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GTC ON-DEMAND

Presentation
Media
Abstract:
We'll explore new techniques for TV show summarization using multimodal deep learning for saliency detection and fusion. For TV show summarization, the goal is to compact visual summary with informativeness and enjoyability to attract audience. In our work, we propose a multimodal summarization platform to integrate the multimodal saliences learned from video, audio, and text. Our work focuses on three aspects: 1) the saliency extraction for video, audio, and text using deep learning networks; 2) fusion framework design for multimodal information integration; 3) developing tools to speed up video processing. Using AI Vision, which is a public cloud-based AI service, we summarize a TV show with 11 hours duration in one minute.
We'll explore new techniques for TV show summarization using multimodal deep learning for saliency detection and fusion. For TV show summarization, the goal is to compact visual summary with informativeness and enjoyability to attract audience. In our work, we propose a multimodal summarization platform to integrate the multimodal saliences learned from video, audio, and text. Our work focuses on three aspects: 1) the saliency extraction for video, audio, and text using deep learning networks; 2) fusion framework design for multimodal information integration; 3) developing tools to speed up video processing. Using AI Vision, which is a public cloud-based AI service, we summarize a TV show with 11 hours duration in one minute.  Back
 
Topics:
Computer Vision, Intelligent Video Analytics, Video & Image Processing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8221
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