RealFill: Reference-Driven Generation for Authentic Image Completion
RealFill: Reference-Driven Generation for Authentic Image Completion
Recent advances in generative imagery have brought forth outpainting and inpainting models that can produce high-quality, plausible image content in unknown regions. However, the content these models hallucinate is necessarily inauthentic, since they are unaware of the true scene. In this work, we propose RealFill, a novel generative approach for …