Search Results for author: Daniel Heydecker

Found 4 papers, 0 papers with code

Delving Into Deep Walkers: A Convergence Analysis of Random-Walk-Based Vertex Embeddings

no code implementations21 Jul 2021 Dominik Kloepfer, Angelica I. Aviles-Rivero, Daniel Heydecker

Firstly, we prove that, under some weak assumptions, vertex embeddings derived from random walks do indeed converge both in the single limit of the number of random walks $N \to \infty$ and in the double limit of both $N$ and the length of each random walk $L\to\infty$.

Dynamic Spectral Residual Superpixels

no code implementations10 Oct 2019 Jianchao Zhang, Angelica I. Aviles-Rivero, Daniel Heydecker, Xiaosheng Zhuang, Raymond Chan, Carola-Bibiane Schönlieb

We consider the problem of segmenting an image into superpixels in the context of $k$-means clustering, in which we wish to decompose an image into local, homogeneous regions corresponding to the underlying objects.


Mirror, Mirror, on the Wall, Who's Got the Clearest Image of Them All? - A Tailored Approach to Single Image Reflection Removal

no code implementations29 May 2018 Daniel Heydecker, Georg Maierhofer, Angelica I. Aviles-Rivero, Qingnan Fan, Dong-Dong Chen, Carola-Bibiane Schönlieb, Sabine Süsstrunk

Removing reflection artefacts from a single image is a problem of both theoretical and practical interest, which still presents challenges because of the massively ill-posed nature of the problem.

Reflection Removal

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