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

TL;DR
FlexEdit is a novel framework for object-centric image editing that iteratively adjusts latents during denoising, enabling realistic, controllable, and seamless object modifications with automatic background protection.
Contribution
We introduce FlexEdit, a flexible, controllable object editing framework that optimizes latents iteratively and employs adaptive masks for seamless object editing.
Findings
Outperforms recent text-guided image editing methods.
Demonstrates versatility across various editing scenarios.
Introduces new evaluation metrics for object-centric editing.
Abstract
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…
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Taxonomy
TopicsImage Retrieval and Classification Techniques
MethodsALIGN
