13 citations · 27 across the 8 of their papers we have counts for
9 papers
SR-RKAC: Improving Single Image Defocus Deblurring
Peng Tang, Zhiqiang Xu, Pengfei Wei +5
We propose an efficient deep learning method for single image defocus deblurring (SIDD) by further exploring inverse kernel properties. Although the current inverse kernel method,…
Application of the nnU-Net for automatic segmentation of lung lesion on CT images, and implication on radiomic models
Matteo Ferrante, Lisa Rinaldi, Francesca Botta +17
Lesion segmentation is a crucial step of the radiomic workflow. Manual segmentation requires long execution time and is prone to variability, impairing the realisation of radiomic…
High-resolution Iterative Feedback Network for Camouflaged Object Detection
Xiaobin Hu, Shuo Wang, Xuebin Qin +5
Spotting camouflaged objects that are visually assimilated into the background is tricky for both object detection algorithms and humans who are usually confused or cheated by the…
Highly Accurate Dichotomous Image Segmentation
Xuebin Qin, Hang Dai, Xiaobin Hu +3
We present a systematic study on a new task called dichotomous image segmentation (DIS) , which aims to segment highly accurate objects from natural images. To this end, we collect…
Multi-Texture GAN: Exploring the Multi-Scale Texture Translation for Brain MR Images
Xiaobin Hu
Inter-scanner and inter-protocol discrepancy in MRI datasets are known to lead to significant quantification variability. Hence image-to-image or scanner-to-scanner translation is…
Face Super-Resolution Guided by 3D Facial Priors
Xiaobin Hu, Wenqi Ren, John LaMaster +5
State-of-the-art face super-resolution methods employ deep convolutional neural networks to learn a mapping between low- and high- resolution facial patterns by exploring local app…