DFRetouch: Decomposed Face Retouching with Target-oriented Feature Fusion

Face retouching is a composite image editing task, and is challenging in simultaneously accomplishing multiple editing targets, such as removing acne and adjusting skin tone. Existing face retouching methods typically perform global editing without target-specific analysis, which leads to the overlook of certain targets and under-edited output. In this work, we propose DFRetouch, a multi-task face retouching framework that enables multi-target editing by explicitly modeling target-related sub-tasks and progressively modulating target-oriented features. Specifically, we introduce a Face-aware Task Embedding (FTE) module that decomposes user instructions into target-associated sub-tasks and generates task-specific retouching embeddings, which encode the information of the requested operations and the corresponding facial structures. To accomplish multiple retouching objectives, we further design a Sub-task Feature Refinement (SFR) module that stacks task fusion cross-attention blocks to aggregate task-specific embeddings and modulates features conditioned on the resulting representation, thereby synthesizing high-quality retouching results. Extensive experiments demonstrate that DFRetouch outperforms state-of-the-art face retouching methods in terms of visual fidelity and multi-task flexibility.