Huazhong University of Science and Technology & VIVO AI Lab · Image Editing

PixelHacker

PixelHacker is a diffusion-based image inpainting model that uses latent categories guidance (LCG) to maintain structural and semantic consistency by encoding foreground/background representations as fixed-size embeddings injected via linear attention during denoising. Trained on a 14M image-mask pair dataset, it achieves state-of-the-art results on Places, CelebA-HQ, and FFHQ benchmarks.