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The ability to identify whether or not a test sample belongs to one of the semantic classes in a classifier's training set is critical to practical deployment of the model.
Improved baselines with momentum contrastive learning
Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He · 2003
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Probabilistic forecasts, calibration and sharpness
Tilmann Gneiting, Fadoua Balabdaoui, and Adrian E. Raftery · 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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80 million tiny images: A large data set for nonparametric object and scene recognition
Antonio Torralba, Rob Fergus, and William T. Freeman · 2008
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Learning multiple layers of features from tiny images
Alex Krizhevsky · 2009
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Mnist handwritten digit database
Yann LeCun, Corinna Cortes, and CJ Burges · 2010
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Reading digits in natural images with unsupervised feature learning
Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, and Andrew Y. Ng · 2011
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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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3d object representations for fine-grained categorization
Jonathan Krause, Michael Stark, Jia Deng, and Li Fei-Fei · 2013
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Fine-grained visual classification of aircraft
Subhransu Maji, Esa Rahtu, Juho Kannala, Matthew Blaschko, and Andrea Vedaldi · 2013
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Towards open set recognition
Walter J. Scheirer, Anderson Rocha, Archana Sapkota, and Terrance E. Boult · 2013
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Describing textures in the wild
M. Cimpoi, S. Maji, I. Kokkinos, S. Mohamed, , and A. Vedaldi · 2014
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Local novelty detection in multi-class recognition problems
Paul Bodesheim, Alexander Freytag, Erik Rodner, and Joachim Denzler · 2015
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Tiny imagenet visual recognition challenge
Ya Le and Xuan Yang · 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, Alexander C. Berg, and Li Fei-Fei · 2015
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
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Turkergaze: Crowdsourcing saliency with webcam based eye tracking
Pingmei Xu, Krista A Ehinger, Yinda Zhang, Adam Finkelstein, Sanjeev R. Kulkarni, and Jianxiong Xiao · 2015
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Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop
Fisher Yu, Yinda Zhang, Shuran Song, Ari Seff, and Jianxiong Xiao · 2015
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Towards open set deep networks
Abhijit Bendale and Terrance E. Boult · 2016
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Deep residual learning for image recognition
Kaiming He, X. Zhang, Shaoqing Ren, and Jian Sun · 2016
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Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, and Zbigniew Wojna · 2016
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Generative openmax for multi-class open set classification
Zongyuan Ge, Sergey Demyanov, and Rahil Garnavi · 2017
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On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q. Weinberger · 2017
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A baseline for detecting misclassified and out-of-distribution examples in neural networks
Dan Hendrycks and Kevin Gimpel · 2017
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SGDR: stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2017
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L2-constrained softmax loss for discriminative face verification
Rajeev Ranjan, Carlos Domingo Castillo, and Rama Chellappa · 2017
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Understanding deep learning requires rethinking generalization
Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, and Oriol Vinyals · 2017
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Places: A 10 million image database for scene recognition
Bolei Zhou, Agata Lapedriza, Aditya Khosla, Aude Oliva, and Antonio Torralba · 2017
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Reducing network agnostophobia
Akshay Raj Dhamija, Manuel Günther, and Terrance E. Boult · 2018
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Enhancing the reliability of out-of-distribution image detection in neural networks
Shiyu Liang, Yixuan Li, and Rayadurgam Srikant · 2018
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Open set learning with counterfactual images
Generative-discriminative feature representations for open-set recognition
Pramuditha Perera, Vlad I. Morariu, Rajiv Jain, Varun Manjunatha, Curtis Wigington, Vicente Ordonez, and Vishal M. Patel · 2020
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P-odn: Prototype-based open deep network for open set recognition
Yu Shu, Yemin Shi, Yaowei Wang, Tiejun Huang, and Yonghong Tian · 2020
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Conditional gaussian distribution learning for open set recognition
Xin Sun, Zhenning Yang, Chi Zhang, Guohao Peng, and Keck-Voon Ling · 2020
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Csi: Novelty detection via contrastive learning on distributionally shifted instances
Jihoon Tack, Sangwoo Mo, Jongheon Jeong, and Jinwoo Shin · 2020
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Hybrid models for open set recognition
Hongjie Zhang, Ang Li, Jie Guo, and Yanwen Guo · 2020
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Revisiting resnets: Improved training and scaling strategies
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Lawrence Neal, Matthew Olson, Xiaoli Fern, Weng-Keen Wong, and Fuxin Li · 2018
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Latent space autoregression for novelty detection
Davide Abati, Angelo Porrello, Simone Calderara, and Rita Cucchiara · 2019
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Learning and the unknown: Surveying steps toward open world recognition
Terrance E. Boult, Steve Cruz, Akshay Raj Dhamija, Manuel Günther, James Henrydoss, and Walter J. Scheirer · 2019
Cited alongside, same era.
