VASC Seminar: Christoph Lampert
Attribute-based classification and the dream of life-long learning for scene understanding
The goal of life-long visual learning is to developing techniques that can continuously and autonomously learn from visual data, potentially for years or decades. During this time the system should build an ever-improving base of generic visual information, and use it as background knowledge and context for solving specific computer vision tasks.
In my talk, I will introduce some challenges one faces when trying to develop life-long learning computer vision systems and I will discuss some of our recent work on attribute-based and other representations that aim at addressing these challenges.
Host: Bernardo Pires
Appointments: Bernardo Pires (email@example.com)
Christoph Lampert received the PhD degree in mathematics from the University of Bonn in 2003. Since 2010 he is an assistant professor at the Institute of Science and Technology Austria (IST Austria), where he heads a research group for computer vision and machine learning. Dr Lampert's research won several international and national awards, including the best paper prize of CVPR 2008 and best student paper award of ECCV 2008. In 2012 he was awarded an ERC Starting Grant by the European Research Council. He is an Associate Editor of the IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI) and Action Editor of the Journal for Machine Learning Research (JMLR).