4 papers
Adaptive Bregman Proximal Stochastic Gradient with a Stabilized Barzilai--Borwein Step Size
Chenhan Jin, Shengze Xu, Binghui Xie +4
Bregman proximal stochastic gradient (BPSG) methods bring variance-reduced composite optimization to objectives whose geometry is poorly captured by Euclidean smoothness. Their per…
OrderDP: A Theoretically Guaranteed Lossless Dynamic Data Pruning Framework
Chenhan Jin, Shengze Xu, Qingsong Wang +3
Data pruning (DP), as an oft-stated strategy to alleviate heavy training burdens, reduces the volume of training samples according to a well-defined pruning method while striving f…
Super-resolving Real-world Image Illumination Enhancement: A New Dataset and A Conditional Diffusion Model
Yang Liu, Yaofang Liu, Jinshan Pan +4
Most existing super-resolution methods and datasets have been developed to improve the image quality in well-lighted conditions. However, these methods do not work well in real-wor…
VJT: A Video Transformer on Joint Tasks of Deblurring, Low-light Enhancement and Denoising
Yuxiang Hui, Yang Liu, Yaofang Liu +4
Video restoration task aims to recover high-quality videos from low-quality observations. This contains various important sub-tasks, such as video denoising, deblurring and low-lig…