Welcome to Qi Mao's Homepage!
Qi Mao (毛 琪)
Lecturer (讲师)
State Key Laboratory of Media Convergence and Communication, Communication University of China
qimao@cuc.edu.cn
About Me
I am now a lecturer at State Key Laboratory of Media Convergence and Communication, Communication University of China.
I have obtained my P.H.D degree from Peking University in July, 2021. (Institute of Digital Media which is directed by Prof. Wen Gao)
I received the B.E. degree in Digital Media Technology and B.A. degree in Journalism in 2016 from Communication University of China.
My current research interests lie in
Image Synthesis especially Image-to-Image Translation
Deep Learning especially Deep Generative Models
Image/Video Compression based on Generative Models.
I am supervised by Prof. Siwei Ma and have been a visiting Ph.D. student at Vision and Learning Lab at University of California, Merced, under the supervision of Prof. Ming-Hsuan Yang
I am lucky to have opportunities to work with Dr. Hsin-Ying Lee (Snap research), Dr. Hung-Yu Tseng (Meta), Dr.Jia-Bin Huang (University of Maryland), Dr. Shiqi Wang (City University of Hong Kong), Dr. Xinfeng Zhang (University of Chinese Academy of Sciences), and Dr. Shanshe Wang (Peking University)
I am a GAN lover and hope to combine AI with art and fashion :-)
Publications
[1] J. Chang, Z. Zhao, C. Jia, S. Wang, L. Yang, Q. Mao, J. Zhang, S. Ma, Conceptual compression via deep structure and texture synthesis, IEEE Transactions on Image Processing (TIP), 2022.[Paper]
[2] Q. Mao, H.-Y. Tseng, H.-Y. Lee, J.-B. Huang, S. Ma, and M.-H. Yang, Continuous and Diverse Image-to-Image Translation via Signed Attribute Vectors, International Journal of Computer Vision (IJCV) , 2022. [Paper] [Project]
[3]H.-Y. Lee*, H.-Y. Tseng*, Q. Mao*, J.-B. Huang, Y.-D. Lu, M. K. Singh, and M.-H. Yang, DRIT++: Diverse Image-to-Image Translation via Disentangled Representations, International Journal of Computer Vision (IJCV) ,2020.(* equal contribution)
[4]Q. Mao*, H.-Y. Lee*, H.-Y. Tseng*, S. Ma, and M.-H. Yang, Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis, 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA, Jun., 2019. (* equal contribution)[Paper] [Project]
[5] Q. Mao, S. Wang, X. Zhang, S. Wang, and S. Ma, Fidelity or Quality? A Region-aware Framework for Enhanced Image Decoding via Hybrid Neural Networks, 2019 IEEE International Conference On Image Processing (ICIP), Taipei, Taiwan, Sep., 2019.
[6] J. Chang, Q. Mao, Z. Zhao, S. Wang, S. Wang, H. Zhu, and S. Ma, Layered Conceptual Image Compression Via Deep Semantic Synthesis, 2019 IEEE International Conference On Image Processing (ICIP), Taipei, Taiwan, Sep., 2019.
[7]Q. Mao, S. Wang, X. Zhang, S. Wang, and S. Ma, Enhanced Image Decoding via Edge-preserving Generative Adversarial Network, 2018 IEEE International Conference on Multimedia and Expo (ICME), San Diego, USA, Jul., 2018. (Oral Presentation)
Early Work
[1]Q. Mao, S. Wang, S. Ma, Local Disparity Vector Derivation Scheme in 3D-AVS2, The 9th Image and Graphics (ICIG), Shanghai, 2017. (Oral Presentation)
[2]Q. Mao, S. Wang, J. Su, X. Zhang, X. Zhang and S. Ma, A local-adapted disparity vector derivation scheme for 3D-AVS, 2016 Visual Communications and Image Processing (VCIP), Chengdu, 2016. (Oral Presentation)