[CVPR 2025] ArtiFade: Learning to Generate High-quality Subject from Blemished Images

Overview of ArtiFade. On the left, we present artifact rectification training, which involves an iterative process of calculating reconstruction loss between an unblemished image and the reconstruction of its blemished embedding. The right-hand side is the inference stage that tests ArtiFade on unseen blemished images. To avoid ambiguity, we (1) simplify the training of Textual Inversion into an input-output form, and (2) use “fine-tuning” and “inference” to respectively refer to the fine-tuning stage of ArtiFade and the use of ArtiFade for subject-driven generation.