Adaptive knowledge transfer for class incremental learning

Zhikun Feng, Mian Zhou, Zan Gao, Angelos Stefanidis, Jionglong Su, Kang Dang, Chuanhui Li

Abstract: Highlights•Adaptive learning knowledge transfers reduce the overall network decision boundary.•Using BDKD with complimentary learning helps further reduce accuracy loss.•Our method achieve superior performance in datasets CIFAR-100 and ImageNet100/1000.