A Closed-form Solution to Photorealistic Image Stylization
Yijun Li, Ming-Yu Liu, Xueting Li, Ming-Hsuan Yang, Jan Kautz
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ReproduceCode
- github.com/NVIDIA/FastPhotoStyleOfficialIn paperpytorch★ 0
- github.com/svjack/PhotoWCTtf★ 0
- github.com/smaranjitghose/DeepHolinone★ 0
- github.com/sleebapaul/AuriaKathipytorch★ 0
- github.com/deepdeepdot/FastPhotoStylepytorch★ 0
- github.com/clovaai/WCT2pytorch★ 0
- github.com/midm/FastPhotoStylepytorch★ 0
- github.com/freedombenLiu/FastPhotoStylepytorch★ 0
- github.com/Lees001/FastPhotoStylepytorch★ 0
- github.com/MohdDanish/FastPhotoStyle1pytorch★ 0
Abstract
Photorealistic image stylization concerns transferring style of a reference photo to a content photo with the constraint that the stylized photo should remain photorealistic. While several photorealistic image stylization methods exist, they tend to generate spatially inconsistent stylizations with noticeable artifacts. In this paper, we propose a method to address these issues. The proposed method consists of a stylization step and a smoothing step. While the stylization step transfers the style of the reference photo to the content photo, the smoothing step ensures spatially consistent stylizations. Each of the steps has a closed-form solution and can be computed efficiently. We conduct extensive experimental validations. The results show that the proposed method generates photorealistic stylization outputs that are more preferred by human subjects as compared to those by the competing methods while running much faster. Source code and additional results are available at https://github.com/NVIDIA/FastPhotoStyle .