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http://dx.doi.org/10.3745/JIPS.02.0098

Video Captioning with Visual and Semantic Features  

Lee, Sujin (Dept. of Computer Science, Graduate School of Kyonggi University)
Kim, Incheol (Dept. of Computer Science, Kyonggi University)
Publication Information
Journal of Information Processing Systems / v.14, no.6, 2018 , pp. 1318-1330 More about this Journal
Abstract
Video captioning refers to the process of extracting features from a video and generating video captions using the extracted features. This paper introduces a deep neural network model and its learning method for effective video captioning. In this study, visual features as well as semantic features, which effectively express the video, are also used. The visual features of the video are extracted using convolutional neural networks, such as C3D and ResNet, while the semantic features are extracted using a semantic feature extraction network proposed in this paper. Further, an attention-based caption generation network is proposed for effective generation of video captions using the extracted features. The performance and effectiveness of the proposed model is verified through various experiments using two large-scale video benchmarks such as the Microsoft Video Description (MSVD) and the Microsoft Research Video-To-Text (MSR-VTT).
Keywords
Attention-Based Caption Generation; Deep Neural Networks; Semantic Feature; Video Captioning;
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