Drag your noise: Interactive point-based editing via diffusion semantic propagation
Point-based interactive editing serves as an essential tool to complement the controllability of existing generative models. A concurrent work, DragDiffusion, updates the diffusion latent map in response to user inputs, causing global latent map alterations. This results in imprecise preservation of...
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sg-smu-ink.sis_research-107732024-12-16T02:28:41Z Drag your noise: Interactive point-based editing via diffusion semantic propagation LIU, Haofeng XU, Chenshu YANG, Yifei ZENG, Lihua HE, Shengfeng Point-based interactive editing serves as an essential tool to complement the controllability of existing generative models. A concurrent work, DragDiffusion, updates the diffusion latent map in response to user inputs, causing global latent map alterations. This results in imprecise preservation of the original content and unsuccessful editing due to gradient vanishing. In contrast, we present DragNoise, offering robust and accelerated editing without retracing the latent map. The core rationale of DragNoise lies in utilizing the predicted noise output of each U-Net as a semantic editor. This approach is grounded in two critical observations: firstly, the bottleneck features of U-Net inherently possess semantically rich features ideal for interactive editing; secondly, highlevel semantics, established early in the denoising process, show minimal variation in subsequent stages. Leveraging these insights, DragNoise edits diffusion semantics in a single denoising step and efficiently propagates these changes, ensuring stability and efficiency in diffusion editing. Comparative experiments reveal that DragNoise achieves superior control and semantic retention, reducing the optimization time by over 50% compared to DragDiffusion. 2024-06-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/9773 https://ink.library.smu.edu.sg/context/sis_research/article/10773/viewcontent/2404.01050v1.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Point-based interactive editing Diffusion latent map alterations Semantic editor Artificial Intelligence and Robotics Graphics and Human Computer Interfaces |
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Point-based interactive editing Diffusion latent map alterations Semantic editor Artificial Intelligence and Robotics Graphics and Human Computer Interfaces LIU, Haofeng XU, Chenshu YANG, Yifei ZENG, Lihua HE, Shengfeng Drag your noise: Interactive point-based editing via diffusion semantic propagation |
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Point-based interactive editing serves as an essential tool to complement the controllability of existing generative models. A concurrent work, DragDiffusion, updates the diffusion latent map in response to user inputs, causing global latent map alterations. This results in imprecise preservation of the original content and unsuccessful editing due to gradient vanishing. In contrast, we present DragNoise, offering robust and accelerated editing without retracing the latent map. The core rationale of DragNoise lies in utilizing the predicted noise output of each U-Net as a semantic editor. This approach is grounded in two critical observations: firstly, the bottleneck features of U-Net inherently possess semantically rich features ideal for interactive editing; secondly, highlevel semantics, established early in the denoising process, show minimal variation in subsequent stages. Leveraging these insights, DragNoise edits diffusion semantics in a single denoising step and efficiently propagates these changes, ensuring stability and efficiency in diffusion editing. Comparative experiments reveal that DragNoise achieves superior control and semantic retention, reducing the optimization time by over 50% compared to DragDiffusion. |
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text |
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LIU, Haofeng XU, Chenshu YANG, Yifei ZENG, Lihua HE, Shengfeng |
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LIU, Haofeng XU, Chenshu YANG, Yifei ZENG, Lihua HE, Shengfeng |
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LIU, Haofeng |
title |
Drag your noise: Interactive point-based editing via diffusion semantic propagation |
title_short |
Drag your noise: Interactive point-based editing via diffusion semantic propagation |
title_full |
Drag your noise: Interactive point-based editing via diffusion semantic propagation |
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Drag your noise: Interactive point-based editing via diffusion semantic propagation |
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Drag your noise: Interactive point-based editing via diffusion semantic propagation |
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drag your noise: interactive point-based editing via diffusion semantic propagation |
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Institutional Knowledge at Singapore Management University |
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2024 |
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https://ink.library.smu.edu.sg/sis_research/9773 https://ink.library.smu.edu.sg/context/sis_research/article/10773/viewcontent/2404.01050v1.pdf |
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