75.5k citations · 100.8k across the 160 of their papers we have counts for
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Reading Text in the Wild with Convolutional Neural Networks
Max Jaderberg, Karen Simonyan, Andrea Vedaldi +1
In this work we present an end-to-end system for text spotting -- localising and recognising text in natural scene images -- and text based image retrieval. This system is based on…
Automatic Discovery and Optimization of Parts for Image Classification
Sobhan Naderi Parizi, Andrea Vedaldi, Andrew Zisserman +1
Part-based representations have been shown to be very useful for image classification. Learning part-based models is often viewed as a two-stage problem. First, a collection of inf…
Deep Structured Output Learning for Unconstrained Text Recognition
Max Jaderberg, Karen Simonyan, Andrea Vedaldi +1
We develop a representation suitable for the unconstrained recognition of words in natural images: the general case of no fixed lexicon and unknown length. To this end we propose a…
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan, Andrew Zisserman
In this work we investigate the effect of the convolutional network depth on its accuracy in the large-scale image recognition setting. Our main contribution is a thorough evaluati…
Efficient On-the-fly Category Retrieval using ConvNets and GPUs
Ken Chatfield, Karen Simonyan, Andrew Zisserman
We investigate the gains in precision and speed, that can be obtained by using Convolutional Networks (ConvNets) for on-the-fly retrieval - where classifiers are learnt at run time…
Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition
Max Jaderberg, Karen Simonyan, Andrea Vedaldi +1
In this work we present a framework for the recognition of natural scene text. Our framework does not require any human-labelled data, and performs word recognition on the whole im…
Two-Stream Convolutional Networks for Action Recognition in Videos
Karen Simonyan, Andrew Zisserman
We investigate architectures of discriminatively trained deep Convolutional Networks (ConvNets) for action recognition in video. The challenge is to capture the complementary infor…
Speeding up Convolutional Neural Networks with Low Rank Expansions
Max Jaderberg, Andrea Vedaldi, Andrew Zisserman
The focus of this paper is speeding up the evaluation of convolutional neural networks. While delivering impressive results across a range of computer vision and machine learning t…
Return of the Devil in the Details: Delving Deep into Convolutional Nets
Ken Chatfield, Karen Simonyan, Andrea Vedaldi +1
The latest generation of Convolutional Neural Networks (CNN) have achieved impressive results in challenging benchmarks on image recognition and object detection, significantly rai…