多服装定制模特生成
Multi-Garment Customized Model Generation
AI总结：
本文提出基于潜在扩散模型的统一框架，通过并行服装编码器和解耦多服装特征融合，实现多件服装自由组合的定制模特生成，并可即插即用地结合 IP-Adapter 与 ControlNet。
摘要：
本文介绍了 Multi-Garment Customized Model Generation（多服装定制模特生成），这是一个基于 Latent Diffusion Models（LDM，潜在扩散模型）的统一框架，旨在解决尚未被探索的任务：合成自由组合多件服装的图像。该方法专注于根据不同文本提示生成穿着各种目标服装的定制模特。主要挑战在于，在保持着装模特自然外观的同时，保留每件服装的复杂纹理，并确保不同服装的信息不会相互干扰。为应对这些挑战，我们首先开发了一个服装编码器，它是一个共享权重的可训练 UNet 副本，能够并行提取服装的详细特征。其次，我们的框架通过解耦的多服装特征融合支持多服装条件生成，使多个服装特征能够注入主干网络，显著缓解服装信息之间的冲突。此外，所提出的服装编码器是一个即插即用模块，可以与 IP-Adapter 和 ControlNet 等其他扩展模块结合，增强生成模特的多样性和可控性。大量实验证明，我们的方法优于现有替代方案，为多件服装组合图像生成任务开辟了新途径。
英文摘要：
This paper introduces Multi-Garment Customized Model Generation, a unified framework based on Latent Diffusion Models (LDMs) aimed at addressing the unexplored task of synthesizing images with free combinations of multiple pieces of clothing. The method focuses on generating customized models wearing various targeted outfits according to different text prompts. The primary challenge lies in maintaining the natural appearance of the dressed model while preserving the complex textures of each piece of clothing, ensuring that the information from different garments does not interfere with each other. To tackle these challenges, we first developed a garment encoder, which is a trainable UNet copy with shared weights, capable of extracting detailed features of garments in parallel. Secondly, our framework supports the conditional generation of multiple garments through decoupled multi-garment feature fusion, allowing multiple clothing features to be injected into the backbone network, significantly alleviating conflicts between garment information. Additionally, the proposed garment encoder is a plug-and-play module that can be combined with other extension modules such as IP-Adapter and ControlNet, enhancing the diversity and controllability of the generated models. Extensive experiments demonstrate the superiority of our approach over existing alternatives, opening up new avenues for the task of generating images with multiple-piece clothing combinations
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
