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Attribute-based classification and the dream of life-long learning for visual scene understanding: VCL Lunch Talk

Seminar: Departmental | March 22 | 12-1 p.m. | Soda Hall, Visual Computing Lab - 510 Soda

Christoph Lampert, Institute of Science and Technology - Austria

Electrical Engineering and Computer Sciences (EECS)

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.