FlexEdit: Flexible and Controllable Diffusion-based Object-centric Image
  Editing
Authors: name: Trong-Tung Nguyen, name: Duc-Anh Nguyen, name: Anh Tran, name: Cuong Pham

Our work addresses limitations seen in previous approaches for object-centric
editing problems, such as unrealistic results due to shape discrepancies and
limited control in object replacement or insertion. To this end, we introduce
FlexEdit, a flexible and controllable editing framework for objects where we
iteratively adjust latents at each denoising step using our FlexEdit block.
Initially, we optimize latents at test time to align with specified object
constraints. Then, our framework employs an adaptive mask, automatically
extracted during denoising, to protect the background while seamlessly blending
new content into the target image. We demonstrate the versatility of FlexEdit
in various object editing tasks and curate an evaluation test suite with
samples from both real and synthetic images, along with novel evaluation
metrics designed for object-centric editing. We conduct extensive experiments
on different editing scenarios, demonstrating the superiority of our editing
framework over recent advanced text-guided image editing methods. Our project
page is published at https://flex-edit.github.io/.