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Diffusion models break down the challenging task of generating data from high-dimensional distributions into a series of easier denoising steps.
Bbdm: Image-to-image translation with brownian bridge diffusion models
Bo Li, Kaitao Xue, Bin Liu, and Yu-Kun Lai · 1961
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On the purpose of low-level vision
David Marr · 1974
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A computational approach to edge detection
John Canny · 1986
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Laplacian operator-based edge detectors
Xin Wang · 2007
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Vision: A computational investigation into the human representation and processing of visual information
David Marr · 2010
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2010
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2011
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The vision of david marr
Kent A Stevens · 2012
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Fast edge detection using structured forests
Piotr Dollár and C Lawrence Zitnick · 2014
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop
Fisher Yu, Ari Seff, Yinda Zhang, Shuran Song, Thomas Funkhouser, and Jianxiong Xiao · 2015
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Improved regularization of convolutional neural networks with cutout
Terrance DeVries and Graham W Taylor · 2017
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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2017
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Finegan: Unsupervised hierarchical disentanglement for fine-grained object generation and discovery
Krishna Kumar Singh, Utkarsh Ojha, and Yong Jae Lee · 2019
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Songwei Ge, Vedanuj Goswami, C Lawrence Zitnick, and Devi Parikh · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Variational diffusion models
Diederik Kingma, Tim Salimans, Ben Poole, and Jonathan Ho · 2021
Cited alongside, same era.
Partgan: Weakly-supervised part decomposition for image generation and segmentation
Yuheng Li, Krishna Kumar Singh, Yang Xue, and Yong Jae Lee · 2021
Cited alongside, same era.
Sdedit: Guided image synthesis and editing with stochastic differential equations
Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon · 2021
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Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
Cited alongside, same era.
Pixel difference networks for efficient edge detection
Zhuo Su, Wenzhe Liu, Zitong Yu, Dewen Hu, Qing Liao, Qi Tian, Matti Pietikäinen, and Li Liu · 2021
Cited alongside, same era.
Deep generative learning via schrödinger bridge
Renderdiffusion: Image diffusion for 3d reconstruction, inpainting and generation
Titas Anciukevičius, Zexiang Xu, Matthew Fisher, Paul Henderson, Hakan Bilen, Niloy J Mitra, and Paul Guerrero · 2023
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Extracting training data from diffusion models
Nicolas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramer, Borja Balle, Daphne Ippolito, and Eric Wallace · 2023
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Implicit diffusion models for continuous super-resolution
Sicheng Gao, Xuhui Liu, Bohan Zeng, Sheng Xu, Yanjing Li, Xiaoyan Luo, Jianzhuang Liu, Xiantong Zhen, and Baochang Zhang · 2023
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Pet image denoising based on denoising diffusion probabilistic model
Kuang Gong, Keith Johnson, Georges El Fakhri, Quanzheng Li, and Tinsu Pan · 2023
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Efficient diffusion training via min-snr weighting strategy
Tiankai Hang, Shuyang Gu, Chen Li, Jianmin Bao, Dong Chen, Han Hu, Xin Geng, and Baining Guo · 2023
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Gefei Wang, Yuling Jiao, Qian Xu, Yang Wang, and Can Yang · 2021
Cited alongside, same era.
Learning sparse masks for diffusion-based image inpainting
Tobias Alt, Pascal Peter, and Joachim Weickert · 2022
Cited alongside, same era.
Mr image denoising and super-resolution using regularized reverse diffusion
Hyungjin Chung, Eun Sun Lee, and Jong Chul Ye · 2022
Cited alongside, same era.
Cascaded diffusion models for high fidelity image generation
Jonathan Ho, Chitwan Saharia, William Chan, David J Fleet, Mohammad Norouzi, and Tim Salimans · 2022
Cited alongside, same era.
Diffusion models for medical image analysis: A comprehensive survey
Amirhossein Kazerouni, Ehsan Khodapanah Aghdam, Moein Heidari, Reza Azad, Mohsen Fayyaz, Ilker Hacihaliloglu, and Dorit Merhof · 2022
Cited alongside, same era.
Srdiff: Single image super-resolution with diffusion probabilistic models
Haoying Li, Yifan Yang, Meng Chang, Shiqi Chen, Huajun Feng, Zhihai Xu, Qi Li, and Yueting Chen · 2022
Cited alongside, same era.
Repaint: Inpainting using denoising diffusion probabilistic models
Andreas Lugmayr, Martin Danelljan, Andres Romero, Fisher Yu, Radu Timofte, and Luc Van Gool · 2022
Cited alongside, same era.
Lianghua Huang, Di Chen, Yu Liu, Yujun Shen, Deli Zhao, and Jingren Zhou · 2023
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Sinddm: A single image denoising diffusion model
Vladimir Kulikov, Shahar Yadin, Matan Kleiner, and Tomer Michaeli · 2023
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Zero-shot image-to-image translation
Gaurav Parmar, Krishna Kumar Singh, Richard Zhang, Yijun Li, Jingwan Lu, and Jun-Yan Zhu · 2023
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Magic123: One image to high-quality 3d object generation using both 2d and 3d diffusion priors
Guocheng Qian, Jinjie Mai, Abdullah Hamdi, Jian Ren, Aliaksandr Siarohin, Bing Li, Hsin-Ying Lee, Ivan Skorokhodov, Peter Wonka, Sergey Tulyakov, et al · 2023
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Plug-and-play diffusion features for text-driven image-to-image translation
Narek Tumanyan, Michal Geyer, Shai Bagon, and Tali Dekel · 2023
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The big data myth: Using diffusion models for dataset generation to train deep detection models
Roy Voetman, Maya Aghaei, and Klaas Dijkstra · 2023
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Adding conditional control to text-to-image diffusion models
Lvmin Zhang, Anyi Rao, and Maneesh Agrawala · 2023
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Fast segment anything, 2023
Xu Zhao, Wenchao Ding, Yongqi An, Yinglong Du, Tao Yu, Min Li, Ming Tang, and Jinqiao Wang · 2023
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Denoising diffusion models for plug-and-play image restoration
Yuanzhi Zhu, Kai Zhang, Jingyun Liang, Jiezhang Cao, Bihan Wen, Radu Timofte, and Luc Van Gool · 2023
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Seed-x: Multimodal models with unified multi-granularity comprehension and generation
Yuying Ge, Sijie Zhao, Jinguo Zhu, Yixiao Ge, Kun Yi, Lin Song, Chen Li, Xiaohan Ding, and Ying Shan · 2024
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An edit friendly ddpm noise space: Inversion and manipulations
Inbar Huberman-Spiegelglas, Vladimir Kulikov, and Tomer Michaeli · 2024
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T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models
Chong Mou, Xintao Wang, Liangbin Xie, Yanze Wu, Jian Zhang, Zhongang Qi, and Ying Shan · 2024
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Uni-controlnet: All-in-one control to text-to-image diffusion models
Shihao Zhao, Dongdong Chen, Yen-Chun Chen, Jianmin Bao, Shaozhe Hao, Lu Yuan, and Kwan-Yee K Wong · 2024
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