FlexEdit: Flexible and Controllable Diffusion-based Object-centric Image
  Editing
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/.
6604e02369c47cd78fde0c3a
Trong-Tung Nguyen
claimed_verified
2024-03-28T16:39:43.587Z
640052b2f4ff62c2616af567
https://cdn-avatars.huggingface.co/v1/production/uploads/640052b2f4ff62c2616af567/PmMNDQtSgdJ_74IFoYdpp.jpeg
NGUYEN TRONG TUNG
user
Tung11
6604e02369c47cd78fde0c3b
Duc-Anh Nguyen
6604e02369c47cd78fde0c3c
Anh Tran
claimed_verified
2024-12-05T09:30:06.052Z
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/avatars/0c34fdaecd7bd8aaffb3d68e83c0eeaf.svg
Anh Tran
user
anhttran1111
6604e02369c47cd78fde0c3d
Cuong Pham
FlexEdit: Flexible and Controllable Diffusion-based Object-centric Image
  Editing
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/.
FlexEdit is a flexible and controllable object-centric editing framework that uses iterative latent adjustment and adaptive masking to improve realism and control in object replacement and insertion.
FlexEdit object-centric editing latents denoising steps adaptive mask text-guided image editing