1 code implementation • 18 Mar 2024 • Yuan Shi, Bin Xia, Xiaoyu Jin, Xing Wang, Tianyu Zhao, Xin Xia, Xuefeng Xiao, Wenming Yang
To address these challenges, we propose VmambaIR, which introduces State Space Models (SSMs) with linear complexity into comprehensive image restoration tasks.
no code implementations • 21 Jan 2024 • Xiaoyu Jin, Yuan Shi, Bin Xia, Wenming Yang
By employing a pretrained multi-modal large language model and a vision language model, we generate text descriptions and encode them as context embedding with degradation information for the degraded image.
no code implementations • 16 Nov 2023 • Yuan Shi, Bin Xia, Rui Zhu, Qingmin Liao, Wenming Yang
Color-guided depth map super-resolution (CDSR) improve the spatial resolution of a low-quality depth map with the corresponding high-quality color map, benefiting various applications such as 3D reconstruction, virtual reality, and augmented reality.
no code implementations • 28 Mar 2022 • Yuan Shi
To solve these problems, enlightened by a processing method of Chinese named entity recognition, we propose to use domain knowledge to improve the performance of named entity recognition in areas with low resources.
Chinese Named Entity Recognition Low Resource Named Entity Recognition +3
no code implementations • 13 Feb 2022 • Yuan Shi, Saied Mahdian, Jose Blanchet, Peter Glynn, Andrew Y. Shin, David Scheinker
Using data from cardiovascular surgery patients with long and highly variable post-surgical lengths of stay (LOS), we develop a modeling framework to reduce recovery unit congestion.
no code implementations • 15 Apr 2014 • Yuan Shi, Aurélien Bellet, Fei Sha
We propose a new approach for metric learning by framing it as learning a sparse combination of locally discriminative metrics that are inexpensive to generate from the training data.