4 citations · 7 across the 9 of their papers we have counts for
4 papers · 1 filter
IllumFlow: Illumination-Adaptive Low-Light Enhancement via Conditional Rectified Flow and Retinex Decomposition
Wenyang Wei, Yang yang, Xixi Jia +3
We present IllumFlow, a novel framework that synergizes conditional Rectified Flow (CRF) with Retinex theory for low-light image enhancement (LLIE). Our model addresses low-light e…
Semi-Supervised Regression with Heteroscedastic Pseudo-Labels
Xueqing Sun, Renzhen Wang, Quanziang Wang +3
Pseudo-labeling is a commonly used paradigm in semi-supervised learning, yet its application to semi-supervised regression (SSR) remains relatively under-explored. Unlike classific…
Data-Distill-Net: A Data Distillation Approach Tailored for Reply-based Continual Learning
Wenyang Liao, Quanziang Wang, Yichen Wu +2
Replay-based continual learning (CL) methods assume that models trained on a small subset can also effectively minimize the empirical risk of the complete dataset. These methods ma…
SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning
Yichen Wu, Hongming Piao, Long-Kai Huang +6
Continual Learning (CL) with foundation models has recently emerged as a promising paradigm to exploit abundant knowledge acquired during pre-training for tackling sequential tasks…