551 citations · 1.4k across the 43 of their papers we have counts for
17 papers · 1 filter
Face-Focused Cross-Stream Network for Deception Detection in Videos
Mingyu Ding, An Zhao, Zhiwu Lu +2
Automated deception detection (ADD) from real-life videos is a challenging task. It specifically needs to address two problems: (1) Both face and body contain useful cues regarding…
Disjoint Label Space Transfer Learning with Common Factorised Space
Xiaobin Chang, Yongxin Yang, Tao Xiang +1
In this paper, a unified approach is presented to transfer learning that addresses several source and target domain label-space and annotation assumptions with a single model. It i…
Zero-Shot Learning with Sparse Attribute Propagation
Nanyi Fei, Jiechao Guan, Zhiwu Lu +2
Zero-shot learning (ZSL) aims to recognize a set of unseen classes without any training images. The standard approach to ZSL requires a set of training images annotated with seen c…
Zero and Few Shot Learning with Semantic Feature Synthesis and Competitive Learning
Zhiwu Lu, Jiechao Guan, Aoxue Li +3
Zero-shot learning (ZSL) is made possible by learning a projection function between a feature space and a semantic space (e.g.,~an attribute space). Key to ZSL is thus to learn a p…
Transferrable Feature and Projection Learning with Class Hierarchy for Zero-Shot Learning
Aoxue Li, Zhiwu Lu, Jiechao Guan +3
Zero-shot learning (ZSL) aims to transfer knowledge from seen classes to unseen ones so that the latter can be recognised without any training samples. This is made possible by lea…
Domain-Invariant Projection Learning for Zero-Shot Recognition
An Zhao, Mingyu Ding, Jiechao Guan +3
Zero-shot learning (ZSL) aims to recognize unseen object classes without any training samples, which can be regarded as a form of transfer learning from seen classes to unseen ones…