A
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.
Papers
More filters
Posted Content
QuerYD: A video dataset with high-quality text and audio narrations
TL;DR: The QuerYD dataset is introduced, a new large-scale dataset for retrieval and event localisation in video that is based on YouDescribe, a volunteer project that assists visually-impaired people by attaching voiced narrations to existing YouTube videos.
Posted Content
From Same Photo: Cheating on Visual Kinship Challenges
TL;DR: In this article, the authors investigate the influence of data inference in published data sets for kinship verification and conclude that faces derived from the same photograph are a strong inadvertent signal in all the data sets they examined, and it is likely that the fraction of kinship explained by existing kinship models is small.
Oxford TRECVid 2007 - Notebook paper
James Philbin,Josef Sivic,Vittorio Ferrari,Manuel Marin,Anna Bosch,Nicholas Apostolof,Andrew Zisserman +6 more
TL;DR: The Oxford team participated in the high-level feature extraction and interactive search tasks and observed that the main observation this year is that the system can boost retrieval performance by using tailored approaches for specific concepts.
Posted Content
BSL-1K: Scaling up co-articulated sign language recognition using mouthing cues.
Samuel Albanie,Gül Varol,Liliane Momeni,Triantafyllos Afouras,Joon Son Chung,Neil Fox,Andrew Zisserman +6 more
TL;DR: The BSL-1K dataset as discussed by the authors is a collection of British Sign Language (BSL) signs of unprecedented scale, which can be used to train strong sign recognition models for co-articulated signs in BSL and additionally form excellent pretraining for other sign languages.
Journal ArticleDOI
Transformational invariance: a primer
TL;DR: A theoretical framework is demonstrated within which it is possible to construct descriptors for curves which do not vary with viewpoint, known as invariants, which make it possible to recognise plane curves, without explicitly determining the relationship between the curve reference frame and the camera coordinate system.