TextRegion: Text-Aligned Region Tokens from Frozen Image-Text Models

• URL: http://arxiv.org/abs/2505.23769v1
• Date: Thu, 29 May 2025 17:59:59 GMT
• Title: TextRegion: Text-Aligned Region Tokens from Frozen Image-Text Models
• Authors: Yao Xiao, Qiqian Fu, Heyi Tao, Yuqun Wu, Zhen Zhu, Derek Hoiem,
• Abstract summary: TextRegion is a simple, effective, and training-free framework that combines the strengths of image-text models and SAM2.<n>These tokens enable detailed visual understanding while preserving open-vocabulary capabilities.
• Score: 16.64400658301794
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Image-text models excel at image-level tasks but struggle with detailed visual understanding. While these models provide strong visual-language alignment, segmentation models like SAM2 offer precise spatial boundaries for objects. To this end, we propose TextRegion, a simple, effective, and training-free framework that combines the strengths of image-text models and SAM2 to generate powerful text-aligned region tokens. These tokens enable detailed visual understanding while preserving open-vocabulary capabilities. They can be directly applied to various downstream tasks, including open-world semantic segmentation, referring expression comprehension, and grounding. We conduct extensive evaluations and consistently achieve superior or competitive performance compared to state-of-the-art training-free methods. Additionally, our framework is compatible with many image-text models, making it highly practical and easily extensible as stronger models emerge. Code is available at: https://github.com/avaxiao/TextRegion.

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