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Cutting-edge diffusion models produce images with high quality and customizability, enabling them to be used for commercial art and graphic design purposes.
Object retrieval with large vocabularies and fast spatial matching
James Philbin, Ondrej Chum, Michael Isard, Josef Sivic, and Andrew Zisserman · 2007
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Automated flower classification over a large number of classes
Maria-Elena Nilsback and Andrew Zisserman · 2008
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Lost in quantization: Improving particular object retrieval in large scale image databases
James Philbin, Ondrej Chum, Michael Isard, Josef Sivic, and Andrew Zisserman · 2008
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Evaluation of gist descriptors for web-scale image search
Matthijs Douze, Hervé Jégou, Harsimrat Sandhawalia, Laurent Amsaleg, and Cordelia Schmid · 2009
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A family of contextual measures of similarity between distributions with application to image retrieval
Florent Perronnin, Yan Liu, and Jean-Michel Renders · 2009
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The caltech-ucsd birds-200-2011 dataset
Catherine Wah, Steve Branson, Peter Welinder, Pietro Perona, and Serge Belongie · 2011
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Neural codes for image retrieval
Artem Babenko, Anton Slesarev, Alexandr Chigorin, and Victor Lempitsky · 2014
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Multi-scale orderless pooling of deep convolutional activation features
Yunchao Gong, Liwei Wang, Ruiqi Guo, and Svetlana Lazebnik · 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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The pascal visual object classes challenge: A retrospective
Mark Everingham, SM Eslami, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2015
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Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
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Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
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Rethinking the inception architecture for computer vision. 2015
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, and Zbigniew Wojna · 2015
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Instre: a new benchmark for instance-level object retrieval and recognition
Shuang Wang and Shuqiang Jiang · 2015
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Deep image retrieval: Learning global representations for image search
Albert Gordo, Jon Almazán, Jerome Revaud, and Diane Larlus · 2016
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Deep metric learning via lifted structured feature embedding
Hyun Oh Song, Yu Xiang, Stefanie Jegelka, and Silvio Savarese · 2016
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Cnn image retrieval learns from bow: Unsupervised fine-tuning with hard examples
Filip Radenović, Giorgos Tolias, and Ondřej Chum · 2016
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Visual instance retrieval with deep convolutional networks
Ali S Razavian, Josephine Sullivan, Stefan Carlsson, and Atsuto Maki · 2016
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A closer look at memorization in deep networks
Devansh Arpit, Stanislaw 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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Deep clustering for unsupervised learning of visual features
Mathilde Caron, Piotr Bojanowski, Armand Joulin, and Matthijs Douze · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Revisiting oxford and paris: Large-scale image retrieval benchmarking
Filip Radenović, Ahmet Iscen, Giorgos Tolias, Yannis Avrithis, and Ondřej Chum · 2018
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Fine-tuning cnn image retrieval with no human annotation
Filip Radenović, Giorgos Tolias, and Ondřej Chum · 2018
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Multigrain: a unified image embedding for classes and instances
Maxim Berman, Hervé Jégou, Andrea Vedaldi, Iasonas Kokkinos, and Matthijs Douze · 2019
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Pytorch image models
Ross Wightman · 2019
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Cutmix: Regularization strategy to train strong classifiers with localizable features
Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, and Youngjoon Yoo · 2019
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Membership Inference Attacks against GANs by Leveraging Over-representation Regions
Hailong Hu and Jun Pang · 2021
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Self-supervised product quantization for deep unsupervised image retrieval
Young Kyun Jang and Nam Ik Cho · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 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
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This Person (Probably) Exists. Identity Membership Attacks Against GAN Generated Faces
Ryan Webster, Julien Rabin, Loic Simon, and Frederic Jurie · 2021
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Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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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
Cited alongside, same era.
What neural networks memorize and why: Discovering the long tail via influence estimation
Vitaly Feldman and Chiyuan Zhang · 2020
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Bootstrap your own latent-a new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, et al · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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A non-parametric test to detect data-copying in generative models
Casey Meehan, Kamalika Chaudhuri, and Sanjoy Dasgupta · 2020
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How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models
Ahmed Alaa, Boris Van Breugel, Evgeny S. Saveliev, and Mihaela van der Schaar · 2022
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Vicregl: Self-supervised learning of local visual features
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Membership Inference Attacks From First Principles
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Quantifying Memorization Across Neural Language Models
Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramer, and Chiyuan Zhang · 2022
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Deep learning for instance retrieval: A survey
Wei Chen, Yu Liu, Weiping Wang, Erwin M Bakker, Theodoros Georgiou, Paul Fieguth, Li Liu, and Michael S Lew · 2022
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Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations
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Towards GAN Benchmarks Which Require Generalization
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Masked autoencoders are scalable vision learners
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Measuring Forgetting of Memorized Training Examples
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Repaint: Inpainting using denoising diffusion probabilistic models
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A self-supervised descriptor for image copy detection
Ed Pizzi, Sreya Dutta Roy, Sugosh Nagavara Ravindra, Priya Goyal, and Matthijs Douze · 2022
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Hierarchical text-conditional image generation with clip latents
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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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Laion-5b: An open large-scale dataset for training next generation image-text models
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Boosting vision transformers for image retrieval
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Memorization without overfitting: Analyzing the training dynamics of large language models
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Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries
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