241 citations · 719 across the 8 of their papers we have counts for
8 papers
Learning Open Set Network with Discriminative Reciprocal Points
Guangyao Chen, Limeng Qiao, Yemin Shi +5
Open set recognition is an emerging research area that aims to simultaneously classify samples from predefined classes and identify the rest as 'unknown'. In this process, one of t…
Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning
Limeng Qiao, Yemin Shi, Jia Li +3
Few-shot learning, which aims at extracting new concepts rapidly from extremely few examples of novel classes, has been featured into the meta-learning paradigm recently. Yet, the…
P-ODN: Prototype based Open Deep Network for Open Set Recognition
Yu Shu, Yemin Shi, Yaowei Wang +2
Most of the existing recognition algorithms are proposed for closed set scenarios, where all categories are known beforehand. However, in practice, recognition is essentially an op…
ODN: Opening the Deep Network for Open-set Action Recognition
Yu Shu, Yemin Shi, Yaowei Wang +3
In recent years, the performance of action recognition has been significantly improved with the help of deep neural networks. Most of the existing action recognition works hold the…
Deep Transfer Learning for Person Re-identification
Mengyue Geng, Yaowei Wang, Tao Xiang +1
Person re-identification (Re-ID) poses a unique challenge to deep learning: how to learn a deep model with millions of parameters on a small training set of few or no labels. In th…
Joint Network based Attention for Action Recognition
Yemin Shi, Yonghong Tian, Yaowei Wang +1
By extracting spatial and temporal characteristics in one network, the two-stream ConvNets can achieve the state-of-the-art performance in action recognition. However, such a frame…
Learning long-term dependencies for action recognition with a biologically-inspired deep network
Yemin Shi, Yonghong Tian, Yaowei Wang +1
Despite a lot of research efforts devoted in recent years, how to efficiently learn long-term dependencies from sequences still remains a pretty challenging task. As one of the key…
Sequential Deep Trajectory Descriptor for Action Recognition with Three-stream CNN
Yemin Shi, Yonghong Tian, Yaowei Wang +1
Learning the spatial-temporal representation of motion information is crucial to human action recognition. Nevertheless, most of the existing features or descriptors cannot capture…