Learning Visual Semantics: Models, Massive Computation, and Innovative Applications


Tutorial at CVPR 2014

June 23rd, 1:00pm-5:00pm, Columbus, OH

Instructors:

     
Shih-Fu Chang John Smith Rogerio Feris Liangliang Cao

Overview:

The explosion of digital multimedia data - including visual content from surveillance cameras, mobile phones, personal photo collections, news footage, or medical images is creating significant opportunities for automated visual analysis. However, the most interesting content in multimedia files is often unconstrained and complex in nature, reflecting a diversity of human behaviors, scenes, activities, and events, which poses serious challenges for computer vision approaches. In this tutorial, we will present the state-of-the-art on large-scale visual semantic modeling, covering methods for obtaining intuitive mid-level semantic feature representations, while presenting innovative applications. The organizers will share their experience in achieving top performance on several recent competitions, including TRECVID, ImageNet, and ImageCLEF, and developing large-scale data and tool resources.

Outline:


Innovative Applications and Datasets:

We will provide pointers to datasets and cover various applications for large-scale visual semantic analysis, including:

Resources: