Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Engineering
R2gan: Cross-Modal Recipe Retrieval With Generative Adversarial Network, Bin Zhu, Chong-Wah Ngo, Jingjing Chen, Yanbin Hao
R2gan: Cross-Modal Recipe Retrieval With Generative Adversarial Network, Bin Zhu, Chong-Wah Ngo, Jingjing Chen, Yanbin Hao
Research Collection School Of Computing and Information Systems
Representing procedure text such as recipe for crossmodal retrieval is inherently a difficult problem, not mentioning to generate image from recipe for visualization. This paper studies a new version of GAN, named Recipe Retrieval Generative Adversarial Network (R2GAN), to explore the feasibility of generating image from procedure text for retrieval problem. The motivation of using GAN is twofold: learning compatible cross-modal features in an adversarial way, and explanation of search results by showing the images generated from recipes. The novelty of R2GAN comes from architecture design, specifically a GAN with one generator and dual discriminators is used, which makes the …
Data-Driven Approaches To Community-Contributed Video Applications, Xiao Wu, Chong-Wah Ngo, Wan-Lei Zhao
Data-Driven Approaches To Community-Contributed Video Applications, Xiao Wu, Chong-Wah Ngo, Wan-Lei Zhao
Research Collection School Of Computing and Information Systems
With the prosperity of video-sharing websites such as YouTube, the amount of community-contributed video has increased dramatically. Reportedly more than 65,000 new videos were uploaded to YouTube every day in July 2006 and it's estimated that 20 hours of new videos were uploaded to the site every minute in May 2009. In addition to the huge volume of video data, the social Web provides rich contextual and social resources associated with videos. These resources include title, tags, thumbnails, related videos, and user and community information, as illustrated in Figure 1. While billions of user-generated videos accompanied with rich-media information have …
Towards Google Challenge: Combining Contextual And Social Information For Web Video Categorization, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo
Towards Google Challenge: Combining Contextual And Social Information For Web Video Categorization, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Web video categorization is a fundamental task for web video search. In this paper, we explore the Google challenge from a new perspective by combing contextual and social information under the scenario of social web. The semantic meaning of text (title and tags), video relevance from related videos, and user interest induced from user videos, are integrated to robustly determine the video category. Experiments on YouTube videos demonstrate the effectiveness of the proposed solution. The performance reaches 60% improvement compared to the traditional text based classifiers.