Hyperbolic Deep Learning in Computer Vision: A Survey
Pascal Mettes,
Mina Ghadimi Atigh,
Martin Keller-Ressel
et al.
Abstract:Deep representation learning is a ubiquitous part of modern computer vision. While Euclidean space has been the de facto standard manifold for learning visual representations, hyperbolic space has recently gained rapid traction for learning in computer vision. Specifically, hyperbolic learning has shown a strong potential to embed hierarchical structures, learn from limited samples, quantify uncertainty, add robustness, limit error severity, and more. In this paper, we provide a categorization and in-depth ove… Show more
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