Instructors/Speakers Prof. Chengzheng SUN Nanyang Technological University Singapore Abstract Nowadays, collaborative editing systems, such Google Docs, Microsoft Office Online, Dropbox Paper, Box Notes, and CodoxWave (for supporting read-time editing in a wide range of existing web browser-based editors, including Gmail, Wikipedia, Evernote, and WordPress), are ubiquitous and commonly used by hundreds of millions of people around the world. Research on collaborative editing, however, started in the 1980s as a niche area (with a small number of persistent researchers) in the field of Computer-Supported Cooperative Work (CSCW), and was driven mainly by academic curiosity. This niche area has been continuously evolving for over 3 decades and eventually resulted in a large scale adoption in major industry products in recent years. In ...
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Instructors/Speakers Prof. Shimin HU Tsinghua University Beijing Abstract In recent years, with the rapid development of digital technology, the public can capture and produce high-quality visual media conten. However, the current visual media processing techniques cannot satisfy the increasing demands of automatically organize, understand and enhance the media data according to the human intentions and potentially billions of personalized editing. So we focus on how to analysis the images and videos in a perception-oriented way. Personal videos often contain visual distractors, i.e. objects that are accidentally captured that can distract viewers from focusing on the main subjects. We propose methods to automatically detect and localize these distractors. A rule-based method is firstly proposed to detect common distractors. Then a learning ... |
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