Timothy M. Hospedales

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Learning to Compare: Relation Network for Few-Shot Learning

Flood Sung, Yongxin Yang, Li Zhang, Tao Xiang, Philip Hilaire Sean Torr, Timothy M. Hospedales
IEEE/CVF Conference on Computer Vision and…
2018

We present a conceptually simple, flexible, and general framework for few-shot learning, where a classifier must learn to recognise new classes given only few examples from each. Our method, called… (More)

A Markov Clustering Topic Model for mining behaviour in video

Timothy M. Hospedales, Shaogang Gong, Tao Xiang
IEEE 12th International Conference on Computer…
2009

This paper addresses the problem of fully automated mining of public space video data. A novel Markov Clustering Topic Model (MCTM) is introduced which builds on existing Dynamic Bayesian Network… (More)

Sketch Me That Shoe

Qian Yu, Feng Liu, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales, Chen Change Loy
IEEE Conference on Computer Vision and Pattern…
2016

We investigate the problem of fine-grained sketch-based image retrieval (SBIR), where free-hand human sketches are used as queries to perform instance-level retrieval of images. This is an extremely… (More)

Sketch-a-Net that Beats Humans

Qian Yu, Yongxin Yang, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales
BMVC
2015

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 performance is a result of… (More)

Transductive Multi-View Zero-Shot Learning

Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Shaogang Gong
IEEE Transactions on Pattern Analysis and Machine…
2015

Most existing zero-shot learning approaches exploit transfer learning via an intermediate semantic representation shared between an annotated auxiliary dataset and a target dataset with different… (More)

Transductive Multi-view Embedding for Zero-Shot Recognition and Annotation

Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Zhen-Yong Fu, Shaogang Gong
ECCV
2014

Most existing zero-shot learning approaches exploit transfer learning via an intermediate-level semantic representation such as visual attributes or semantic word vectors. Such a semantic… (More)

Person Re-identification by Attributes

Ryan Layne, Timothy M. Hospedales, Shaogang Gong
BMVC
2012

Visually identifying a target individual reliably in a crowded environment observed by a distributed camera network is critical to a variety of tasks in managing business information, border control,… (More)

Attribute Learning for Understanding Unstructured Social Activity

Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Shaogang Gong
ECCV
2012

The rapid development of social video sharing platforms has created a huge demand for automatic video classification and annotation techniques, in particular for videos containing social activities… (More)

Attributes-Based Re-identification

Ryan Layne, Timothy M. Hospedales, Shaogang Gong
Person Re-Identification
2014

Automated person re-identification using only visual information from public-space CCTV video is challenging for many reasons, such as poor resolution or challenges involved in dealing with camera… (More)

Learning Multimodal Latent Attributes

Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Shaogang Gong
IEEE Transactions on Pattern Analysis and Machine…
2014

The rapid development of social media sharing has created a huge demand for automatic media classification and annotation techniques. Attribute learning has emerged as a promising paradigm for… (More)

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