Neural Fields for Embedded Variational Problems in Imaging

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• Danielle Bednarski (DESY Hamburg)
• Tuesday 03 December 2024, 13:00-14:00
• MR14 Centre for Mathematical Sciences.

If you have a question about this talk, please contact Ferdia Sherry.

Calibration-based functional lifting allows us to embed non-convex variational problems into another space, such that the embedded and relaxed formulation is convex and that global minimizers of the later can be mapped to global minimizers of the original problem. While related theory and results in the continuous setting are very elegant, practical implementation of the calibration-based lifted formulation comes with certain challenges. In the first part of this talk, we look at the theoretic derivation and properties of the (continuous) lifting approach and discuss difficulties encountered using established discretization approaches. In the second part, we introduce a more recent stochastic optimization approach using neural fields and discuss its current restrictions and future prospects.

This talk is part of the Cambridge Image Analysis Seminars series.

This talk is included in these lists:

• Cambridge Image Analysis Seminars
• MR14 Centre for Mathematical Sciences

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