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20162026
most citedOn Tiny Episodic Memories in Continual Learning

327 citations · 1.9k across the 347 of their papers we have counts for

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Showing 2021Show all

31 papers · 1 filter

cs.CV2021★ 3 cited

Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning

Yujun Shi, Kuangqi Zhou, Jian Liang +5

Class Incremental Learning (CIL) aims at learning a multi-class classifier in a phase-by-phase manner, in which only data of a subset of the classes are provided at each phase. Pre…

cs.CV2021★ 22 cited

LAVT: Language-Aware Vision Transformer for Referring Image Segmentation

Zhao Yang, Jiaqi Wang, Yansong Tang +3

Referring image segmentation is a fundamental vision-language task that aims to segment out an object referred to by a natural language expression from an image. One of the key cha…

cs.CR2021★ 2 cited

Fixed Points in Cyber Space: Rethinking Optimal Evasion Attacks in the Age of AI-NIDS

Christian Schroeder de Witt, Yongchao Huang, Philip H. S. Torr +1

Cyber attacks are increasing in volume, frequency, and complexity. In response, the security community is looking toward fully automating cyber defense systems using machine learni…

cs.CV2021★ 5 cited

Adversarial Examples on Segmentation Models Can be Easy to Transfer

Jindong Gu, Hengshuang Zhao, Volker Tresp +1

Deep neural network-based image classification can be misled by adversarial examples with small and quasi-imperceptible perturbations. Furthermore, the adversarial examples created…

cs.CV2021★ 2 cited

TransMix: Attend to Mix for Vision Transformers

Jie-Neng Chen, Shuyang Sun, Ju He +3

Mixup-based augmentation has been found to be effective for generalizing models during training, especially for Vision Transformers (ViTs) since they can easily overfit. However, p…

cs.CV2021★ 4 cited

Occluded Video Instance Segmentation: Dataset and ICCV 2021 Challenge

Jiyang Qi, Yan Gao, Yao Hu +7

Although deep learning methods have achieved advanced video object recognition performance in recent years, perceiving heavily occluded objects in a video is still a very challengi…