808 citations · 3.7k across the 25 of their papers we have counts for
6 papers · 1 filter
Unsupervised Learning of 3D Structure from Images
Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed +3
A key goal of computer vision is to recover the underlying 3D structure from 2D observations of the world. In this paper we learn strong deep generative models of 3D structures, an…
Spatial Transformer Networks
Max Jaderberg, Karen Simonyan, Andrew Zisserman +1
Convolutional Neural Networks define an exceptionally powerful class of models, but are still limited by the lack of ability to be spatially invariant to the input data in a comput…
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…
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…
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…
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…