268 citations · 1.3k across the 43 of their papers we have counts for
5 papers · 1 filter
Dealing With Heterogeneous 3D MR Knee Images: A Federated Few-Shot Learning Method With Dual Knowledge Distillation
Xiaoxiao He, Chaowei Tan, Bo Liu +8
Federated Learning has gained popularity among medical institutions since it enables collaborative training between clients (e.g., hospitals) without aggregating data. However, due…
AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Results
Ren Yang, Radu Timofte, Xin Li +49
This paper reviews the Challenge on Super-Resolution of Compressed Image and Video at AIM 2022. This challenge includes two tracks. Track 1 aims at the super-resolution of compress…
TransFusion: Multi-view Divergent Fusion for Medical Image Segmentation with Transformers
Di Liu, Yunhe Gao, Qilong Zhangli +8
Combining information from multi-view images is crucial to improve the performance and robustness of automated methods for disease diagnosis. However, due to the non-alignment char…
A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark
Yunhe Gao, Mu Zhou, Di Liu +3
Transformers have demonstrated remarkable performance in natural language processing and computer vision. However, existing vision Transformers struggle to learn from limited medic…
Unsupervised Low-light Image Enhancement with Decoupled Networks
Wei Xiong, Ding Liu, Xiaohui Shen +2
In this paper, we tackle the problem of enhancing real-world low-light images with significant noise in an unsupervised fashion. Conventional unsupervised learning-based approaches…