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Few-shot class incremental learning (FSCIL) portrays the problem of learning new concepts gradually, where only a few examples per concept are available to the learner.
Catastrophic Interference in Connectionist Networks: The Sequential Learning Problem
Michael McCloskey and Neal J. Cohen · 1989
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The Caltech-UCSD Birds-200-2011 Dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
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Distributed Representations of Words and Phrases and their Compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
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Adam: A Method for Stochastic Optimization
Diederik P. Kingma and Jimmy Ba · 2014
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Glove: Global Vectors for Word Representation
Jeffrey Pennington, Richard Socher, and Christopher D. Manning · 2014
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Distilling the Knowledge in a Neural Network
Geoffrey Hinton, Oriol Vinyals, and Jeffrey Dean · 2015
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An empirical study and analysis of generalized zero-shot learning for object recognition in the wild
Wei-Lun Chao, Soravit Changpinyo, Boqing Gong, and Fei Sha · 2016
Earlier work this paper cites.
Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Matching Networks for One Shot Learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, koray kavukcuoglu, and Daan Wierstra · 2016
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Latent embeddings for zero-shot classification
Yongqin Xian, Zeynep Akata, Gaurav Sharma, Quynh Nguyen, Matthias Hein, and Bernt Schiele · 2016
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icarl: Incremental Classifier and Representation Learning
S. Rebuffi, A. Kolesnikov, G. Sperl, and C. H. Lampert · 2017
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Continual Learning with Deep Generative Replay
Hanul Shin, Jung Kwon Lee, Jaehong Kim, and Jiwon Kim · 2017
Earlier work this paper cites.
Incremental Learning of Object Detectors Without Catastrophic Forgetting
Konstantin Shmelkov, Cordelia Schmid, and Karteek Alahari · 2017
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Continual Learning Through Synaptic Intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
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End-to-End Incremental Learning
Francisco M. Castro, Manuel J Marín-Jiménez, Nicolás Guil, Cordelia Schmid, and Karteek Alahari · 2018
Cited alongside, same era.
End-to-End Incremental Learning
Francisco M. Castro, Manuel J. Marin-Jimenez, Nicolas Guil, Cordelia Schmid, and Karteek Alahari · 2018
Cited alongside, same era.
Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence
Arslan Chaudhry, Puneet K. Dokania, Thalaiyasingam Ajanthan, and Philip H. S. Torr · 2018
Cited alongside, same era.
Dynamic Few-Shot Visual Learning Without Forgetting
S. Gidaris and N. Komodakis · 2018
Cited alongside, same era.
Learning without Forgetting
Z. Li and D. Hoiem · 2018
Cited alongside, same era.
A Simple Neural Attentive Meta-Learner
Nikhil Mishra, Mostafa Rohaninejad, Xi Chen, and Pieter Abbeel · 2018
Cited alongside, same era.
Incremental Few-Shot Learning with Attention Attractor Networks, booktitle= Advances in Neural Information Processing Systems (NeurIPS), year = 2019,
Mengye Ren, Renjie Liao, Ethan Fetaya, and Richard S. Zemel · 2019
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Learning to Learn Without Forgetting By Maximizing Transfer and Minimizing Interference
Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, , and Gerald Tesauro · 2019
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Three Scenarios for Continual Learning
Gido M. van de Ven and Andreas S. Tolias · 2019
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Large Scale Incremental Learning
Yue Wu, Yinpeng Chen, Lijuan Wang, Yuancheng Ye, Zicheng Liu, Yandong Guo, and Yun Fu · 2019
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Transductive zero-shot learning for 3d point cloud classification
Ali Cheraghian, Shafin Rahman, Dylan Campbell, and Lars Petersson · 2020
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Variational Continual Learning
Cuong V. Nguyen, Yingzhen Li, Thang D. Bui, and Richard E. Turner · 2018
Cited alongside, same era.
Low-Shot Learning with Imprinted Weights
H. Qi, M. Brown, and D. G. Lowe · 2018
Cited alongside, same era.
Mitigating the hubness problem for zero-shot learning of 3d objects
Ali Cheraghian, Shafin Rahman, Dylan Campbell, and Lars Petersson · 2019
Cited alongside, same era.
Zero-shot learning of 3d point cloud objects
Ali Cheraghian, Shafin Rahman, and Lars Petersson · 2019
Cited alongside, same era.
Bilinear Attention Networks for Person Retrieval
Pengfei Fang, Jieming Zhou, Soumava Kumar Roy, Lars Petersson, and Mehrtash Harandi · 2019
Cited alongside, same era.
Learning a Unified Classifier Incrementally via Rebalancing
Saihui Hou, Xinyu Pan, Chen Change Loy, Zilei Wang, and Dahua Lin · 2019
Cited alongside, same era.
Latent embedding feedback and discriminative features for zero-shot classification
Sanath Narayan, Akshita Gupta, Fahad Shahbaz Khan, Cees G. M. Snoek, and Ling Shao · 2020
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Few-Shot Class-Incremental Learning
Xiaoyu Tao, Xiaopeng Hong, Xinyuan Chang, Songlin Dong, Xing Wei, and Yihong Gong · 2020
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Xtarnet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning
Sung Whan Yoon, Do-Yeon Kim, Jun Seo, and Jaekyun Moon · 2020
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Class-incremental Learning via Deep Model Consolidation
J. Zhang, J. Zhang, S. Ghosh, D. Li, S. Tasci, L. Heck, H. Zhang, and C. . Jay Kuo · 2020
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Maintaining Discrimination and Fairness in Class Incremental Learning
B. Zhao, X. Xiao, G. Gan, B. Zhang, and S. T. Xia · 2020
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Reinforced Attention for Few-Shot Learning and Beyond
Jie Hong, Pengfei Fang, Weihao Li, Zhang Tong, Christian Simon, Lars Petersson, and Mehrtash Harandi · 2021
Closest in time.
Any-shot object detection
Shafin Rahman, Salman Khan, Nick Barnes, and Fahad Shahbaz Khan · 2021
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On Learning the Geodesic Path for Incremental Learning
Christian Simon, Piotr Koniusz, and Mehrtash Harandi · 2021
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