  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
