Rich Image Captioning in the Wild

March 30, 2016 Β· Declared Dead Β· πŸ› 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

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Authors Kenneth Tran, Xiaodong He, Lei Zhang, Jian Sun, Cornelia Carapcea, Chris Thrasher, Chris Buehler, Chris Sienkiewicz arXiv ID 1603.09016 Category cs.CV: Computer Vision Citations 128 Venue 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) Last Checked 4 months ago
Abstract
We present an image caption system that addresses new challenges of automatically describing images in the wild. The challenges include high quality caption quality with respect to human judgments, out-of-domain data handling, and low latency required in many applications. Built on top of a state-of-the-art framework, we developed a deep vision model that detects a broad range of visual concepts, an entity recognition model that identifies celebrities and landmarks, and a confidence model for the caption output. Experimental results show that our caption engine outperforms previous state-of-the-art systems significantly on both in-domain dataset (i.e. MS COCO) and out of-domain datasets.
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