Style-Editor: Text-driven object-centric style editing
This work addresses the challenge of precise, object-level style manipulation for image editing applications, representing an incremental improvement over existing methods.
The paper tackles the problem of text-driven object-centric style editing in images by introducing Style-Editor, which uses a novel Patch-wise Co-Directional loss and modules for text-based object identification, achieving visually coherent and textually aligned edits without requiring segmentation masks.
We present Text-driven object-centric style editing model named Style-Editor, a novel method that guides style editing at an object-centric level using textual inputs. The core of Style-Editor is our Patch-wise Co-Directional (PCD) loss, meticulously designed for precise object-centric editing that are closely aligned with the input text. This loss combines a patch directional loss for text-guided style direction and a patch distribution consistency loss for even CLIP embedding distribution across object regions. It ensures a seamless and harmonious style editing across object regions. Key to our method are the Text-Matched Patch Selection (TMPS) and Pre-fixed Region Selection (PRS) modules for identifying object locations via text, eliminating the need for segmentation masks. Lastly, we introduce an Adaptive Background Preservation (ABP) loss to maintain the original style and structural essence of the image's background. This loss is applied to dynamically identified background areas. Extensive experiments underline the effectiveness of our approach in creating visually coherent and textually aligned style editing.