Shengrong Gu

A Training-Free Framework for High-Fidelity Appearance Transfer via Diffusion Transformers

Diffusion Transformers (DiTs) excel at generation, but their global self-attention makes controllable, reference-image-based editing a distinct challenge. Unlike U-Nets, naively injecting local appearance into a DiT can disrupt its holistic scene structure. We address this by proposing the first tra…