3 accepted papers
In this work, we propose using a unified representation, termed **Factorized Features**, for low-level vision tasks, where we test on **Single Image Super-Resolution (SISR)** and **Image Compression**. Motivated by the shared principles between these tasks, they require recovering and preserving fin…
Recent text-to-image (T2I) diffusion models have revolutionized image editing by empowering users to control outcomes using natural language. However the ease of image manipulation has raised ethical concerns with the potential for malicious use in generating deceptive or harmful content. To address…
Large Pre-trained Transformers exhibit an intriguing capacity for in-context learning. Without gradient updates, these models can rapidly construct new predictors from demonstrations presented in the inputs. Recent works promote this ability in the vision-language domain by incorporating visual info…