AnnoSearch: Image Auto-Annotation by Search
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Image annotation by large-scale content-based image retrieval
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Scene completion using millions of photographs
ACM SIGGRAPH 2007 papers
Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions
Communications of the ACM - 50th anniversary issue: 1958 - 2008
Learning to reduce the semantic gap in web image retrieval and annotation
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Annotating Images by Mining Image Search Results
IEEE Transactions on Pattern Analysis and Machine Intelligence
80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using large-scale web data to facilitate textual query based retrieval of consumer photos
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Textual Query of Personal Photos Facilitated by Large-Scale Web Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Nowadays, increasingly rich and massive social media data (such as texts, images, audios, videos, blogs, and so on) are being posted to the web, including social networking websites (e.g., MySpace, Facebook), photo and video sharing websites (e.g., Flickr, YouTube), and photo forums (e.g., Photosig.com and Photo.net). Recently, researchers from multidisciplinary areas have proposed to use data-driven approaches for multimedia content understanding by leveraging such unlimited web images and videos as well as their associated rich contextual information (e.g., tag, comments, category, title and metadata). In this three hour tutorial, we plan to introduce the important general concepts and themes of this timely topic. We will also review and summarize the recent multimedia content analysis methods using web-scale social media data as well as present insight into the challenges and future directions in this area. Moreover, we will also show extensive demos on image annotation and retrieval by using rich social media data.