Strictly-ID-Preserved and Controllable Accessory Advertising Image Generation
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arXiv
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| Format: | Preprint |
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2024
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| author | Xue, Youze Chen, Binghui Geng, Yifeng Xie, Xuansong Chen, Jiansheng Ma, Hongbing |
| author_facet | Xue, Youze Chen, Binghui Geng, Yifeng Xie, Xuansong Chen, Jiansheng Ma, Hongbing |
| contents | Customized generative text-to-image models have the ability to produce images that closely resemble a given subject. However, in the context of generating advertising images for e-commerce scenarios, it is crucial that the generated subject's identity aligns perfectly with the product being advertised. In order to address the need for strictly-ID preserved advertising image generation, we have developed a Control-Net based customized image generation pipeline and have taken earring model advertising as an example. Our approach facilitates a seamless interaction between the earrings and the model's face, while ensuring that the identity of the earrings remains intact. Furthermore, to achieve a diverse and controllable display, we have proposed a multi-branch cross-attention architecture, which allows for control over the scale, pose, and appearance of the model, going beyond the limitations of text prompts. Our method manages to achieve fine-grained control of the generated model's face, resulting in controllable and captivating advertising effects. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_04828 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Strictly-ID-Preserved and Controllable Accessory Advertising Image Generation Xue, Youze Chen, Binghui Geng, Yifeng Xie, Xuansong Chen, Jiansheng Ma, Hongbing Computer Vision and Pattern Recognition Customized generative text-to-image models have the ability to produce images that closely resemble a given subject. However, in the context of generating advertising images for e-commerce scenarios, it is crucial that the generated subject's identity aligns perfectly with the product being advertised. In order to address the need for strictly-ID preserved advertising image generation, we have developed a Control-Net based customized image generation pipeline and have taken earring model advertising as an example. Our approach facilitates a seamless interaction between the earrings and the model's face, while ensuring that the identity of the earrings remains intact. Furthermore, to achieve a diverse and controllable display, we have proposed a multi-branch cross-attention architecture, which allows for control over the scale, pose, and appearance of the model, going beyond the limitations of text prompts. Our method manages to achieve fine-grained control of the generated model's face, resulting in controllable and captivating advertising effects. |
| title | Strictly-ID-Preserved and Controllable Accessory Advertising Image Generation |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2404.04828 |