Code and data: learning, evaluation

Introduction


This is the project page for learning mixed templates composed of sketches and textures. Combining the methodology of the active basis model and the idea of composing two types of image manifolds, this work seeks integrated modeling for a general set of image features regardless of their forms and metrics. In our search for informative and generative image features, it is observed that simple features and simple combination of them are able to provide promising results in object categorization.

Publication

Zhangzhang Si, Haifeng Gong, Ying Nian Wu, Song-Chun Zhu
Learning mixed image templates for object recognition
IEEE Conference on Vision and Pattern Recognition, June 2009. PDF | Code: learning, evaluation | Latex (zip) | poster (pptx)
Ying Nian Wu, Zhangzhang Si, Chuck Fleming, Song-Chun Zhu
Deformable template as active basis.
International Conference on Computer Vision, 2007. (oral) PDF | Code