OmniStyle: Filtering High Quality Style Transfer Data at Scale
Ye Wang, Ruiqi Liu, Jiang Lin, Fei Liu, Zili Yi, Yilin Wang, Rui Ma
摘要
Illustration Examples Content (a) Instruction-Guided Style Transfer Make this image into XXX Style Travis Foster iPad white-carve Rococo-style oil painting magic color illustration natural wood style flat design Chinese ancient art sketch Style Content (b) Image-Guided Style Transfer Figure 1. OmniStyle enables high-quality (a) instruction-guided style transfer and (b) reference image-guided style transfer, covering a diverse range of styles, including but not limited to comics, vector art, oil painting, sketch, and Chinese ancient art. Note that in (a), a style image of the style descriptions is provided for illustration, and our method only takes a text instruction and a content image as input. In (b), results are generated in a traditional manner of style transfer, in which the model takes both the content and style images as input.
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引用它的顶会 Paper11
- FFP-300K: Scaling First-Frame Propagation for Generalizable Video EditingXijie Huang, Chengming Xu, Donghao Luo, Xiaobin Hu 等CVPR 2026 · 被引用 5 次
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- Premier: Personalized Preference Modulation with Learnable User Embedding in Text-to-Image GenerationZihao Wang, Yuxiang Wei, Xinpeng Zhou, Tianyu Zhang 等CVPR 2026 · 被引用 1 次
- Mixture of Style Experts for Diverse Image StylizationShihao Zhu, Ziheng Ouyang, Yijia Kang, Qilong Wang 等CVPR 2026 · 被引用 1 次
它引用的顶会 Paper20
- Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh 等ICML 2021 · 被引用 47,906 次
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- Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain GeneralizationYabin Zhang, Minghan Li, Ruihuang Li, Kui Jia 等CVPR 2022 · 被引用 217 次
- Domain Enhanced Arbitrary Image Style Transfer via Contrastive LearningYuxin Zhang, Fan Tang, Weiming Dong, Haibin Huang 等SIGGRAPH 2022 · 被引用 211 次
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