Summary of Regional Style and Color Transfer, by Zhicheng Ding et al.
Regional Style and Color Transfer
by Zhicheng Ding, Panfeng Li, Qikai Yang, Siyang Li, Qingtian Gong
First submitted to arxiv on: 22 Apr 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed method for regional style transfer addresses the limitation of existing approaches by using a segmentation network to isolate foreground objects within an input image, applying style transfer exclusively to the background region, and reintegrating the isolated foreground objects into the style-transferred background. To enhance visual coherence, a color transfer step is employed on the foreground elements prior to their reintegration. The final composition is achieved through feathering techniques, resulting in visually unified and aesthetically pleasing results. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper presents a new approach to regional style transfer that allows for more natural and realistic transformations of images. It uses a segmentation network to isolate objects within an image and then applies the desired style only to the background. The foreground objects are then reintegrated into the transformed background, resulting in a final composition that is visually consistent and pleasing. |
Keywords
» Artificial intelligence » Style transfer
