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Jiexin Luo

2 accepted papers

2025

Playing to the Strengths of High- and Low-Resolution Cues for Ultra-High Resolution Image Segmentation

RA-L 2025

In ultra-high resolution image segmentation task for robotic platforms like UAVs and autonomous vehicles, existing paradigms process a downsampled input image through a deep network and the original high-resolution image through a shallow network, then fusing their features for final segmentation. A

Cited by 1SourceScholar
2024

Memory-Constrained Semantic Segmentation for Ultra-High Resolution UAV Imagery

RA-L 2024

Ultra-high resolution image segmentation poses a formidable challenge for UAVs with limited computation resources. Moreover, with multiple deployed tasks (e.g., mapping, localization, and decision making), the demand for a memory efficient model becomes more urgent. This letter delves into the intri

Cited by 13SourceScholar