Our guest speaker is Laurynas Karazija from the Visual Geometry Group, University of Oxford.

You are all cordially invited to the CVG Seminar on January 12th at 2:30 pm CET

• via Zoom (passcode is 043728).

Abstract

Detecting, localising and representing objects comprising the visual world is an important and interesting problem with many downstream applications. Today's systems are supervised, relying on extensive and expensive manual annotations. In this talk, I will introduce some recent works that explore learning from appearance, motion and language in an unsupervised or weakly-supervised manner. In particular, I will focus on the drawbacks of appearance-based object-centric models, explain how to teach segmentation networks using optical flow in an end-to-end manner and show how pretrained generative diffusion models can be used to synthesise segmenters directly by sampling and representing objects and their context.

Bio

Laurynas Karazija is a PhD student at the Visual Geometry Group at the University of Oxford, UK, working with Prof Andrea Vedaldi, Prof Christian Rupprecht and Dr Iro Laina. He focuses on learning to understand and decompose the visual world into distinct objects with as little supervision as possible.