Biphasic Face Photo-Sketch Synthesis via Semantic-Driven Generative Adversarial Network With Graph Representation Learning

Author:

Qi Xingqun1ORCID,Sun Muyi2ORCID,Wang Zijian3,Liu Jiaming4,Li Qi2,Zhao Fang5ORCID,Zhang Shanghang4ORCID,Shan Caifeng5ORCID

Affiliation:

1. Institute of Automation, Chinese Academy of Sciences, Beijing, China

2. CRIPAC, NLPR, Institute of Automation, Chinese Academy of Sciences, Beijing, China

3. School of Computer Science, The University of Sydney, Sydney, NSW, Australia

4. School of Computer Science, National Key Laboratory for Multimedia Information Processing, Peking University, Beijing, China

5. School of Intelligence Science and Technology, Nanjing University, Nanjing, China

Funder

Talent Introduction Program for Youth Innovation Teams of Shandong Province

National Natural Science Foundation of China

National Key Research and Development Project of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Cited by 5 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. Few-shot face sketch-to-photo synthesis via global-local asymmetric image-to-image translation;ACM Transactions on Multimedia Computing, Communications, and Applications;2024-07-20

2. An accelerated zeroing neural network for solving continuous coupled Lyapunov matrix equations;IET Control Theory & Applications;2024-06-10

3. Face photo-line drawings synthesis based on local extraction preserving generative adversarial networks;The Imaging Science Journal;2024-02-11

4. Few-Shot Face Stylization via GAN Prior Distillation;IEEE Transactions on Neural Networks and Learning Systems;2024

5. Human-Inspired Facial Sketch Synthesis with Dynamic Adaptation;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

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