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Explore cutting-edge approaches to addressing data scarcity in machine learning with Andreas Geiger's insightful conference talk. Delve into innovative techniques such as specialized architectures, soft constraints, self-supervision, mixed reality, and label transfer. Gain valuable insights on improving optical flow algorithms and enhancing generalization capabilities in data-hungry applications. Discover how these methods can revolutionize the field of computer vision and help overcome the challenges posed by limited labeled datasets.
Syllabus
Intro
The problem
Optical flow
Specialized architectures
Soft constraints
Self supervision
Mixed Reality
Label Transfer
Generalization
Taught by
Andreas Geiger