SDP-GAN: Saliency Detail Preservation Generative Adversarial Networks for High Perceptual Quality Style Transfer-Reference-Cited by-同舟云学术

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SDP-GAN: Saliency Detail Preservation Generative Adversarial Networks for High Perceptual Quality Style Transfer

Published:2021 Issue: Volume:30 Page:374-385
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Li Ru^ORCID,Wu Chi-Hao^ORCID,Liu Shuaicheng^ORCID,Wang Jue^ORCID,Wang Guangfu^ORCID,Liu Guanghui^ORCID,Zeng Bing^ORCID

Funder

National Natural Science Foundation of China

“111” Projects

Sichuan Science and Technology Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9263394/09259251.pdf?arnumber=9259251

Cited by 25 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. ReLU-oscillator: Chaotic VGG10 model for real-time neural style transfer on painting authentication;Expert Systems with Applications;2024-12

2. HDMA-CGAN: Advancing Image Style Transfer with Deep Learning;International Journal of Pattern Recognition and Artificial Intelligence;2024-06-29

3. MCLGAN: a multi-style cartoonization method based on style condition information;The Visual Computer;2024-06-21

4. Saliency Guided Deep Neural Network for Color Transfer With Light Optimization;IEEE Transactions on Image Processing;2024

5. Attention-guided cross-modal multiple feature aggregation network for RGB-D salient object detection;Electronic Research Archive;2024

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