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In this work, we aim to address the challenging task of open set recognition (OSR).
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Abhijit Bendale and Terrance E Boult · 2016
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Sergey Demyanov Zongyuan Ge and Rahil Garnavi · 2017
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Ben Poole, Sherjil Ozair, Aaron van den Oord, Alexander A Alemi, and George Tucker · 2019
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Classification-reconstruction learning for open-set recognition
Ryota Yoshihashi, Wen Shao, Rei Kawakami, Shaodi You, Makoto Iida, and Takeshi Naemura · 2019
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Learning open set network with discriminative reciprocal points
Guangyao Chen, Limeng Qiao, Yemin Shi, Peixi Peng, Jia Li, Tiejun Huang, Shiliang Pu, and Yonghong Tian · 2020
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Generalized odin: Detecting out-of-distribution image without learning from out-of-distribution data
Yen-Chang Hsu, Yilin Shen, Hongxia Jin, and Zsolt Kira · 2020
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Formal limitations on the measurement of mutual information
David McAllester and Karl Stratos · 2020
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Pramuditha Perera, Vlad I Morariu, Rajiv Jain, Varun Manjunatha, Curtis Wigington, Vicente Ordonez, and Vishal M Patel · 2020
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Conditional gaussian distribution learning for open set recognition
Xin Sun, Zhenning Yang, Chi Zhang, Keck-Voon Ling, and Guohao Peng · 2020
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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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Interaction via bi-directional graph of semantic region affinity for scene parsing
Henghui Ding, Hui Zhang, Jun Liu, Jiaxin Li, Zijian Feng, and Xudong Jiang · 2021
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Prototypical matching and open set rejection for zero-shot semantic segmentation
Hui Zhang and Henghui Ding · 2021
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