Nested Learning For Multi-Granular Tasks. - Raphaël Achddou; J. Matías Di Martino; Guillermo Sapiro (CoRR, 2020)

Nested Learning for Multi-Level Classification. - Raphaël Achddou; J. Matías Di Martino; Guillermo Sapiro (ICASSP, 2021)

Synthetic Images as a Regularity Prior for Image Restoration Neural Networks. - Raphaël Achddou; Yann Gousseau; Saïd Ladjal (SSVM, 2021)

Learning Raw Image Denoising Using a Parametric Color Image Model. - Raphaël Achddou; Yann Gousseau; Saïd Ladjal (ICIP, 2023)

Hybrid Training of Denoising Networks to Improve the Texture Acutance of Digital Cameras. - Raphaël Achddou; Yann Gousseau; Saïd Ladjal (SSVM, 2023)

Synthetic learning for neural image restoration methods. (Apprentissage synthétique pour les méthodes neuronales de restauration d'images). - Raphaël Achddou (2023)

Fully synthetic training for image restoration tasks. - Raphaël Achddou; Yann Gousseau; Saïd Ladjal (Comput. Vis. Image Underst., 2023)

CNNs for Style Transfer of Digital to Film Photography. - Pierre Mackenzie; Mika Senghaas; Raphaël Achddou (CoRR, 2024)

Noise Synthesis for Low-Light Image Denoising with Diffusion Models. - Liying Lu; Raphaël Achddou; Sabine Süsstrunk (CoRR, 2025)

VibrantLeaves: A principled parametric image generator for training deep restoration models. - Raphaël Achddou; Yann Gousseau; Saïd Ladjal; Sabine Süsstrunk (CoRR, 2025)