Workshop and Challenge on Learned Image Compression

Director of the Institute of Information and Communication Networks Engineering. Prof. Yu has been ISO/IEC JTC 1 / SC 29 / WG11 (MPEG) Video Chair since Jan. 2018. And she is Membership Chair of Visual Signal Processing and Communication TC and Elected Chair of Circuits and Systems Education and Outreach TC of IEE E Circuits and Systems Society, Steering Committee member of Picture Coding Symposim. She acted as Video Chair of the Audio and Video Coding Standardization Working Group of China (AVS) for 13 years, general chair of the 15th Workshop on Packet Video in 2016. Her research area is visual perception, visual perceptual quality assessment, visual signal representation and coding, multimedia intelligent processing, and related ASIC and SoC design, in which she is a principal investigator of a number of national R&D projects such as Natural Science Foundation of China, 863 Hi-tech Program and inventor of 80+ granted patents. She published more than 100 technical papers and contributed hundreds proposals to international and national standards in the past years.Read More

Nils Thuerey is an Associate-Professor at the Technical University of Munich (TUM). He focuses on deep-learning methods for physical data, with a special emphasis on fluids. Beyond latent-space simulation algorithms and learning with differentiable solvers, generative models have been a central theme of his work. Motivated by time-dependent problems from the physics area, Nils especially focuses on spatio-temporal data such as videos. Here, self-supervision in space as well as time has shown lots of promise, e.g., in form of the TecoGAN model, which can handle video super-resolution as well as unpaired video translation.Read More

Tom is a machine learning researcher at UCL, London. Currently working towards his PhD, he has worked on probabilistic generative modelling and variational methods. He has made a novel contribution to lossless compression by being a part of the research team that developed BB-ANS, a way to convert latent variable ML models such as VAEs into practical lossless compression systems. Before beginning his PhD, he worked in quantitative finance and Fintech, after getting his BA & Master's in Maths from the University of Cambridge.Read More

Yochai recently completed his PhD thesis at the Technion, Israel, where he focused on fundamental tradeoffs in image compression and restoration. His contributions include theoretical research on the role of perceptual quality within modern image restoration and compression algorithms, as well as novel methodologi es for properly evaluating their performance. As part of this research, he co-organized the PIRM workshop and challenges at ECCV 2018, which promoted perceptual-quality-aware algorithms and evaluation schemes. Yochai is now working at Google on automated medicine through intelligent imaging.Read More