D Object Detection and Tracking
Thomas Heitzinger, Martin Kampel
We present FUS3D, a fast and lightweight system for real-time 3D object detection and tracking on edge devices. Our approach seamlessly integrates stages for 3D object detection and multi-object-tracking into a single, end-to-end trainable model. FUS3D is specially tuned for indoor 3D human behavior analysis, with target applications in Ambient Assisted Living (AAL) or surveillance. The system is optimized for inference on the edge, thus enabling sensor-near processing of potentially sensitive data. In addition, our system relies exclusively on the less privacy-intrusive 3D depth imaging modality, thus further highlighting the potential of our method for application in sensitive areas. FUS3D achieves best results when utilized in a joint detection and tracking configuration. Nevertheless, the proposed detection stage can function as a fast standalone object detection model if required. We have evaluated FUS3D extensively on the MIPT dataset and demonstrated its superior performance over comparable existing state-of-the-art methods in terms of 3D object detection, multi-object tracking, and most importantly, runtime. Model code will be made publicly available.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections