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Learning to understand dynamic scenes

Date: Tuesday, December 12, 2017 15:00 - 16:00
Speaker: Laura Leal-Taixe (TUM)
Location: Mondi Seminar Room 2, Central Building
Series: CS Talk Series
Host: Christoph Lampert

Abstract:

Dynamic scene understanding englobes many of the classic problems in Computer Vision. Semantically labelling every pixel in a video sequence is a big step towards understanding the world around us, and is key to applications such as autonomous driving or human-robot interaction. In this talk, I will present several works that bring us closer to solving the problem of dynamic scene understanding, focusing especially on the role of Deep Learning for video analysis. I will present our recent works on multiple object tracking and video object segmentation and discuss the importance of big data and our efforts towards building a benchmark for multiple object tracking.Finally, I will briefly discuss future research plans and the recently accepted project socialMaps.
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