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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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Video Action Transformer Network
TL;DR: Action Transformer as discussed by the authors uses a Transformer-style architecture to aggregate features from the spatio-temporal context around the person whose actions we are trying to classify, and shows that by using high-resolution, person-specific, class-agnostic queries, the model spontaneously learns to track individual people and to pick up on semantic context from the actions of others.
Proceedings ArticleDOI
Robust computation and parametrization of multiple view relations
TL;DR: A new method is presented for robustly estimating multiple view relations from image point correspondences and its use is illustrated for the estimation of fundamental matrices, image to image homographies and quadratic transformations.
Book ChapterDOI
Feature Based Methods for Structure and Motion Estimation
TL;DR: This report is a brief overview of the use of “feature based” methods in structure and motion computation and a companion paper by Irani and Anandan reviews “direct’ methods.
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LRS3-TED: a large-scale dataset for visual speech recognition
TL;DR: This paper introduces a new multi-modal dataset for visual and audio-visual speech recognition that includes face tracks from over 400 hours of TED and TEDx videos, along with the corresponding subtitles and word alignment boundaries.
Proceedings ArticleDOI
Harvesting Image Databases from the Web
TL;DR: A multi-modal approach employing both text, meta data and visual features is used to gather many, high-quality images from the Web to automatically generate a large number of images for a specified object class.