Jia Li

This paper introduces Diffusion-Classifier Synergy (DCS), a novel framework where a diffusion model and an FSCIL classifier co-evolve through a dynamic, classifier-derived reward system to achieve state-of-the-art few-shot class-incremental learning.

A novel multi-modality framework for resilient event-RGB semantic segmentation under extreme conditions.