Statistics Enhancement Generative Adversarial Networks for Diverse Conditional Image Synthesis-Reference-Cited by-同舟云学术

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Statistics Enhancement Generative Adversarial Networks for Diverse Conditional Image Synthesis

Published:2024-07 Issue:7 Volume:34 Page:6167-6180
ISSN:1051-8215
Container-title:IEEE Transactions on Circuits and Systems for Video Technology
language:
Short-container-title:IEEE Trans. Circuits Syst. Video Technol.

Author:

Zuo Zhiwen¹^ORCID,Li Ailin²^ORCID,Wang Zhizhong²^ORCID,Zhao Lei²^ORCID,Dong Jianfeng¹^ORCID,Wang Xun¹^ORCID,Wang Meng³

Affiliation:

1. College of Computer Science and Technology, Zhejiang Gongshang University, Hangzhou, China

2. College of Computer Science and Technology, Zhejiang University, Hangzhou, China

3. School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China

Funder

Pioneer and Leading Goose Research and Development Program of Zhejiang

Young Elite Scientists Sponsorship Program by China Association for Science and Technology

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/76/10582818/10378665.pdf?arnumber=10378665

Reference115 articles.

1. ImageNet classification with deep convolutional neural networks;Krizhevsky

2. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

3. You Only Look Once: Unified, Real-Time Object Detection

4. Deep Residual Learning for Image Recognition

5. An image is worth 16×16 words: Transformers for image recognition at scale;Dosovitskiy;arXiv:2010.11929,2020

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