ThermoStereoRT: Thermal Stereo Matching in Real Time via Knowledge Distillation and Attention-based Refinement
Journal:
arXiv
Published Date:
Apr 10, 2025
Abstract
We introduce ThermoStereoRT, a real-time thermal stereo matching method
designed for all-weather conditions that recovers disparity from two rectified
thermal stereo images, envisioning applications such as night-time drone
surveillance or under-bed cleaning robots. Leveraging a lightweight yet
powerful backbone, ThermoStereoRT constructs a 3D cost volume from thermal
images and employs multi-scale attention mechanisms to produce an initial
disparity map. To refine this map, we design a novel channel and spatial
attention module. Addressing the challenge of sparse ground truth data in
thermal imagery, we utilize knowledge distillation to boost performance without
increasing computational demands. Comprehensive evaluations on multiple
datasets demonstrate that ThermoStereoRT delivers both real-time capacity and
robust accuracy, making it a promising solution for real-world deployment in
various challenging environments. Our code will be released on
https://github.com/SJTU-ViSYS-team/ThermoStereoRT
