9 citations · 29 across the 10 of their papers we have counts for
5 papers · 1 filter
Inconsistency Ranking-based Noisy Label Detection for High-quality Data
Ruibin Yuan, Hanzhi Yin, Yi Wang +4
The success of deep learning requires high-quality annotated and massive data. However, the size and the quality of a dataset are usually a trade-off in practice, as data collectio…
Point-DAE: Denoising Autoencoders for Self-supervised Point Cloud Learning
Yabin Zhang, Jiehong Lin, Ruihuang Li +2
Masked autoencoder has demonstrated its effectiveness in self-supervised point cloud learning. Considering that masking is a kind of corruption, in this work we explore a more gene…
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…
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…
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,…