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Alexander C. Berg
Researcher at University of North Carolina at Chapel Hill
Publications - 111
Citations - 92856
Alexander C. Berg is an academic researcher from University of North Carolina at Chapel Hill. The author has contributed to research in topics: Object detection & Natural language. The author has an hindex of 57, co-authored 109 publications receiving 67829 citations. Previous affiliations of Alexander C. Berg include Facebook & Stanford University.
Papers
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Proceedings ArticleDOI
Who are you with and where are you going
TL;DR: This model views pedestrians as decision-making agents who consider a plethora of personal, social, and environmental factors to decide where to go next and forms prediction of pedestrian behavior as an energy minimization on this model.
Posted Content
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky,Jia Deng,Hao Su,Jonathan Krause,Sanjeev Satheesh,Sean Ma,Zhiheng Huang,Andrej Karpathy,Aditya Khosla,Michael S. Bernstein,Alexander C. Berg,Li Fei-Fei +11 more
TL;DR: The creation of this benchmark dataset and the advances in object recognition that have been possible as a result are described, and the state-of-the-art computer vision accuracy with human accuracy is compared.
Journal ArticleDOI
Describable Visual Attributes for Face Verification and Image Search
TL;DR: It is shown how one can create and label large data sets of real-world images to train classifiers which measure the presence, absence, or degree to which an attribute is expressed in images, which can then automatically label new images.
Posted Content
Modeling Context in Referring Expressions
TL;DR: This work focuses on incorporating better measures of visual context into referring expression models and finds that visual comparison to other objects within an image helps improve performance significantly.
Book ChapterDOI
Automatic attribute discovery and characterization from noisy web data
TL;DR: This work focuses on discovering attributes and their visual appearance, and is as agnostic as possible about the textual description, and characterizes attributes according to their visual representation: global or local, and type: color, texture, or shape.