ECE Colloquium Series: Tsachy Weissman: What Can We Learn from Humans about Compression?
What Can We Learn from Humans about Compression?
Contact firstname.lastname@example.org for ZOOM login info.
Inspired by Shannon's work on estimating the entropy of a language, we experimented with a framework for image compression comprising one human describing images using text instructions to another, who is tasked with reconstructing the original image. These image reconstructions were then rated by human scorers on the Amazon Mechanical Turk platform and compared to reconstructions obtained by existing image compressors. The results suggest potential for substantial improvements over current approaches to lossy compression. I'll describe some of our recent work attempting to deliver on this potential in image, audio and video compression. Bio Tsachy Weissman has been on the faculty of the Electrical Engineering department at Stanford since 2003, where he enjoys activities such as research and teaching the science of information. He has served and still does on editorial boards for scientific journals, technical advisory boards in industry, and as founding director of the Stanford Compression Forum. His favorite gig to date was being an advisor to the HBO show “Silicon Valley” until he was terminated when it was realized his students make for more creative and reliable consultants. He hates writing about himself in the third person.