277 citations · 1.7k across the 70 of their papers we have counts for
6 papers · 1 filter
Zero-Shot Domain Adaptation via Kernel Regression on the Grassmannian
Yongxin Yang, Timothy Hospedales
Most visual recognition methods implicitly assume the data distribution remains unchanged from training to testing. However, in practice domain shift often exists, where real-world…
When Face Recognition Meets with Deep Learning: an Evaluation of Convolutional Neural Networks for Face Recognition
Guosheng Hu, Yongxin Yang, Dong Yi +4
Deep learning, in particular Convolutional Neural Network (CNN), has achieved promising results in face recognition recently. However, it remains an open question: why CNNs work we…
Weakly Supervised Learning of Objects, Attributes and their Associations
Zhiyuan Shi, Yongxin Yang, Timothy M. Hospedales +1
When humans describe images they tend to use combinations of nouns and adjectives, corresponding to objects and their associated attributes respectively. To generate such a descrip…
Transductive Multi-class and Multi-label Zero-shot Learning
Yanwei Fu, Yongxin Yang, Timothy M. Hospedales +2
Recently, zero-shot learning (ZSL) has received increasing interest. The key idea underpinning existing ZSL approaches is to exploit knowledge transfer via an intermediate-level se…
Transductive Multi-label Zero-shot Learning
Yanwei Fu, Yongxin Yang, Tim Hospedales +2
Zero-shot learning has received increasing interest as a means to alleviate the often prohibitive expense of annotating training data for large scale recognition problems. These me…
Sketch-a-Net that Beats Humans
Qian Yu, Yongxin Yang, Yi-Zhe Song +2
We propose a multi-scale multi-channel deep neural network framework that, for the first time, yields sketch recognition performance surpassing that of humans. Our superior perform…