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Recent advances in text-to-image (T2I) diffusion models have facilitated creative and photorealistic image synthesis.
Visualizing data using t-sne
Laurens Van der Maaten and Geoffrey Hinton · 2008
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Principal component analysis
Hervé Abdi and Lynne J Williams · 2010
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Learning multiple layers of features from tiny images
Alex Krizhevsky · 2012
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Python tesseract
Samuel Hoffstaetter and contributors · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Texture synthesis using convolutional neural networks
Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge · 2015
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Image style transfer using convolutional neural networks
Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge · 2016
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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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Openimages: A public dataset for large-scale multi-label and multi-class image classification
Ivan Krasin, Tom Duerig, Neil Alldrin, Vittorio Ferrari, Sami Abu-El-Haija, Alina Kuznetsova, Hassan Rom, Jasper Uijlings, Stefan Popov, Shahab Kamali, Matteo Malloci, Jordi Pont-Tuset, Andreas Veit, Serge Belongie, Victor Gomes, Abhinav Gupta, Chen Sun, Gal Chechik, David Cai, Zheyun Feng, Dhyanesh Narayanan, and Kevin Murphy · 2017
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Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2017
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Decoupled weight decay regularization, 2019
Ilya Loshchilov and Frank Hutter · 2019
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The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale
Alina Kuznetsova, Hassan Rom, Neil Alldrin, Jasper Uijlings, Ivan Krasin, Jordi Pont-Tuset, Shahab Kamali, Stefan Popov, Matteo Malloci, Alexander Kolesnikov, Tom Duerig, and Vittorio Ferrari · 2020
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Individual differences among deep neural network models
Johannes Mehrer, Courtney Spoerer, Nikolaus Kriegeskorte, and Tim Kietzmann · 2020
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pytorch-fid: FID Score for PyTorch
Maximilian Seitzer · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Accounting for variance in machine learning benchmarks
Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Nazanin Mohammadi Sepahvand, Edward Raff, Kanika Madan, Vikram Voleti, et al · 2021
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Pytorch library for cam methods
Jacob Gildenblat and contributors · 2021
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David Picard · 2021
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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, et al · 2021
Cited alongside, same era.
ediff-i: Text-to-image diffusion models with an ensemble of expert denoisers
Yogesh Balaji, Seungjun Nah, Xun Huang, Arash Vahdat, Jiaming Song, Qinsheng Zhang, Karsten Kreis, Miika Aittala, Timo Aila, Samuli Laine, et al · 2022
Cited alongside, same era.
Masked-attention mask transformer for universal image segmentation
Bowen Cheng, Ishan Misra, Alexander G Schwing, Alexander Kirillov, and Rohit Girdhar · 2022
Localizing object-level shape variations with text-to-image diffusion models
Or Patashnik, Daniel Garibi, Idan Azuri, Hadar Averbuch-Elor, and Daniel Cohen-Or · 2023
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Wuerstchen: An efficient architecture for large-scale text-to-image diffusion models, 2023
Pablo Pernias, Dominic Rampas, Mats L. Richter, Christopher J. Pal, and Marc Aubreville · 2023
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Synthetic shifts to initial seed vector exposes the brittle nature of latent-based diffusion models
Mao Po-Yuan, Shashank Kotyan, Tham Yik Foong, and Danilo Vasconcellos Vargas · 2023
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It is all about where you start: Text-to-image generation with seed selection
Dvir Samuel, Rami Ben-Ari, Simon Raviv, Nir Darshan, and Gal Chechik · 2023
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Cited alongside, same era.
Instance-wise occlusion and depth orders in natural scenes
Hyunmin Lee and Jaesik Park · 2022
Cited alongside, same era.
Efficientformer: Vision transformers at mobilenet speed
Yanyu Li, Geng Yuan, Yang Wen, Ju Hu, Georgios Evangelidis, Sergey Tulyakov, Yanzhi Wang, and Jian Ren · 2022
Cited alongside, same era.
Hierarchical text-conditional image generation with clip latents, 2022
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models, 2022
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Improving deep neural network random initialization through neuronal rewiring
Leonardo Scabini, Bernard De Baets, and Odemir M Bruno · 2022
Cited alongside, same era.
Diffusers: State-of-the-art diffusion models
Patrick von Platen, Suraj Patil, Anton Lozhkov, Pedro Cuenca, Nathan Lambert, Kashif Rasul, Mishig Davaadorj, Dhruv Nair, Sayak Paul, William Berman, Yiyi Xu, Steven Liu, and Thomas Wolf · 2022
Cited alongside, same era.
Scaling autoregressive models for content-rich text-to-image generation
Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, et al · 2022
Cited alongside, same era.
Axel Sauer, Dominik Lorenz, Andreas Blattmann, and Robin Rombach · 2023
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Dragdiffusion: Harnessing diffusion models for interactive point-based image editing
Yujun Shi, Chuhui Xue, Jiachun Pan, Wenqing Zhang, Vincent YF Tan, and Song Bai · 2023
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Freeu: Free lunch in diffusion u-net
Chenyang Si, Ziqi Huang, Yuming Jiang, and Ziwei Liu · 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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Uncovering the disentanglement capability in text-to-image diffusion models
Qiucheng Wu, Yujian Liu, Handong Zhao, Ajinkya Kale, Trung Bui, Tong Yu, Zhe Lin, Yang Zhang, and Shiyu Chang · 2023
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Xiaoshi Wu, Yiming Hao, Keqiang Sun, Yixiong Chen, Feng Zhu, Rui Zhao, and Hongsheng Li · 2023
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Synartifact: Classifying and alleviating artifacts in synthetic images via vision-language model
Bin Cao, Jianhao Yuan, Yexin Liu, Jian Li, Shuyang Sun, Jing Liu, and Bo Zhao · 2024
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Tino-edit: Timestep and noise optimization for robust diffusion-based image editing
Sherry X Chen, Yaron Vaxman, Elad Ben Baruch, David Asulin, Aviad Moreshet, Kuo-Chin Lien, Misha Sra, and Pradeep Sen · 2024
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Tiam-a metric for evaluating alignment in text-to-image generation
Paul Grimal, Hervé Le Borgne, Olivier Ferret, and Julien Tourille · 2024
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Initno: Boosting text-to-image diffusion models via initial noise optimization
Xiefan Guo, Jinlin Liu, Miaomiao Cui, Jiankai Li, Hongyu Yang, and Di Huang · 2024
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Diffusion lens: Interpreting text encoders in text-to-image pipelines
Michael Toker, Hadas Orgad, Mor Ventura, Dana Arad, and Yonatan Belinkov · 2024
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Depth anything: Unleashing the power of large-scale unlabeled data
Lihe Yang, Bingyi Kang, Zilong Huang, Xiaogang Xu, Jiashi Feng, and Hengshuang Zhao · 2024
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Mastering text-to-image diffusion: Recaptioning, planning, and generating with multimodal llms
Ling Yang, Zhaochen Yu, Chenlin Meng, Minkai Xu, Stefano Ermon, and Bin Cui · 2024
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Uncovering the text embedding in text-to-image diffusion models
Hu Yu, Hao Luo, Fan Wang, and Feng Zhao · 2024
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