CafeBoost: Causal Feature Boost To Eliminate Task-Induced Bias for Class Incremental Learning

no code implementations • CVPR 2023 • Benliu Qiu, Hongliang Li, Haitao Wen, Heqian Qiu, Lanxiao Wang, Fanman Meng, Qingbo Wu, Lili Pan

We place continual learning into a causal framework, based on which we find the task-induced bias is reduced naturally by two underlying mechanisms in task and domain incremental learning.

Class Incremental Learning Incremental Learning

Contrastive Continuity on Augmentation Stability Rehearsal for Continual Self-Supervised Learning

no code implementations • ICCV 2023 • Haoyang Cheng, Haitao Wen, Xiaoliang Zhang, Heqian Qiu, Lanxiao Wang, Hongliang Li

In order to address catastrophic forgetting without overfitting on the rehearsal samples, we propose Augmentation Stability Rehearsal (ASR) in this paper, which selects the most representative and discriminative samples by estimating the augmentation stability for rehearsal.

Self-Supervised Learning