Feng Yang
Feng Yang is a Principal Engineer at Google DeepMind, where he leads the AIM Engine team. He was a postdoctoral researcher at Illumination&Imaging Lab, Robotics Institute, CMU, supervised by Prof. Srinivasa Narasimhan. He interned at Intel Research Center, Beijing advised by Eric Li and Nokia Research, Palo Alto, CA advised by Kari Pulli. He was a Research Assistant with the Broadband Network and Digital Multimedia Laboratory, Tsinghua University, advised by Prof. Qionghai Dai, member of Chinese Academy of Engineering and Audiovisual Communications Laboratory, EPFL, advised by Prof. Martin Vetterli, President of EPFL and member the US National Academy of Engineering. His research interests include deep learning, image quality assessment, digital rights management, image and video synthesis, image and video processing, computational photography, video streaming, distributed video coding, sampling theories, and mobile sensing.
Most recently, he is working on building the next generation image/video processing, serving and storage system with AI. A lot of his algorithms are landed in Google's products and significantly increased the company's revenue and reduced cost.
Feng Yang received the B.Eng. and M.Eng. degrees in automatic control from Tsinghua University, Beijing, China, in 2004 and 2007, respectively. He won Outstanding master thesis of Tsinghua University. He got Ph.D. degree in communication systems at the École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland in 2012. He won Fritz Kutter Award for best PhD thesis. He holds several patents and some of them sold to Rambus Inc.
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Rich Human Feedback for Text to Image Generation
Katherine Collins
Nicholas Carolan
Youwei Liang
Peizhao Li
Dj Dvijotham
Gang Li
Sarah Young
Jiao Sun
Kai Kohlhoff
Arseniy Klimovskiy
2024
SVDiff: Compact Parameter Space for Diffusion Fine-Tuning
Ligong Han
Han Zhang
Dimitris Metaxas
IEEE/CVF International Conference on Computer Vision (ICCV) (2023)
DVMark: A Deep Multiscale Network for Video Watermarking
Huiwen Chang
Ce Liu
IEEE Transactions on Image Processing (2023)
MAXIM: Multi-Axis MLP for Image Processing
Zhengzhong Tu
Han Zhang
Alan Bovik
IEEE/CVF Conference on Computer Vision and Pattern Recognition (2022)
Deep 3D-to-2D Watermarking: Embedding Messages in 3D Meshes and Extracting Them from 2D Renderings
Ce Liu
Huiwen Chang
Innfarn Yoo
Ondrej Stava
Computer Vision and Pattern Recognition (2022)
MaxViT: Multi-Axis Vision Transformer
Zhengzhong Tu
Han Zhang
Alan Bovik
European Conference on Computer Vision (ECCV) (2022)
Better Compression with Deep Pre-Editing
Michael Elad
IEEE Transactions on Image Processing (2021)
COMISR: Compression-Informed Video Super-Resolution
Ce Liu
IEEE/CVF International Conference on Computer Vision (ICCV) (2021)
Deep Perceptual Image Quality Assessment for Compression
ICIP 2021 International Conference on Image Processing (2021)
