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Andrew Zisserman
Researcher at University of Oxford
Publications - 808
Citations - 312028
Andrew Zisserman is an academic researcher from University of Oxford. The author has contributed to research in topics: Convolutional neural network & Real image. The author has an hindex of 167, co-authored 808 publications receiving 261717 citations. Previous affiliations of Andrew Zisserman include University of Edinburgh & Microsoft.
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Re-presentations of Art Collections
TL;DR: The objective of this paper is to show how modern computer vision methods can be used to aid the art or book historian in analysing large digital art collections.
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Compact Deep Aggregation for Set Retrieval.
TL;DR: The objective of this work is to learn a compact embedding of a set of descriptors that is suitable for efficient retrieval and ranking, whilst maintaining discriminability of the individual descriptors.
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Interferences in match kernels
TL;DR: This work considers the design of an image representation that embeds and aggregates a set of local descriptors into a single vector and proposes two related solutions, both aimed at equalising the individual contributions of the local descriptor contributions in the final representation.
Book ChapterDOI
Immediate ROI search for 3-d medical images
Karen Simonyan,Marc Modat,Sebastien Ourselin,David M. Cash,Antonio Criminisi,Andrew Zisserman +5 more
TL;DR: A scalable, real-time, visual search engine for 3-D medical images, where a user is able to select a query Region Of Interest (ROI) and automatically detect the corresponding regions within all returned images.
Digital Art History: A subject in transition
TL;DR: In this paper, the authors explore the use of computer graphics and computer vision techniques in the history of art, focusing on analyzing the geometry of perspective paintings to learn about the perspectival skills of artists and explore the evolution of linear perspective in history.