5 papers
LCPNet: Latent Consistent Proximal Unfolding Network for Infrared Small Target Detection
Tianfang Zhang, Fengyi Wu, Lei Li +4
Infrared small target detection (IRSTD) aims to identify long distance small targets from complex infrared backgrounds, and is a fundamental task in remote sensing. Deep learning m…
Low-Rank Tensor Recovery via Variational Schatten-p Quasi-Norm and Jacobian Regularization
Zhengyun Cheng, Ruizhe Zhang, Guanwen Zhang +3
Higher-order tensors are well-suited for representing multi-dimensional data, such as images and videos, which typically characterize low-rank structures. Low-rank tensor decomposi…
ConformalSAM: Unlocking the Potential of Foundational Segmentation Models in Semi-Supervised Semantic Segmentation with Conformal Prediction
Danhui Chen, Ziquan Liu, Chuxi Yang +4
Pixel-level vision tasks, such as semantic segmentation, require extensive and high-quality annotated data, which is costly to obtain. Semi-supervised semantic segmentation (SSSS)…
Stochastic Weakly Convex Optimization Under Heavy-Tailed Noises
Tianxi Zhu, Yi Xu, Xiangyang Ji
An increasing number of studies have focused on stochastic first-order methods (SFOMs) under heavy-tailed gradient noises, which have been observed in the training of practical dee…
Score-Based Model for Low-Rank Tensor Recovery
Zhengyun Cheng, Changhao Wang, Guanwen Zhang +3
Low-rank tensor decompositions (TDs) provide an effective framework for multiway data analysis. Traditional TD methods rely on predefined structural assumptions, such as CP or Tuck…