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C. Lawrence Zitnick
Researcher at Facebook
Publications - 127
Citations - 66784
C. Lawrence Zitnick is an academic researcher from Facebook. The author has contributed to research in topics: Object detection & Computer science. The author has an hindex of 58, co-authored 118 publications receiving 47012 citations. Previous affiliations of C. Lawrence Zitnick include Massachusetts Institute of Technology & University of Washington.
Papers
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Book ChapterDOI
Microsoft COCO: Common Objects in Context
Tsung-Yi Lin,Michael Maire,Serge Belongie,James Hays,Pietro Perona,Deva Ramanan,Piotr Dollár,C. Lawrence Zitnick +7 more
TL;DR: A new dataset with the goal of advancing the state-of-the-art in object recognition by placing the question of object recognition in the context of the broader question of scene understanding by gathering images of complex everyday scenes containing common objects in their natural context.
Proceedings ArticleDOI
VQA: Visual Question Answering
Stanislaw Antol,Aishwarya Agrawal,Jiasen Lu,Margaret Mitchell,Dhruv Batra,C. Lawrence Zitnick,Devi Parikh +6 more
TL;DR: The task of free-form and open-ended Visual Question Answering (VQA) is proposed, given an image and a natural language question about the image, the task is to provide an accurate natural language answer.
Proceedings ArticleDOI
CIDEr: Consensus-based image description evaluation
TL;DR: A novel paradigm for evaluating image descriptions that uses human consensus is proposed and a new automated metric that captures human judgment of consensus better than existing metrics across sentences generated by various sources is evaluated.
Book ChapterDOI
Edge Boxes: Locating Object Proposals from Edges
C. Lawrence Zitnick,Piotr Dollár +1 more
TL;DR: A novel method for generating object bounding box proposals using edges is proposed, showing results that are significantly more accurate than the current state-of-the-art while being faster to compute.
Posted Content
VQA: Visual Question Answering
Aishwarya Agrawal,Jiasen Lu,Stanislaw Antol,Margaret Mitchell,C. Lawrence Zitnick,Dhruv Batra,Devi Parikh +6 more
TL;DR: The task of free-form and open-ended Visual Question Answering (VQA) is proposed, given an image and a natural language question about the image, the task is to provide an accurate natural language answer.