activity
20182022
most citedDetails or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution

8 citations · 10 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2022

Rapid model transfer for medical image segmentation via iterative human-in-the-loop update: from labelled public to unlabelled clinical datasets for multi-organ segmentation in CT

Wenao Ma, Shuang Zheng, Lei Zhang +2

Despite the remarkable success on medical image analysis with deep learning, it is still under exploration regarding how to rapidly transfer AI models from one dataset to another f…

cs.CV20222 cited

Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution

Jie Liang, Hui Zeng, Lei Zhang

Efficient and effective real-world image super-resolution (Real-ISR) is a challenging task due to the unknown complex degradation of real-world images and the limited computation r…

eess.IV20228 cited

Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution

Jie Liang, Hui Zeng, Lei Zhang

Single image super-resolution (SISR) with generative adversarial networks (GAN) has recently attracted increasing attention due to its potentials to generate rich details. However,…

q-bio.MN2020

Noise control and utility: from regulatory network to spatial patterning

Qing Nie, Lingxia Qiao, Yuchi Qiu +2

Stochasticity (or noise) at cellular and molecular levels has been observed extensively as a universal feature for living systems. However, how living systems deal with noise while…

eess.SP2018

An Adaptive Markov Random Field for Structured Compressive Sensing

Suwichaya Suwanwimolkul, Lei Zhang, Dong Gong +4

Exploiting intrinsic structures in sparse signals underpins the recent progress in compressive sensing (CS). The key for exploiting such structures is to achieve two desirable prop…