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Text-to-image diffusion models have made significant advances in generating and editing high-quality images.
Data driven image models through continuous joint alignment
Erik G. Learned-Miller · 2005
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SIFT Flow: Dense correspondence across scenes and its applications
Ce Liu, Jenny Yuen, and Antonio Torralba · 2010
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Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
Nathan Halko, Per-Gunnar Martinsson, and Joel A. Tropp · 2011
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Semantic contours from inverse detectors
Bharath Hariharan, Pablo Arbeláez, Lubomir Bourdev, Subhransu Maji, and Jitendra Malik · 2011
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Articulated human detection with flexible mixtures of parts
Yi Yang and Deva Ramanan · 2012
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Unsupervised joint object discovery and segmentation in internet images
Michael Rubinstein, Armand Joulin, Johannes Kopf, and Ce Liu · 2013
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Jointly optimizing 3D model fitting and fine-grained classification
Yen-Liang Lin, Vlad I Morariu, Winston Hsu, and Larry S. Davis · 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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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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A benchmark dataset and evaluation methodology for video object segmentation
Federico Perazzi, Jordi Pont-Tuset, Brian McWilliams, Luc Van Gool, Markus Gross, and Alexander Sorkine-Hornung · 2016
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Joint recovery of dense correspondence and cosegmentation in two images
Tatsunori Taniai, Sudipta N Sinha, and Yoichi Sato · 2016
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LIFT: Learned invariant feature transform
Kwang Moo Yi, Eduard Trulls, Vincent Lepetit, and Pascal Fua · 2016
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Proposal Flow: Semantic correspondences from object proposals
Bumsub Ham, Minsu Cho, Cordelia Schmid, and Jean Ponce · 2017
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Convolutional neural network architecture for geometric matching
Ignacio Rocco, Relja Arandjelović, and Josef Sivic · 2017
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Neural best-buddies: Sparse cross-domain correspondence
Kfir Aberman, Jing Liao, Mingyi Shi, Dani Lischinski, Baoquan Chen, and Daniel Cohen-Or · 2018
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PARN: Pyramidal affine regression networks for dense semantic correspondence
Sangryul Jeon, Seungryong Kim, Dongbo Min, and Kwanghoon Sohn · 2018
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DifNet: Semantic segmentation by diffusion networks
Peng Jiang, Fanglin Gu, Yunhai Wang, Changhe Tu, and Baoquan Chen · 2018
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Recurrent transformer networks for semantic correspondence
Seungryong Kim, Stephen Lin, Sang Ryul Jeon, Dongbo Min, and Kwanghoon Sohn · 2018
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LF-Net: Learning local features from images
Yuki Ono, Eduard Trulls, Pascal Fua, and Kwang Moo Yi · 2018
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End-to-end weakly-supervised semantic alignment
Ignacio Rocco, Relja Arandjelović, and Josef Sivic · 2018
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Attentive semantic alignment with offset-aware correlation kernels
Paul Hongsuck Seo, Jongmin Lee, Deunsol Jung, Bohyung Han, and Minsu Cho · 2018
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D2-Net: A trainable CNN for joint description and detection of local features
Mihai Dusmanu, Ignacio Rocco, Tomas Pajdla, Marc Pollefeys, Josef Sivic, Akihiko Torii, and Torsten Sattler · 2019
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SPair-71k: A large-scale benchmark for semantic correspondence
Juhong Min, Jongmin Lee, Jean Ponce, and Minsu Cho · 2019
Cited alongside, same era.
R2D2: Reliable and repeatable detector and descriptor
Jerome Revaud, César De Souza, Martin Humenberger, and Philippe Weinzaepfel · 2019
Cited alongside, same era.
Unsupervised learning of visual features by contrasting cluster assignments
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Semantic correspondence as an optimal transport problem
Yanbin Liu, Linchao Zhu, Makoto Yamada, and Yi Yang · 2020
Cited alongside, same era.
