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: