114 citations · 228 across the 9 of their papers we have counts for
9 papers
Explore the Power of Dropout on Few-shot Learning
Shaobo Lin, Xingyu Zeng, Rui Zhao
The generalization power of the pre-trained model is the key for few-shot deep learning. Dropout is a regularization technique used in traditional deep learning methods. In this pa…
A Unified Framework with Meta-dropout for Few-shot Learning
Shaobo Lin, Xingyu Zeng, Rui Zhao
Conventional training of deep neural networks usually requires a substantial amount of data with expensive human annotations. In this paper, we utilize the idea of meta-learning to…
Memory Enhanced Embedding Learning for Cross-Modal Video-Text Retrieval
Rui Zhao, Kecheng Zheng, Zheng-Jun Zha +2
Cross-modal video-text retrieval, a challenging task in the field of vision and language, aims at retrieving corresponding instance giving sample from either modality. Existing app…
Enhancing and Learning Denoiser without Clean Reference
Rui Zhao, Daniel P. K. Lun, Kin-Man Lam
Recent studies on learning-based image denoising have achieved promising performance on various noise reduction tasks. Most of these deep denoisers are trained either under the sup…
Deep Multi-task Learning for Facial Expression Recognition and Synthesis Based on Selective Feature Sharing
Rui Zhao, Tianshan Liu, Jun Xiao +2
Multi-task learning is an effective learning strategy for deep-learning-based facial expression recognition tasks. However, most existing methods take into limited consideration th…
Enhancement of a CNN-Based Denoiser Based on Spatial and Spectral Analysis
Rui Zhao, Kin-Man Lam, Daniel P. K. Lun
Convolutional neural network (CNN)-based image denoising methods have been widely studied recently, because of their high-speed processing capability and good visual quality. Howev…
Stacked Convolutional Deep Encoding Network for Video-Text Retrieval
Rui Zhao, Kecheng Zheng, Zheng-jun Zha
Existing dominant approaches for cross-modal video-text retrieval task are to learn a joint embedding space to measure the cross-modal similarity. However, these methods rarely exp…
Two-Stream RNN/CNN for Action Recognition in 3D Videos
Rui Zhao, Haider Ali, Patrick van der Smagt
The recognition of actions from video sequences has many applications in health monitoring, assisted living, surveillance, and smart homes. Despite advances in sensing, in particul…
Evaluating Two-Stream CNN for Video Classification
Hao Ye, Zuxuan Wu, Rui-Wei Zhao +3
Videos contain very rich semantic information. Traditional hand-crafted features are known to be inadequate in analyzing complex video semantics. Inspired by the huge success of th…