241 citations · 279 across the 3 of their papers we have counts for
4 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…