Custom-Edit: Text-Guided Image Editing with Customized Diffusion Models
Text-to-image diffusion models can generate diverse, high-fidelity images
based on user-provided text prompts. Recent research has extended these models
to support text-guided image editing. While text guidance is an intuitive
editing interface for users, it often fails to ensure the precise concept
conveyed by users. To address this issue, we propose Custom-Edit, in which we
(i) customize a diffusion model with a few reference images and then (ii)
perform text-guided editing. Our key discovery is that customizing only
language-relevant parameters with augmented prompts improves reference
similarity significantly while maintaining source similarity. Moreover, we
provide our recipe for each customization and editing process. We compare
popular customization methods and validate our findings on two editing methods
using various datasets.
647015269ba7aeaacb27c080
Jooyoung Choi
claimed_verified
2023-05-26T13:57:32.536Z
62f9e54defd2de85492a4dde
/avatars/9925de0d02b2f2ed03cbafda44fd7de4.svg
Jooyoung Choi
user
jychoi
647015269ba7aeaacb27c081
Yunjey Choi
647015269ba7aeaacb27c082
Yunji Kim
647015269ba7aeaacb27c083
Junho Kim
647015269ba7aeaacb27c084
Sungroh Yoon
claimed_verified
2024-05-02T07:18:30.976Z
64c99967d33e6a7f82c35f0b
/avatars/70e77eb570d12e11c2807e10cd4d926d.svg
Sungroh Yoon
user
sryoon
Custom-Edit: Text-Guided Image Editing with Customized Diffusion Models
Text-to-image diffusion models can generate diverse, high-fidelity images
based on user-provided text prompts. Recent research has extended these models
to support text-guided image editing. While text guidance is an intuitive
editing interface for users, it often fails to ensure the precise concept
conveyed by users. To address this issue, we propose Custom-Edit, in which we
(i) customize a diffusion model with a few reference images and then (ii)
perform text-guided editing. Our key discovery is that customizing only
language-relevant parameters with augmented prompts improves reference
similarity significantly while maintaining source similarity. Moreover, we
provide our recipe for each customization and editing process. We compare
popular customization methods and validate our findings on two editing methods
using various datasets.
Custom-Edit enhances text-guided image editing by fine-tuning only language-relevant diffusion model parameters to improve reference similarity while preserving source similarity.
diffusion models text-to-image text-guided image editing Custom-Edit language-relevant parameters reference similarity source similarity