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Training models continually to detect and classify objects, from new classes and new domains, remains an open problem.
Catastrophic forgetting in connectionist networks
Robert M French · 1999
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Continual universal object detection
Xialei Liu, Hao Yang, Avinash Ravichandran, Rahul Bhotika, and Stefano Soatto · 2002
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The PASCAL Visual Object Classes Challenge 2007 (VOC2007) Results
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2007
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The stability-plasticity dilemma: Investigating the continuum from catastrophic forgetting to age-limited learning effects
Martial Mermillod, Aurélia Bugaiska, and Patrick Bonin · 2013
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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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Fast r-cnn
Ross Girshick · 2015
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al · 2017
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Learning without forgetting
Zhizhong Li and Derek Hoiem · 2017
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Gradient episodic memory for continual learning
David Lopez-Paz and Marc’Aurelio Ranzato · 2017
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icarl: Incremental classifier and representation learning
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph H Lampert · 2017
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Incremental learning of object detectors without catastrophic forgetting
Konstantin Shmelkov, Cordelia Schmid, and Karteek Alahari · 2017
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Memory aware synapses: Learning what (not) to forget
Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach, and Tinne Tuytelaars · 2018
Cited alongside, same era.
Packnet: Adding multiple tasks to a single network by iterative pruning
Arun Mallya and Svetlana Lazebnik · 2018
Cited alongside, same era.
Overcoming catastrophic forgetting with hard attention to the task
Joan Serra, Didac Suris, Marius Miron, and Alexandros Karatzoglou · 2018
Cited alongside, same era.
Gradient based sample selection for online continual learning
Rahaf Aljundi, Min Lin, Baptiste Goujaud, and Yoshua Bengio · 2019
Cited alongside, same era.
Continual learning with tiny episodic memories
Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet K Dokania, Philip HS Torr, and Marc’Aurelio Ranzato · 2019
Cited alongside, same era.
Optimal continual learning has perfect memory and is np-hard
Jeremias Knoblauch, Hisham Husain, and Tom Diethe · 2020
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Continual learning for domain adaptation in chest x-ray classification
Matthias Lenga, Heinrich Schulz, and Axel Saalbach · 2020
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Class-incremental learning: survey and performance evaluation on image classification
Marc Masana, Xialei Liu, Bartlomiej Twardowski, Mikel Menta, Andrew D Bagdanov, and Joost van de Weijer · 2020
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Faster ilod: Incremental learning for object detectors based on faster rcnn
Can Peng, Kun Zhao, and Brian C Lovell · 2020
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Class-incremental learning via deep model consolidation
Junting Zhang, Jie Zhang, Shalini Ghosh, Dawei Li, Serafettin Tasci, Larry Heck, Heming Zhang, and C-C Jay Kuo · 2020
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Sebastian Flennerhag, Andrei A Rusu, Razvan Pascanu, Francesco Visin, Hujun Yin, and Raia Hadsell · 2019
Cited alongside, same era.
Memory efficient experience replay for streaming learning
Tyler L Hayes, Nathan D Cahill, and Christopher Kanan · 2019
Cited alongside, same era.
Rilod: Near real-time incremental learning for object detection at the edge
Dawei Li, Serafettin Tasci, Shalini Ghosh, Jingwen Zhu, Junting Zhang, and Larry Heck · 2019
Cited alongside, same era.
Three scenarios for continual learning
Gido M Van de Ven and Andreas S Tolias · 2019
Cited alongside, same era.
Detectron2
Yuxin Wu, Alexander Kirillov, Francisco Massa, Wan-Yen Lo, and Ross Girshick · 2019
Cited alongside, same era.
Rodeo: Replay for online object detection
Manoj Acharya, Tyler L Hayes, and Christopher Kanan · 2020
Cited alongside, same era.
Understanding regularisation methods for continual learning
Frederik Benzing · 2020
Cited alongside, same era.
Wang Zhou, Shiyu Chang, Norma Sosa, Hendrik Hamann, and David Cox · 2020
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Continual prototype evolution: Learning online from non-stationary data streams
Matthias De Lange and Tinne Tuytelaars · 2021
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A continual learning survey: Defying forgetting in classification tasks
Matthias Delange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Ales Leonardis, Greg Slabaugh, and Tinne Tuytelaars · 2021
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Towards open world object detection
KJ Joseph, Salman Khan, Fahad Shahbaz Khan, and Vineeth N Balasubramanian · 2021
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Incremental object detection via meta-learning
Joseph Kj, Jathushan Rajasegaran, Salman Khan, Fahad Shahbaz Khan, and Vineeth N Balasubramanian · 2021
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Rehearsal revealed: The limits and merits of revisiting samples in continual learning
Eli Verwimp, Matthias De Lange, and Tinne Tuytelaars · 2021
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Iccv 2021 workshop sslad track 3b - continual object detection
SSLAD2021 · 2022
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