19 citations · 23 across the 6 of their papers we have counts for
6 papers
Dual-CBA: Improving Online Continual Learning via Dual Continual Bias Adaptors from a Bi-level Optimization Perspective
Quanziang Wang, Renzhen Wang, Yichen Wu +3
In online continual learning (CL), models trained on changing distributions easily forget previously learned knowledge and bias toward newly received tasks. To address this issue,…
A Refreshed Similarity-based Upsampler for Direct High-Ratio Feature Upsampling
Minghao Zhou, Hong Wang, Yefeng Zheng +1
Feature upsampling is a fundamental and indispensable ingredient of almost all current network structures for dense prediction tasks. Recently, a popular similarity-based feature u…
MEPNet: A Model-Driven Equivariant Proximal Network for Joint Sparse-View Reconstruction and Metal Artifact Reduction in CT Images
Hong Wang, Minghao Zhou, Dong Wei +2
Sparse-view computed tomography (CT) has been adopted as an important technique for speeding up data acquisition and decreasing radiation dose. However, due to the lack of sufficie…
Interactive Segmentation as Gaussian Process Classification
Minghao Zhou, Hong Wang, Qian Zhao +4
Click-based interactive segmentation (IS) aims to extract the target objects under user interaction. For this task, most of the current deep learning (DL)-based methods mainly foll…
Diagnosing Batch Normalization in Class Incremental Learning
Minghao Zhou, Quanziang Wang, Jun Shu +2
Extensive researches have applied deep neural networks (DNNs) in class incremental learning (Class-IL). As building blocks of DNNs, batch normalization (BN) standardizes intermedia…
Multispectral and Hyperspectral Image Fusion by MS/HS Fusion Net
Qi Xie, Minghao Zhou, Qian Zhao +3
Hyperspectral imaging can help better understand the characteristics of different materials, compared with traditional image systems. However, only high-resolution multispectral (H…