SuperGlue: Learning feature matching with graph neural networks
GAN-supervised dense visual alignment
William Peebles, Jun-Yan Zhu, Richard Zhang, Antonio Torralba, Alexei A. Efros, and Eli Shechtman · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Semantic diffusion network for semantic segmentation
Haoru Tan, Sitong Wu, and Jimin Pi · 2022
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Probabilistic warp consistency for weakly-supervised semantic correspondences
Prune Truong, Martin Danelljan, Fisher Yu, and Luc Van Gool · 2022
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Paul-Edouard Sarlin, Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich · 2020
Cited alongside, same era.
Improved techniques for training score-based generative models
Yang Song and Stefano Ermon · 2020
Cited alongside, same era.
DISK: Learning local features with policy gradient
Michał J. Tyszkiewicz, Pascal Fua, and Eduard Trulls · 2020
Cited alongside, same era.
SegDiff: Image segmentation with diffusion probabilistic models
Tomer Amit, Tal Shaharbany, Eliya Nachmani, and Lior Wolf · 2021
Cited alongside, same era.
Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
Cited alongside, same era.
Cats: Cost aggregation transformers for visual correspondence
Seokju Cho, Sunghwan Hong, Sangryul Jeon, Yunsung Lee, Kwanghoon Sohn, and Seungryong Kim · 2021
Cited alongside, same era.
Diffusion models beat GANs on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
Cited alongside, same era.
Binxin Yang, Shuyang Gu, Bo Zhang, Ting Zhang, Xuejin Chen, Xiaoyan Sun, Dong Chen, and Fang Wen · 2022
Later among the works it cites.
Text-to-image diffusion models are zero-shot classifiers
Kevin Clark and Priyank Jaini · 2023
Closest in time.
DiffEdit: Diffusion-based semantic image editing with mask guidance
Guillaume Couairon, Jakob Verbeek, Holger Schwenk, and Matthieu Cord · 2023
Closest in time.
DiffusionDepth: Diffusion denoising approach for monocular depth estimation
Yiqun Duan, Xianda Guo, and Zheng Zhu · 2023
Closest in time.
PAIR-Diffusion: Object-level image editing with structure-and-appearance paired diffusion models
Vidit Goel, Elia Peruzzo, Yifan Jiang, Dejia Xu, Nicu Sebe, Trevor Darrell, Zhangyang Wang, and Humphrey Shi · 2023
Closest in time.
ASIC: Aligning sparse in-the-wild image collections
Kamal Gupta, Varun Jampani, Carlos Esteves, Abhinav Shrivastava, Ameesh Makadia, Noah Snavely, and Abhishek Kar · 2023
Closest in time.
Imagic: Text-based real image editing with diffusion models
Bahjat Kawar, Shiran Zada, Oran Lang, Omer Tov, Huiwen Chang, Tali Dekel, Inbar Mosseri, and Michal Irani · 2023
Closest in time.
Your diffusion model is secretly a zero-shot classifier
Alexander C. Li, Mihir Prabhudesai, Shivam Duggal, Ellis Brown, and Deepak Pathak · 2023
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Diffusion hyperfeatures: Searching through time and space for semantic correspondence
Grace Luo, Lisa Dunlap, Dong Huk Park, Aleksander Holynski, and Trevor Darrell · 2023
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Neural Congealing: Aligning images to a joint semantic atlas
Dolev Ofri-Amar, Michal Geyer, Yoni Kasten, and Tali Dekel · 2023
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DINOv2: Learning robust visual features without supervision
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, et al · 2023
Closest in time.
Monocular depth estimation using diffusion models
Saurabh Saxena, Abhishek Kar, Mohammad Norouzi, and David J. Fleet · 2023
Closest in time.
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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Open-vocabulary panoptic segmentation with text-to-image diffusion models
Jiarui Xu, Sifei Liu, Arash Vahdat, Wonmin Byeon, Xiaolong Wang, and Shalini De Mello · 2023
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Adding conditional control to text-to-image diffusion models
Lvmin Zhang and Maneesh Agrawala · 2023
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Unleashing text-to-image diffusion models for visual perception
Wenliang Zhao, Yongming Rao, Zuyan Liu, Benlin Liu, Jie Zhou, and Jiwen Lu · 2023
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