To cope with real-world dynamics, an intelligent system needs to incrementally acquire,
update, accumulate, and exploit knowledge throughout its lifetime. This ability, known as …

Deep models, eg, CNNs and Vision Transformers, have achieved impressive achievements
in many vision tasks in the closed world. However, novel classes emerge from time to time in …

We present a novel class incremental learning approach based on deep neural networks,
which continually learns new tasks with limited memory for storing examples in the previous …

In this paper, we introduce audio-visual class-incremental learning, a class-incremental
learning scenario for audio-visual video recognition. We demonstrate that joint audio-visual …

A primary goal of class-incremental learning is to strike a balance between stability and
plasticity, where models should be both stable enough to retain knowledge learned from …

Modern machine learning pipelines are limited due to data availability, storage quotas,
privacy regulations, and expensive annotation processes. These constraints make it difficult …

This paper investigates data-free class-incremental learning (DFCIL) for hand gesture
recognition from 3D skeleton sequences. In this class-incremental learning (CIL) setting …

Recently, prompt-based learning has made impressive progress on image class-
incremental learning, but it still lacks sufficient exploration in the video domain. In this paper …

Continual learning (CL) is under-explored in the video domain. The few existing works
contain splits with imbalanced class distributions over the tasks, or study the problem in …

Recent incremental learning for action recognition usually stores representative videos to
mitigate catastrophic forgetting. However, only a few bulky videos can be stored due to the …