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Diffusion models (DMs) produce very detailed and high-quality images.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C. Bovik, Hamid R. Sheikh, and Eero P. Simoncelli · 2004
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Advanced Engineering Mathematics
Erwin Kreyszig, Herbert Kreyszig, and E. J. Norminton · 2011
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge J. Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C. Lawrence Zitnick · 2014
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Model inversion attacks that exploit confidence information and basic countermeasures
Matt Fredrikson, Somesh Jha, and Thomas Ristenpart · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Understanding deep learning requires rethinking generalization
Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, and Oriol Vinyals · 2016
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A closer look at memorization in deep networks
Devansh Arpit, Stanisław Jastrzebski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S Kanwal, Tegan Maharaj, Asja Fischer, Aaron Courville, Yoshua Bengio, et al · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Demystifying MMD gans
Mikolaj Binkowski, Danica J. Sutherland, Michael Arbel, and Arthur Gretton · 2018
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Learning and memorization
Satrajit Chatterjee · 2018
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The secret sharer: Evaluating and testing unintended memorization in neural networks
Nicholas Carlini, Chang Liu, Úlfar Erlingsson, Jernej Kos, and Dawn Song · 2019
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PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Does learning require memorization? a short tale about a long tail
Vitaly Feldman · 2020
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What neural networks memorize and why: Discovering the long tail via influence estimation
Vitaly Feldman and Chiyuan Zhang · 2020
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Denoising Diffusion Probabilistic Models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Improved Techniques for Training Score-Based Generative Models
Yang Song and Stefano Ermon · 2020
Cited alongside, same era.
On the geometry of generalization and memorization in deep neural networks
Cory Stephenson, Abhinav Ganesh, Yue Hui, Hanlin Tang, SueYeon Chung, et al · 2020
Cited alongside, same era.
Deep learning through the lens of example difficulty
Robert Baldock, Hartmut Maennel, and Behnam Neyshabur · 2021
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Extracting training data from large language models
Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, et al · 2021
Cited alongside, same era.
Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
Cited alongside, same era.
The role of imagenet classes in fréchet inception distance
Tuomas Kynkäänniemi, Tero Karras, Miika Aittala, Timo Aila, and Jaakko Lehtinen · 2023
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Cones: Concept Neurons in Diffusion Models for Customized Generation
Zhiheng Liu, Ruili Feng, Kai Zhu, Yifei Zhang, Kecheng Zheng, Yu Liu, Deli Zhao, Jingren Zhou, and Yang Cao · 2023
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Can neural network memorization be localized?
Pratyush Maini, Michael Curtis Mozer, Hanie Sedghi, Zachary Chase Lipton, J Zico Kolter, and Chiyuan Zhang · 2023
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Understanding and mitigating copying in diffusion models
Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, and Tom Goldstein · 2023
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DeepFloyd IF: a novel state-of-the-art open-source text-to-image model with a high degree of photorealism and language understanding
StabilityAI · 2023
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Gaurav Parmar, Richard Zhang, and Jun-Yan Zhu · 2022
Cited alongside, same era.
A self-supervised descriptor for image copy detection
Ed Pizzi, Sreya Dutta Roy, Sugosh Nagavara Ravindra, Priya Goyal, and Matthijs Douze · 2022
Cited alongside, same era.
Hierarchical text-conditional image generation with CLIP latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L. Denton, Seyed Kamyar Seyed Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J. Fleet, and Mohammad Norouzi · 2022
Cited alongside, same era.
LAION-5B: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, and Jenia Jitsev · 2022
Cited alongside, same era.
Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks
Lukas Struppek, Dominik Hintersdorf, Antonio De Almeida Correia, Antonia Adler, and Kristian Kersting · 2022
Cited alongside, same era.
Dynamic prompt learning: Addressing cross-attention leakage for text-based image editing
Kai Wang, Fei Yang, Shiqi Yang, Muhammad Atif Butt, and Joost van de Weijer · 2023
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A reproducible extraction of training images from diffusion models
Ryan Webster · 2023
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Diffusion Probabilistic Models Generalize when They Fail to Memorize
TaeHo Yoon, Joo Young Choi, Sehyun Kwon, and Ernest K. Ryu · 2023
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Training-free layout control with cross-attention guidance
Minghao Chen, Iro Laina, and Andrea Vedaldi · 2024
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Unified concept editing in diffusion models
Rohit Gandikota, Hadas Orgad, Yonatan Belinkov, Joanna Materzynska, and David Bau · 2024
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Do ssl models have déjà vu? a case of unintended memorization in self-supervised learning
Casey Meehan, Florian Bordes, Pascal Vincent, Kamalika Chaudhuri, and Chuan Guo · 2024
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Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention
Jie Ren, Yaxin Li, Shenglai Zeng, Han Xu, Lingjuan Lyu, Yue Xing, and Jiliang Tang · 2024
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Memorization in Self-Supervised Learning Improves Downstream Generalization
Wenhao Wang, Muhammad Ahmad Kaleem, Adam Dziedzic, Michael Backes, Nicolas Papernot, and Franziska Boenisch · 2024
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Detecting, Explaining, and Mitigating Memorization in Diffusion Models
Yuxin Wen, Yuchen Liu, Chen Chen, and Lingjuan Lyu · 2024
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Intriguing properties of data attribution on diffusion models
Xiaosen Zheng, Tianyu Pang, Chao Du, Jing Jiang, and Min Lin · 2024
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