C
Christopher R. Dance
Researcher at Xerox
Publications - 102
Citations - 4984
Christopher R. Dance is an academic researcher from Xerox. The author has contributed to research in topics: Pixel & Digital image. The author has an hindex of 30, co-authored 102 publications receiving 4772 citations.
Papers
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Proceedings ArticleDOI
Fisher Kernels on Visual Vocabularies for Image Categorization
TL;DR: This work shows that Fisher kernels can actually be understood as an extension of the popular bag-of-visterms, and proposes to apply this framework to image categorization where the input signals are images and where the underlying generative model is a visual vocabulary: a Gaussian mixture model which approximates the distribution of low-level features in images.
Book ChapterDOI
Adapted vocabularies for generic visual categorization
TL;DR: A novel and practical approach to GVC is proposed, which describes the content of all the considered classes of images, and class vocabularies obtained through the adaptation of the universal vocabulary using class-specific data.
Categorizing Nine Visual Classes using Local Appearance Descriptors
TL;DR: A thorough evaluation clearly demonstrates that the bag of keypoints method is robust to background clutter and produces good categorization accuracy even without exploiting geometric information.
Journal ArticleDOI
Knowledge graph completion via complex tensor factorization
Théo Trouillon,Christopher R. Dance,Eric Gaussier,Johannes Welbl,Sebastian Riedel,Guillaume Bouchard +5 more
TL;DR: The approach based on complex embeddings is arguably simple, as it only involves a Hermitian dot product, the complex counterpart of the standard dot product between real vectors, whereas other methods resort to more and more complicated composition functions to increase their expressiveness.
Patent
Mosaicing images with an offset lens
TL;DR: In this paper, a camera can be used to record multiple low-resolution images of an object by shifting a camera lens relative to an image sensor of the camera, each camera image represents a portion of the object.