With the explosive growth of visual/acoustic signal data in local and cloud data centers, as well as the increasing social-networking sites, we have witnessed the popularity of big data in many multimedia based applications, e.g., large-scale image and video retrieval. Semantically understanding the content of these multimedia data can substantially enhance applications based on the large-scale multimedia data. The major limitation of the many existing models in multimedia and computer vision is that they are built upon low-level visual features and have limited predictability power of regional semantics. The problem is known as the “semantic gap” between the human perception and the low-level visual features. For example, conventional image/video annotators cannot efficiently and effectively label the semantics of these large-scale visual/acoustic data. Many of them are designed heuristically and can only detect a few semantic categories. To effectively fill the semantic gap of visual data in large-scale applications, weakly supervised learning paradigms are developed recently. They focus on an intelligent mechanism that transfers the image/video /social level semantics to different finer levels, e.g., image regions. Compared to the labor-intensive labeling in the fully supervised setting, the transferring mechanism can greatly reduce human effort. Extensive efforts have been dedicated to design weakly supervised learning models that enhance conventional multimedia tasks, while effective tools to manipulate these data are still at their infancy. This special session will target the most recent progresses on visual/acoustic semantic understanding with weak supervision. The possible topics are weakly supervised image segmentation/annotation, photo aesthetic ranking/cropping/retargeting, object localization/tracking, and video summarization/recommendation. This special session also targets on applying new types of weak supervision in semantic modeling, e.g., interactive image rendering and socially-aware image search. The primary objective of this special session fosters focused attention on the latest research progress in this interesting area.
Luming Zhang, National University of Singapore
Yi Yang, The University of Queensland
Liqiang Nie, National University of Singapore
Deadline: January 25, 2015, 11:59 PM PST
Please submit your work using the EasyChair conference website.