218 citations · 247 across the 5 of their papers we have counts for
5 papers
Efficient Low-Resolution Face Recognition via Bridge Distillation
Shiming Ge, Shengwei Zhao, Chenyu Li +2
Face recognition in the wild is now advancing towards light-weight models, fast inference speed and resolution-adapted capability. In this paper, we propose a bridge distillation a…
Look One and More: Distilling Hybrid Order Relational Knowledge for Cross-Resolution Image Recognition
Shiming Ge, Kangkai Zhang, Haolin Liu +4
In spite of great success in many image recognition tasks achieved by recent deep models, directly applying them to recognize low-resolution images may suffer from low accuracy due…
Uncertainty-Aware Learning Against Label Noise on Imbalanced Datasets
Yingsong Huang, Bing Bai, Shengwei Zhao +2
Learning against label noise is a vital topic to guarantee a reliable performance for deep neural networks. Recent research usually refers to dynamic noise modeling with model outp…
Spatiotemporal Knowledge Distillation for Efficient Estimation of Aerial Video Saliency
Jia Li, Kui Fu, Shengwei Zhao +1
The performance of video saliency estimation techniques has achieved significant advances along with the rapid development of Convolutional Neural Networks (CNNs). However, devices…
Low-resolution Face Recognition in the Wild via Selective Knowledge Distillation
Shiming Ge, Shengwei Zhao, Chenyu Li +1
Typically, the deployment of face recognition models in the wild needs to identify low-resolution faces with extremely low computational cost. To address this problem, a feasible s…