8 citations · 12 across the 6 of their papers we have counts for
6 papers · 1 filter
Specify and Edit: Overcoming Ambiguity in Text-Based Image Editing
Ekaterina Iakovleva, Fabio Pizzati, Philip Torr +1
Text-based editing diffusion models exhibit limited performance when the user's input instruction is ambiguous. To solve this problem, we propose (SANE)…
Towards image compression with perfect realism at ultra-low bitrates
Marlène Careil, Matthew J. Muckley, Jakob Verbeek +1
Image codecs are typically optimized to trade-off bitrate \vs distortion metrics. At low bitrates, this leads to compression artefacts which are easily perceptible, even when train…
Face Aging via Diffusion-based Editing
Xiangyi Chen, Stéphane Lathuilière
In this paper, we address the problem of face aging: generating past or future facial images by incorporating age-related changes to the given face. Previous aging methods rely sol…
Zero-shot spatial layout conditioning for text-to-image diffusion models
Guillaume Couairon, Marlène Careil, Matthieu Cord +2
Large-scale text-to-image diffusion models have significantly improved the state of the art in generative image modelling and allow for an intuitive and powerful user interface to…
Few-shot Semantic Image Synthesis with Class Affinity Transfer
Marlène Careil, Jakob Verbeek, Stéphane Lathuilière
Semantic image synthesis aims to generate photo realistic images given a semantic segmentation map. Despite much recent progress, training them still requires large datasets of ima…
Unifying conditional and unconditional semantic image synthesis with OCO-GAN
Marlène Careil, Stéphane Lathuilière, Camille Couprie +1
Generative image models have been extensively studied in recent years. In the unconditional setting, they model the marginal distribution from unlabelled images. To allow for more…