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    • Semantic Alignment and Locality-Driven Open-Vocabulary Semantic Segmentation

    • The TG-CLIP framework does not require pixel level fine-tuning, improving the quality of open vocabulary semantic segmentation and providing an easy to deploy and robust engineering solution for training free open vocabulary segmentation.
    • Pages: 1-11(2026)   

      Received:29 October 2025

      Revised:2026-01-16

      Accepted:21 January 2026

      Published Online:21 January 2026

    • DOI: 10.11834/jig.250540     

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  • Wang Xinjing, Gao Ying, Zou Yaqi, Zhu Zhengyu, Xu Chunxue, Zhao Qi. Semantic Alignment and Locality-Driven Open-Vocabulary Semantic Segmentation[J/OL]. Journal of Image and Graphics, 2026, 1-11. DOI: 10.11834/jig.250540.
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相关作者

Zheng Hu 北方民族大学计算机科学与工程学院
Yan Hao 北方民族大学计算机科学与工程学院
Bai Jing 北方民族大学计算机科学与工程学院;国家民委图像图形智能处理实验室
Yong Ma 武汉大学电子信息学院;武汉大学宇航科学与技术研究院
Jun Huang 武汉大学电子信息学院;武汉大学宇航科学与技术研究院
Fan Fan 武汉大学电子信息学院;武汉大学宇航科学与技术研究院
Hao Li 武汉轻工大学数学与计算机科学学院
Jiayi Ma 武汉大学电子信息学院;武汉大学宇航科学与技术研究院

相关机构

School of Computer Science and Engineering, North Minzu University
The Key Laboratory of Images and Graphics Intelligent Processing of State Ethnic Affairs Commission
Electronic Information School, Wuhan University
Institute of Aerospace Science and Technology, Wuhan University
College of Mathematics and Computer Science, Wuhan Polytechnic University
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