Self-Supervised Visual Learning and Synthesis

Lecturer: Alexei A. Efros

Event type: Guest lecture

Event time: 2018-06-15 10:00 to 11:00

Place: Lecture hall T1, CS Building, Aalto University, Konemiehentie 2, Espoo

Web page: Helsinki Distinguished Lecture Series on Future IT


Welcome to the next lecture in the Helsinki Distinguished Lecture series on Future Information Technology which will be given by Professor Alexei Efros from UC Berkeley.

The lecture is free of charge and open to everyone interested in the latest research in information technology. Coffee and light refreshments will be served after the lecture.

Please sign up through this link by 11 June.


Computer vision has made impressive gains through the use of deep learning models, trained with large-scale labeled data. However, labels require expertise and curation and are expensive to collect. Can one discover useful visual representations without the use of explicitly curated labels? In this talk, I will present several case studies exploring the paradigm of self-supervised learning — using raw data as its own supervision. Several ways of defining objective functions in high-dimensional spaces will be discussed, including the use of General Adversarial Networks (GANs) to learn the objective function directly from the data. Applications in image synthesis will be shown, including automatic colorization, paired and unpaired image-to-image translation (aka pix2pix and cycleGAN), curiosity-based exploration, and, terrifyingly, #edges2cats.

About the Speaker

Alexei (Alyosha) Efros joined UC Berkeley in 2013. Prior to that, he was nine years on the faculty of Carnegie Mellon University, and has also been affiliated with École Normale Supérieure/INRIA and University of Oxford. His research is in the area of computer vision and computer graphics, especially at the intersection of the two. He is particularly interested in using data-driven techniques to tackle problems where large quantities of unlabeled visual data are readily available. Efros received his PhD in 2003 from UC Berkeley. He is a recipient of CVPR Best Paper Award (2006), NSF CAREER award (2006), Sloan Fellowship (2008), Guggenheim Fellowship (2008), Okawa Grant (2008), Finmeccanica Career Development Chair (2010), SIGGRAPH Significant New Researcher Award (2010), ECCV Best Paper Honorable Mention (2010), 3 Helmholtz Test-of-Time Prizes (2013,2017), and the ACM Prize in Computing (2016).