# FastTrack: GPU-Accelerated Tracking for Visual SLAM

arXiv: https://arxiv.org/abs/2509.10757 · HTML: https://mlsanity.com/paper/2509.10757/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Sep 2025.

## Built on by (most cited first, 2 of 2)

- [VkVIO: Cross-platform GPU Acceleration for Visual-Inertial Odometry with Vulkan](https://mlsanity.com/paper/2609.30459/) (2026)
- [HexVIO: Towards All-Day Stereo-Inertial Tracking Through Commodity DSPs](https://mlsanity.com/paper/2610.03283/) (2026)

## Abstract (arXiv)

The tracking module of a visual-inertial SLAM system processes incoming image frames and IMU data to estimate the position of the frame in relation to the map. It is important for the tracking to complete in a timely manner for each frame to avoid poor localization or tracking loss. We therefore present a new approach which leverages GPU computing power to accelerate time-consuming components of tracking in order to improve its performance. These components include stereo feature matching and local map tracking. We implement our design inside the ORB-SLAM3 tracking process using CUDA. Our evaluation demonstrates an overall improvement in tracking performance of up to 2.8x on a desktop and Jetson Xavier NX board in stereo-inertial mode, using the well-known SLAM datasets EuRoC and TUM-VI.