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20152023
most citedEvaluating Two-Stream CNN for Video Classification

114 citations · 228 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.CV2023

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…

cs.CV2022

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…

cs.CV2021★ 3 cited

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…

cs.CV2020★ 3 cited

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…

cs.CV2017★ 100 cited

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…

cs.CV2015★ 114 cited

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…