papers: visual attribute and object class recognition

Several recent papers discussed the methods to extract visual attributes from images and/or use these attributes for object class recognition. We can view visual attributes as another type of annotation. While image annotation is applied to individual image, visual attributes are specified to an object class; image annotations are usually words, i.e., discrete values, visual attributes can be either discrete (e.g. color={red, blue, ...}) or continuous values (e.g., average size). Here are a few papers I am reading:

• Describing Objects by their Attributes, CVPR 2009
  
• Joint learning of visual attributes, object classes and visual saliency, ICCV 2009
• Learning To Detect Unseen Object Classes by Between-Class Attribute Transfer, CVPR 2009
• Learning Visual Attributes, NIPS 2007

Here is a blog about visual attribute from Tombone.