Alias-Free Latent Diffusion Models: Improving Fractional Shift Equivariance of Diffusion Latent Space
Yifan Zhou, Zeqi Xiao, Shuai Yang, Xingang Pan
Abstract
Abstract Latent Diffusion Models (LDMs) are known to have an unstable generation process, where even small perturbations or shifts in the input noise can lead to significantly different outputs. This hinders their applicability in applications requiring consistent results.
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Cited by top-tier papers8
- Latent Harmony: Synergistic Unified UHD Image Restoration via Latent Space Regularization and Controllable RefinementYidi Liu, Xueyang Fu, Jie Huang, Jie Xiao et al.NeurIPS 2025 · 3 citations
- Alias-Free ViT: Fractional Shift Invariance via Linear AttentionHagay Michaeli, Daniel SoudryNeurIPS 2025 · 2 citations
- Steering Where to Diffuse: Generative Modeling of Phenotypic Response Simulation with Steered Diffusion BridgeRongchao Zhang, Chengxin Li, Yiwei Lou, Yuling Shi et al.CVPR 2026 · 1 citation
- Optimal Stopping in Latent Diffusion ModelsYu-Han Wu, Quentin Berthet, Gérard Biau, Claire Boyer et al.ICML 2026 · 1 citation
- Improving the Diffusability of AutoencodersIvan Skorokhodov, Sharath Girish, Benran Hu, Willi Menapace et al.ICML 2025
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- Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh et al.ICML 2021 · 47,906 citations
- Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter AbbeelNeurIPS 2020 · 35,902 citations
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser et al.CVPR 2022 · 13,123 citations
- Denoising Diffusion Implicit ModelsJiaming Song, Chenlin Meng, Stefano ErmonICLR 2021 · 11,743 citations
- Adding Conditional Control to Text-to-Image Diffusion ModelsLvmin Zhang, Anyi Rao, Maneesh AgrawalaICCV 2023 · 6,759 citations
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