Strictly-ID-Preserved and Controllable Accessory Advertising Image Generation
Youze Xue, Binghui Chen, Yifeng Geng, Xuansong Xie, Jiansheng Chen,, and Hongbing Ma

TL;DR
This paper introduces a novel image generation pipeline that ensures strict identity preservation of accessories in advertising images, enabling precise control over model attributes for e-commerce applications.
Contribution
The paper presents a Control-Net based pipeline and a multi-branch cross-attention architecture for controllable, identity-preserving accessory image generation in advertising.
Findings
Achieves strict accessory identity preservation in generated images.
Enables control over scale, pose, and appearance of models.
Produces diverse, high-quality advertising images.
Abstract
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…
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Taxonomy
TopicsVideo Analysis and Summarization · Advanced Steganography and Watermarking Techniques · Digital Media and Visual Art
