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照片交換:圖像中的個性化主題交換

Photoswap: Personalized Subject Swapping in Images

May 29, 2023
作者: Jing Gu, Yilin Wang, Nanxuan Zhao, Tsu-Jui Fu, Wei Xiong, Qing Liu, Zhifei Zhang, He Zhang, Jianming Zhang, HyunJoon Jung, Xin Eric Wang
cs.AI

摘要

在一個以圖像和視覺內容主導數位景觀的時代,操控和個性化這些圖像的能力已成為必需。想像著在一張照片中無縫地將一隻悠閒躺在陽光照耀的窗台上的虎斑貓替換為你自己的俏皮小狗,同時保留圖像的原始魅力和構圖。我們提出了Photoswap,一種新穎的方法,通過在現有圖像中進行個性化主題替換,實現這種身臨其境的圖像編輯體驗。Photoswap首先從參考圖像中學習主題的視覺概念,然後使用預先訓練的擴散模型以無需訓練的方式將其交換到目標圖像中。我們確立了一個經過良好構思的視覺主題可以通過適當的自我關注和交叉關注操作,無縫地轉移到任何圖像中,保持替換主題的姿勢和圖像的整體一致性。全面的實驗強調了Photoswap在個性化主題替換中的有效性和可控性。此外,Photoswap在人類評分中在主題替換、背景保留和整體質量方面明顯優於基準方法,揭示了其廣泛的應用潛力,從娛樂到專業編輯。
English
In an era where images and visual content dominate our digital landscape, the ability to manipulate and personalize these images has become a necessity. Envision seamlessly substituting a tabby cat lounging on a sunlit window sill in a photograph with your own playful puppy, all while preserving the original charm and composition of the image. We present Photoswap, a novel approach that enables this immersive image editing experience through personalized subject swapping in existing images. Photoswap first learns the visual concept of the subject from reference images and then swaps it into the target image using pre-trained diffusion models in a training-free manner. We establish that a well-conceptualized visual subject can be seamlessly transferred to any image with appropriate self-attention and cross-attention manipulation, maintaining the pose of the swapped subject and the overall coherence of the image. Comprehensive experiments underscore the efficacy and controllability of Photoswap in personalized subject swapping. Furthermore, Photoswap significantly outperforms baseline methods in human ratings across subject swapping, background preservation, and overall quality, revealing its vast application potential, from entertainment to professional editing.
PDF30December 15, 2024