CleanDIFT: Diffusion Features without Noise
Nick Stracke, Stefan Andreas Baumann, Kolja Bauer, Frank Fundel, Björn Ommer
2025Year
13Top-tier citations
Abstract
Figure 1. Our proposed CleanDIFT feature extraction method yields noise-free, timestep-independent, general-purpose features that significantly outperform standard diffusion features. CleanDIFT operates on clean images, while extracting diffusion features with existing approaches requires adding noise to an image before passing it through the model. Adding noise reduces the information present in the image and requires tuning a timestep per downstream task.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers13
- Emergent Temporal Correspondences from Video Diffusion TransformersJisu Nam, Soowon Son, Dahyun Chung, Jiyoung Kim et al.NeurIPS 2025 · 30 citations
- Attention (as Discrete-Time Markov) ChainsYotam Erel, Olaf Dünkel, Rishabh Dabral, Vladislav Golyanik et al.NeurIPS 2025 · 12 citations
- Inverse Virtual Try-On: Generating Multi-Category Product-Style Images from Clothed IndividualsDavide Lobba, Fulvio Sanguigni, Bin Ren, Marcella Cornia et al.ICLR 2026 · 7 citations
- Mind-the-Glitch: Visual Correspondence for Detecting Inconsistencies in Subject-Driven GenerationAbdelrahman Eldesokey, Aleksandar Cvejic, Bernard Ghanem, Peter WonkaNeurIPS 2025 · 6 citations
- LayerSync: Self-aligning Intermediate LayersYasaman Haghighi, Bastien van Delft, Mariam Hassan, Alexandre AlahiICLR 2026 · 6 citations
Builds on39
- 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
- LoRA: Low-Rank Adaptation of Large Language ModelsEdward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu et al.ICLR 2022 · 18,833 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
Related papers
- Emergent Correspondence from Image DiffusionLuming Tang, Menglin Jia, Qianqian Wang, Cheng Perng Phoo et al.NeurIPS 2023 · 555 citations
- Suppress Content Shift: Better Diffusion Features via Off-the-Shelf Generation TechniquesBenyuan Meng, Qianqian Xu, Zitai Wang, Zhiyong Yang et al.NeurIPS 2024 · 3 citations
- Beyond Generation: A Diffusion-based Low-level Feature Extractor for Detecting AI-generated ImagesNan Zhong, Haoyu Chen, Yiran Xu, Zhenxing Qian et al.CVPR 2025
- No Training, No Problem: Rethinking Classifier-Free Guidance for Diffusion ModelsSeyedmorteza Sadat, Manuel Kansy, Otmar Hilliges, Romann M. WeberICLR 2025
- Faster Diffusion: Rethinking the Role of the Encoder for Diffusion Model InferenceSenmao Li, Taihang Hu, Joost van de Weijer, Fahad Shahbaz Khan et al.NeurIPS 2024 · 50 citations
