13 citations · 20 across the 8 of their papers we have counts for
8 papers
ASteISR: Adapting Single Image Super-resolution Pre-trained Model for Efficient Stereo Image Super-resolution
Yuanbo Zhou, Yuyang Xue, Wei Deng +3
Despite advances in the paradigm of pre-training then fine-tuning in low-level vision tasks, significant challenges persist particularly regarding the increased size of pre-trained…
Erase to Enhance: Data-Efficient Machine Unlearning in MRI Reconstruction
Yuyang Xue, Jingshuai Liu, Steven McDonagh +1
Machine unlearning is a promising paradigm for removing unwanted data samples from a trained model, towards ensuring compliance with privacy regulations and limiting harmful biases…
The state-of-the-art in Cardiac MRI Reconstruction: Results of the CMRxRecon Challenge in MICCAI 2023
Jun Lyu, Chen Qin, Shuo Wang +47
Cardiac MRI, crucial for evaluating heart structure and function, faces limitations like slow imaging and motion artifacts. Undersampling reconstruction, especially data-driven alg…
Inference Stage Denoising for Undersampled MRI Reconstruction
Yuyang Xue, Chen Qin, Sotirios A. Tsaftaris
Reconstruction of magnetic resonance imaging (MRI) data has been positively affected by deep learning. A key challenge remains: to improve generalisation to distribution shifts bet…
Toward Real World Stereo Image Super-Resolution via Hybrid Degradation Model and Discriminator for Implied Stereo Image Information
Yuanbo Zhou, Yuyang Xue, Jiang Bi +8
Real-world stereo image super-resolution has a significant influence on enhancing the performance of computer vision systems. Although existing methods for single-image super-resol…
Cine cardiac MRI reconstruction using a convolutional recurrent network with refinement
Yuyang Xue, Yuning Du, Gianluca Carloni +3
Cine Magnetic Resonance Imaging (MRI) allows for understanding of the heart's function and condition in a non-invasive manner. Undersampling of the -space is employed to reduce…
Stain Style Transfer using Transitive Adversarial Networks
Shaojin Cai, Yuyang Xue3 Qinquan Gao, Min Du +3
Digitized pathological diagnosis has been in increasing demand recently. It is well known that color information is critical to the automatic and visual analysis of pathological sl…
Attention Based Image Compression Post-Processing Convolutional Neural Network
Yuyang Xue, Jiannan Su
The traditional image compressors, e.g., BPG and H.266, have achieved great image and video compression quality. Recently, Convolutional Neural Network has been used widely in imag…