The world-wide-web has become a large ecosystem that reaches billions of users through information processing and sharing, and most of this information resides in pixels. Web-based services like YouTube and Flickr, and social networks such as Facebook have become more and more popular, allowing people to easily upload, share and annotate massive amounts of images and videos. Vision and social media thus has recently become a very active inter-disciplinary area, involving computer vision, multimedia, machine-learning, information retrieval, and data mining.
This workshop aims to bring together leading researchers in the related fields to advocate and promote new research directions for problems involving vision and social media, such as large-scale visual content analysis, search and mining. VSM will provide an interactive platform for academic and industry researchers to disseminate their most recent results, discuss potential new directions in vision and social media, and promote new interdisciplinary collaborations. The program will consist of invited talks, panels, discussions, and reviewed paper submissions.
Topics of interest include (but are not limited to):
- Content analysis for vision and social media
- Efficient learning and mining algorithms for large-scale vision and social media analysis
- Understanding social media content and dynamics
- Contextual models for computer vision and social media
- Machine learning and data mining for social media
- Indexing and retrieval for largescale social media information
- Tagging, semantic annotation, and object recognition on massive multimedia collections
- Scalable and distributed machine learning and data mining methods for vision
- Interfaces for exploring, browsing and visualizing large visual collections
- Construction and evaluation of large‐scale visual collections
- Crowdsourcing for vision problems Scene reconstruction and matching using large scale web images