NDLI: TVPRNN for image caption generation

Content Provider	IET Digital Library
Author	Yang, Liang Hu, Haifeng
Abstract	Image caption generation has attracted considerable interest in computer vision and natural language processes. However, existing methods usually use convolution neural network (CNN) for extracting image feature and recurrent NN (RNN) to predict next produced word, which may make the obtained features unadaptable to the word generated at current time. A new time-varying parallel RNN (TVPRNN) to deal with this task is proposed. TVPRNN uses two classical CNNs (i.e. VggNet and inception v3) for extracting global image feature, jointly with RNN to obtain time-varying feature at each time step, which are used for representing current word. Visual and textual representation in a multimodal space is fused. Moreover, visual attention mechanism is introduced to guild the proposed network. The approach is evaluated using the benchmark Flickr8k, Flickr30k and MSCOCO datasets. The experimental results show that TVPRNN achieves better or on par with the state-of-the-art methods.
Starting Page	1471
Ending Page	1473
Page Count	3
ISSN	00135194
Volume Number	53
e-ISSN	1350911X
Issue Number	Issue 22, Oct (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/53/22
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2017.2351
Journal	Electronics Letters
Publisher Date	2017-09-21
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Benchmark Flickr8k Datasets Computer Vision Computer Vision And Image Processing Technique Convolution Neural Network Feature Extraction Flickr30k Datasets Image Caption Generation Image Feature Extraction Image Recognition Image Representation MSCOCO Datasets Multimodal Space Natural Language Processes Natural Language Processing Neural Computing Technique Recurrent Neural Nets Textual Representation Time-varying Parallel Recurrent Neural Network TVPRNN Visual Attention Mechanism Visual Representation Word Prediction
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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