no code implementations • 21 Sep 2023 • Mengda Ji, Genjiu Xu, Jianjun Ge, Mingqiang Li
In this paper, we introduce a data sharing game model for federated learning and employ game-theoretic approaches to design a core-selecting incentive mechanism by utilizing a popular concept in cooperative games, the core.
1 code implementation • CVPR 2023 • Xiang Chen, Hao Li, Mingqiang Li, Jinshan Pan
To overcome this problem, we propose an effective DeRaining network, Sparse Transformer (DRSformer) that can adaptively keep the most useful self-attention values for feature aggregation so that the aggregated features better facilitate high-quality image reconstruction.
1 code implementation • CVPR 2023 • Lingshun Kong, Jiangxin Dong, Mingqiang Li, Jianjun Ge, Jinshan Pan
We present an effective and efficient method that explores the properties of Transformers in the frequency domain for high-quality image deblurring.
Ranked #1 on Image Deblurring on GoPro (using extra training data)
no code implementations • 21 Jan 2021 • Ziwen Liu, Mingqiang Li, Congying Han
It is well known that information theory has an excellent explanatory meaning for the network, so we start to solve the disentanglement problem from the perspective of information theory.