[1/10] 🚨 We present our recent @Snap project: Stable Flow --- A training-free method that performs various types of image editing operations (e.g., non-rigid editing, object addition and replacement) using flow models. Project page: omriavrahami.com/stable-flow

[1/10] 🚨 We present our recent @Snap project: Stable Flow --- A training-free method that performs various types of image editing operations (e.g., non-rigid editing, object addition and replacement) using flow models. Project page: omriavrahami.com/stable-flow

The Chosen One: Consistent Characters in Text-to-Image Diffusion Models paper page: huggingface.co/papers/2311.1… Recent advances in text-to-image generation models have unlocked vast potential for visual creativity. However, these models struggle with generation of consistent characters, a crucial aspect for numerous real-world applications such as story visualization, game development asset design, advertising, and more. Current methods typically rely on multiple pre-existing images of the target character or involve labor-intensive manual processes. In this work, we propose a fully automated solution for consistent character generation, with the sole input being a text prompt. We introduce an iterative procedure that, at each stage, identifies a coherent set of images sharing a similar identity and extracts a more consistent identity from this set. Our quantitative analysis demonstrates that our method strikes a better balance between prompt alignment and identity consistency compared to the baseline methods, and these findings are reinforced by a user study. To conclude, we showcase several practical applications of our approach.

#ECCV2022 list of paper IDs of accepted papers is NOW available! eccv2022.ecva.net/submission…

Blended Diffusion for Text-driven Editing of Natural Images abs: arxiv.org/abs/2111.14818 introduce solution for performing local (region-based) edits in generic natural images, based on a natural language description along with an ROI mask