DEADiff Diffusion for Stylized Generation — Poster
A conference poster presenting DEADiff, a diffusion model for stylized image generation. It details a dual decoupling representation extraction mechanism, compares results against T2I-Adapter and IP-Adapter, and demonstrates style mixing and object generation capabilities through various visual examples.
논문 컨텍스트
Paper title: DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations Abstract: A conference poster presenting DEADiff, a diffusion model for stylized image generation. It details a dual decoupling representation extraction mechanism, compares results against T2I-Adapter and IP-Adapter, and demonstrates style mixing and object generation capabilities through various visual examples. Paper body (method & results): <!DOCTYPE html> <html lang="en"> <head> <meta content="text/html; charset=utf-8" http-equiv="content-type"/> <title>DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations</title> <!--Generated on Mon Mar 11 17:31:59 2024 by LaTeXML (version 0.8.7) http://dlmf.nist.gov/LaTeXML/.--> <meta content="width=device-width, initial-scale=1, shrink-to-fit=no" name="viewport"/> <link href="https://cdn.jsdelivr.net/npm/bootstrap@5.3.0/dist/css/bootstrap.min.css" rel="stylesheet" type="text/css"/> <link href="/static/browse/0.3.4/css/ar5iv_0.7.4.min.css" rel="stylesheet" type="text/css"/> <link href="/static/browse/0.3.4/css/latexml_styles.css" rel="stylesheet" type="text/css"/> <script src="https://cdn.jsdelivr.net/npm/bootstrap@5.3.0/dist/js/bootstrap.bundle.min.js"></script> <script src="https://cdnjs.cloudflare.com/ajax/libs/html2canvas/1.3.3/html2canvas.min.js"></script> <script src="/static/browse/0.3.4/js/addons.js"></script> <script src="/static/browse/0.3.4/js/feedbackOverlay.js"></script> <base href="/html/2403.06951v1/"/></head> <body> <nav class="ltx_page_navbar"> <nav class="ltx_TOC"> <ol class="ltx_toclist"> <li class="ltx_tocentry ltx_tocentry_section"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S1" title="1 Introduction ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">1 </span>Introduction</span></a></li> <li class="ltx_tocentry ltx_tocentry_section"> <a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S2" title="2 Related Work ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">2 </span>Related Work</span></a> <ol class="ltx_toclist ltx_toclist_section"> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S2.SS1" title="2.1 Diffusion-based Text-to-Image Generation ‣ 2 Related Work ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">2.1 </span>Diffusion-based Text-to-Image Generation</span></a></li> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S2.SS2" title="2.2 Stylized Image Generation with T2I Models ‣ 2 Related Work ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">2.2 </span>Stylized Image Generation with T2I Models</span></a></li> </ol> </li> <li class="ltx_tocentry ltx_tocentry_section"> <a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S3" title="3 Method ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">3 </span>Method</span></a> <ol class="ltx_toclist ltx_toclist_section"> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S3.SS1" title="3.1 Preliminary ‣ 3 Method ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">3.1 </span>Preliminary</span></a></li> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S3.SS2" title="3.2 Dual Decoupling Representation Extraction ‣ 3 Method ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">3.2 </span>Dual Decoupling Representation Extraction</span></a></li> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S3.SS3" title="3.3 Disentangled Conditioning Mechanism ‣ 3 Method ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">3.3 </span>Disentangled Conditioning Mechanism</span></a></li> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S3.SS4" title="3.4 Paired Datasets Construction ‣ 3 Method ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">3.4 </span>Paired Datasets Construction</span></a></li> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S3.SS5" title="3.5 Training and Inference. ‣ 3 Method ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">3.5 </span>Training and Inference.</span></a></li> </ol> </li> <li class="ltx_tocentry ltx_tocentry_section"> <a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S4" title="4 Experiment ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">4 </span>Experiment</span></a> <ol class="ltx_toclist ltx_toclist_section"> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S4.SS1" title="4.1 Experiment Settings ‣ 4 Experiment ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">4.1 </span>Experiment Settings</span></a></li> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S4.SS2" title="4.2 Comparison with State-of-the-Arts ‣ 4 Experiment ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">4.2 </span>Comparison with State-of-the-Arts</span></a></li> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S4.SS3" title="4.3 Ablation Study ‣ 4 Experiment ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">4.3 </span>Ablation Study</span></a></li> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S4.SS4" title="4.4 Applications ‣ 4 Experiment ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">4.4 </span>Applications</span></a></li> </ol> </li> <li class="ltx_tocentry ltx_tocentry_section"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S5" title="5 Conclusion ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">5 </span>Conclusion</span></a></li> <li class="ltx_tocentry ltx_tocentry_section"> <a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S6" title="6 Supplementary ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">6 </span>Supplementary</span></a> <ol class="ltx_toclist ltx_toclist_section"> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S6.SS1" title="6.1 Quantitative Comparisons ‣ 6 Supplementary ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">6.1 </span>Quantitative Comparisons</span></a></li> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S6.SS2" title="6.2 User Study ‣ 6 Supplementary ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">6.2 </span>User Study</span></a></li> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S6.SS3" title="6.3 Inference Efficiency ‣ 6 Supplementary ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">6.3 </span>Inference Efficiency</span></a></li> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S6.SS4" title="6.4 Comparison with ControlNet 1.1 Shuffle ‣ 6 Supplementary ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">6.4 </span>Comparison with ControlNet 1.1 Shuffle</span></a></li> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S6.SS5" title="6.5 Combination with DreamBooth/LoRA ‣ 6 Supplementary ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">6.5 </span>Combination with DreamBooth/LoRA</span></a></li> <li class="ltx_tocentry ltx_tocentry_subsection"><a class="ltx_ref" href="https://arxiv.org/html/2403.06951v1#S6.SS6" title="6.6 More Examples ‣ 6 Supplementary ‣ DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations"><span class="ltx_text ltx_ref_title"><span class="ltx_tag ltx_tag_ref">6.6 </span>More Examples</span></a></li> </ol> </li> 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