Continual learning is a branch of deep learning that seeks to strike a balance between learning stability and plasticity. The CVPR 2020 CLVision Continual Learning for Computer Vision challenge is dedicated to evaluating and advancing the current state-of-the-art continual learning methods using the CORe50 dataset with three different continual learning scenarios. This paper presents our approach, called Batch-level Experience Replay with Review, to this challenge. Our team achieved the 1'st place in all three scenarios out of 79 participated teams. The codebase of our implementation is publicly available at https://github.com/RaptorMai/CVPR20_CLVision_challenge
@article{arxiv.2007.05683,
title = {Batch-level Experience Replay with Review for Continual Learning},
author = {Zheda Mai and Hyunwoo Kim and Jihwan Jeong and Scott Sanner},
journal= {arXiv preprint arXiv:2007.05683},
year = {2020}
}