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循环对比对抗式学习与结构一致性无监督的高质量图像脱轨变压器

Chen Zhao1, Weiling Cai1, Chengwei Hu1

  • 1School of Artificial Intelligence, Nanjing Normal University, Nanjing, 210023, China.

Neural networks : the official journal of the International Neural Network Society
|June 20, 2024
PubMed
概括

本研究介绍了CCLformer,这是一种新的无监督单图像脱轨 (SID) 方法. 它通过使用循环对比学习 (CCL) 和位置对比学习 (LCL) 有效地去除雨水,同时保留图像内容.

关键词:
相反的学习学习.生成性对抗性网络 (GAN) 是一种对抗性网络.一个图像脱轨的单一图像视觉变压器 (VIT) 是一个视觉变压器.

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