DiffUTE: Universal Text Editing Diffusion Model

Diffusion model based language-guided image editing has achieved great success recently. However, existing state-of-the-art diffusion models struggle with rendering correct text and text style during generation. To tackle this problem, we propose a universal self-supervised text editing diffusion model (DiffUTE), which aims to replace or modify words in the source image with another one while maintaining its realistic appearance. Specifically, we build our model on a diffusion model and carefully modify the network structure to enable the model for drawing multilingual characters with the help of glyph and position information. Moreover, we design a self-supervised learning framework to leverage large amounts of web data to improve the representation ability of the model. Experimental results show that our method achieves an impressive performance and enables controllable editing on in-the-wild images with high fidelity. Our code will be avaliable in \url{https://github.com/chenhaoxing/DiffUTE}

The afterlife of 'living deliverables': angels or zombies?

Within the STELLAR project, we provide the possibility to use living documents for the collaborative writing work on deliverables. Compared to 'normal' deliverables, 'living' deliverables come into existence much earlier than their delivery deadline and are expected to 'live on' after their official delivery to the European Commission. They are expected to foster collaboration. Within this contribution we investigate, how these deliverables have been used over the first 16 months of the project. We therefore propose a set of new analysis methods facilitating social network analysis on publicly available revision history data. With this instrumentarium, we critically look at whether the living deliverables have been successfully used for collaboration and whether their 'afterlife' beyond the contractual deadline had turned them into 'zombies' (still visible, but no or little live editing activities). The results show that the observed deliverables show signs of life, but often in connection with a topical change and in conjunction with changes in the pattern of collaboration