5 papers
2-Shots in the Dark: Low-Light Denoising with Minimal Data Acquisition
Liying Lu, Raphaël Achddou, Sabine Süsstrunk
Raw images taken in low-light conditions are very noisy due to low photon count and sensor noise. Learning-based denoisers have the potential to reconstruct high-quality images. Fo…
Hölder continuity and composition operators in pluriharmonic Bloch spaces
Jie Huang, Suman Das, Antti Rasila
We show a Hölder estimate of order for pluriharmonic Bloch mappings in the unit ball with respect to the Bergman metric. We apply this to…
Dark Noise Diffusion: Noise Synthesis for Low-Light Image Denoising
Liying Lu, Raphaël Achddou, Sabine Süsstrunk
Low-light photography produces images with low signal-to-noise ratios due to limited photons. In such conditions, common approximations like the Gaussian noise model fall short, an…
Hybrid Training of Denoising Networks to Improve the Texture Acutance of Digital Cameras
Raphaël Achddou, Yann Gousseau, Saïd Ladjal
In order to evaluate the capacity of a camera to render textures properly, the standard practice, used by classical scoring protocols, is to compute the frequential response to a d…
Nested Learning For Multi-Granular Tasks
Raphaël Achddou, J. Matias di Martino, Guillermo Sapiro
Standard deep neural networks (DNNs) are commonly trained in an end-to-end fashion for specific tasks such as object recognition, face identification, or character recognition, amo…