9 citations · 19 across the 3 of their papers we have counts for
3 papers
eess.IV2021★ 6 cited
RA V-Net: Deep learning network for automated liver segmentation
Zhiqi Lee, Sumin Qi, Chongchong Fan +1
Accurate segmentation of the liver is a prerequisite for the diagnosis of disease. Automated segmentation is an important application of computer-aided detection and diagnosis of l…
cs.CV2020★ 9 cited
Component Divide-and-Conquer for Real-World Image Super-Resolution
Pengxu Wei, Ziwei Xie, Hannan Lu +4
In this paper, we present a large-scale Diverse Real-world image Super-Resolution dataset, i.e., DRealSR, as well as a divide-and-conquer Super-Resolution (SR) network, exploring t…
cs.CV2019★ 4 cited
Difficulty-aware Image Super Resolution via Deep Adaptive Dual-Network
Jinghui Qin, Ziwei Xie, Yukai Shi +1
Recently, deep learning based single image super-resolution(SR) approaches have achieved great development. The state-of-the-art SR methods usually adopt a feed-forward pipeline to…