DocumentCode :
3672315
Title :
Mind´s eye: A recurrent visual representation for image caption generation
Author :
Xinlei Chen;C. Lawrence Zitnick
Author_Institution :
Carnegie Mellon University, USA
fYear :
2015
fDate :
6/1/2015 12:00:00 AM
Firstpage :
2422
Lastpage :
2431
Abstract :
In this paper we explore the bi-directional mapping between images and their sentence-based descriptions. Critical to our approach is a recurrent neural network that attempts to dynamically build a visual representation of the scene as a caption is being generated or read. The representation automatically learns to remember long-term visual concepts. Our model is capable of both generating novel captions given an image, and reconstructing visual features given an image description. We evaluate our approach on several tasks. These include sentence generation, sentence retrieval and image retrieval. State-of-the-art results are shown for the task of generating novel image descriptions. When compared to human generated captions, our automatically generated captions are equal to or preferred by humans 21.0% of the time. Results are better than or comparable to state-of-the-art results on the image and sentence retrieval tasks for methods using similar visual features.
Keywords :
"Visualization","Computational modeling","Recurrent neural networks","Training","Bidirectional control","Entropy"
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on
Electronic_ISBN :
1063-6919
Type :
conf
DOI :
10.1109/CVPR.2015.7298856
Filename :
7298856
Link To Document :
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