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Guoqiang Zhao

2 accepted papers

2025

Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language Guidance

IROS 2025

The perception capability of robotic systems relies on the richness of the dataset. Although Segment Anything Model 2 (SAM2), trained on large datasets, demonstrates strong perception potential in perception tasks, its inherent training paradigm prevents it from being suitable for RGB-T tasks. To ad

Cited by 11SourcecodeScholar
2024

Open-Vocabulary RGB-Thermal Semantic Segmentation

ECCV 2024poster

"RGB-Thermal (RGB-T) semantic segmentation is an important research branch of multi-modal image segmentation. The current RGB-T semantic segmentation methods generally have two unsolved and typical shortcomings. First, they do not have the open-vocabulary recognition ability, which significantly lim…