DirectEdit: Step-Level Accurate Inversion for Flow-Based Image Editing
With recent advancements in large-scale pre-trained text-to-image (T2I) models, training-free image editing methods have demonstrated remarkable success. Typically, these methods involve adding noise to a clean image via an inversion process, followed by separate denoising steps for the reconstruction and editing paths during the forward process. However, since the reconstruction path is approximated using noisy latents from mismatched timesteps, existing methods inevitably suffer from accumulated drift, which fundamentally limits reconstruction fidelity. To address this challenge, we systematically analyze the inversion process within the flow transformer and propose DirectEdit, a simple...
| Authors | Desong Yang, Mang Ye |
|---|---|
| Primary category | cs.CV |
| Published | 4 May 2026 |
| Last updated at source | 27 May 2026 |
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