Learning to discover novel visual categories via deep transfer clustering
Kai Han, Andrea Vedaldi, and Andrew Zisserman · 2019
Cited alongside, same era.
Deep anomaly detection with outlier exposure
Dan Hendrycks, Mantas Mazeika, and Thomas Dietterich · 2019
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Fast autoaugment
Sungbin Lim, Ildoo Kim, Taesup Kim, Chiheon Kim, and Sungwoong Kim · 2019
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C2ae: Class conditioned auto-encoder for open-set recognition
Poojan Oza and Vishal M. Patel · 2019
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Irwan Bello, William Fedus, Xianzhi Du, Ekin D. Cubuk, Aravind Srinivas, Tsung-Yi Lin, Jonathon Shlens, and Barret Zoph · 2021
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Adversarial reciprocal points learning for open set recognition
Guangyao Chen, Peixi Peng, Xiangqian Wang, and Yonghong Tian · 2021
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2021
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Exploring the limits of out-of-distribution detection
Stanislav Fort, Jie Ren, and Balaji Lakshminarayanan · 2021
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Conditional variational capsule network for open set recognition
Yunrui Guo, Guglielmo Camporese, Wenjing Yang, Alessandro Sperduti, and Lamberto Ballan · 2021
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Autonovel: Automatically discovering and learning novel visual categories
Kai Han, Sylvestre-Alvise Rebuffi, Sebastien Ehrhardt, Andrea Vedaldi, and Andrew Zisserman · 2021
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Natural adversarial examples
Dan Hendrycks, Kevin Zhao, Steven Basart, Jacob Steinhardt, and Dawn Song · 2021
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Opengan: Open-set recognition via open data generation
Shu Kong and Deva Ramanan · 2021
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Open world vision challenge
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Do you even need attention? a stack of feed-forward layers does surprisingly well on imagenet
Luke Melas-Kyriazi · 2021
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Class anchor clustering: a distance-based loss for training open set classifiers
Dimity Miller, Niko Sünderhauf, Michael Milford, and Feras Dayoub · 2021
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Revisiting the calibration of modern neural networks
Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, and Mario Lucic · 2021
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Imagenet-21k pretraining for the masses
Tal Ridnik, Emanuel Ben-Baruch, Asaf Noy, and Lihi Zelnik-Manor · 2021
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Concept generalization in visual representation learning
Mert Bulent Sariyildiz, Yannis Kalantidis, Diane Larlus, and Karteek Alahari · 2021
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Open set recognition with conditional probabilistic generative models
Xin Sun, Chi Zhang, Guosheng Lin, and Keck-Voon Ling · 2021
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Mlp-mixer: An all-mlp architecture for vision
Ilya O. Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Andreas Steiner, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, and Alexey Dosovitskiy · 2021
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What makes instance discrimination good for transfer learning?
Nanxuan Zhao, Zhirong Wu, Rynson W.H. Lau, and Stephen Lin · 2021
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Learning placeholders for open-set recognition
Da-Wei Zhou, Han-Jia Ye, and De-Chuan Zhan · 2021
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Vos: Learning what you don’t know by virtual outlier synthesis
Xuefeng Du, Zhaoning Wang, Mu Cai, and Yixuan Li · 2022
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