APF-GAN：探索条件生成式对抗网络的非对称预训练和微调策略

IF 17.3 3区计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING Computational Visual Media Pub Date : 2023-11-30 DOI:10.1007/s41095-023-0357-1

Yuxuan Li, Lingfeng Yang, Xiang Li

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APF-GAN: Exploring asymmetric pre-training and fine-tuning strategy for conditional generative adversarial network

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来源期刊

Computational Visual Media Computer Science-Computer Graphics and Computer-Aided Design

CiteScore

16.90

自引率

5.80%

发文量

243

审稿时长

6 weeks

期刊介绍： Computational Visual Media is a peer-reviewed open access journal. It publishes original high-quality research papers and significant review articles on novel ideas, methods, and systems relevant to visual media. Computational Visual Media publishes articles that focus on, but are not limited to, the following areas: • Editing and composition of visual media • Geometric computing for images and video • Geometry modeling and processing • Machine learning for visual media • Physically based animation • Realistic rendering • Recognition and understanding of visual media • Visual computing for robotics • Visualization and visual analytics Other interdisciplinary research into visual media that combines aspects of computer graphics, computer vision, image and video processing, geometric computing, and machine learning is also within the journal''s scope. This is an open access journal, published quarterly by Tsinghua University Press and Springer. The open access fees (article-processing charges) are fully sponsored by Tsinghua University, China. Authors can publish in the journal without any additional charges.

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