114 citations · 373 across the 27 of their papers we have counts for
6 papers · 1 filter
AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results
Andreas Lugmayr, Martin Danelljan, Radu Timofte +18
This paper reviews the AIM 2019 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world setting,…
Progressive Perception-Oriented Network for Single Image Super-Resolution
Zheng Hui, Jie Li, Xinbo Gao +1
Recently, it has been demonstrated that deep neural networks can significantly improve the performance of single image super-resolution (SISR). Numerous studies have concentrated o…
A sparse annotation strategy based on attention-guided active learning for 3D medical image segmentation
Zhenxi Zhang, Jie Li, Zhusi Zhong +2
3D image segmentation is one of the most important and ubiquitous problems in medical image processing. It provides detailed quantitative analysis for accurate disease diagnosis, a…
Reconstructing Perceived Images from Brain Activity by Visually-guided Cognitive Representation and Adversarial Learning
Ziqi Ren, Jie Li, Xuetong Xue +4
Reconstructing visual stimulus (image) only from human brain activity measured with functional Magnetic Resonance Imaging (fMRI) is a significant and meaningful task in Human-AI co…
An Attention-Guided Deep Regression Model for Landmark Detection in Cephalograms
Zhusi Zhong, Jie Li, Zhenxi Zhang +2
Cephalometric tracing method is usually used in orthodontic diagnosis and treatment planning. In this paper, we propose a deep learning based framework to automatically detect anat…
Shared Predictive Cross-Modal Deep Quantization
Erkun Yang, Cheng Deng, Chao Li +3
With explosive growth of data volume and ever-increasing diversity of data modalities, cross-modal similarity search, which conducts nearest neighbor search across different modali…