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ICCV
2011
IEEE
12 years 5 months ago
Actively Selecting Annotations Among Objects and Attributes
We present an active learning approach to choose image annotation requests among both object category labels and the objects’ attribute labels. The goal is to solicit those labe...
Adriana Kovashka, Sudheendra Vijayanarasimhan, Kri...
CVPR
2011
IEEE
13 years 1 months ago
Sharing Features Between Objects and Their Attributes
Visual attributes expose human-defined semantics to object recognition models, but existing work largely restricts their influence to mid-level cues during classifier training....
Sung Ju Hwang, Fei Sha, Kristen Grauman
AAAI
2012
11 years 7 months ago
Relative Attributes for Enhanced Human-Machine Communication
We propose to model relative attributes1 that capture the relationships between images and objects in terms of human-nameable visual properties. For example, the models can captur...
Devi Parikh, Adriana Kovashka, Amar Parkash, Krist...
ICCV
2011
IEEE
12 years 5 months ago
Relative Attributes
Human-nameable visual “attributes” can benefit various recognition tasks. However, existing techniques restrict these properties to categorical labels (for example, a person ...
Devi Parikh, Kristen Grauman
TVCG
2010
217views more  TVCG 2010»
13 years 3 months ago
How Information Visualization Novices Construct Visualizations
—It remains challenging for information visualization novices to rapidly construct visualizations during exploratory data analysis. We conducted an exploratory laboratory study i...
Lars Grammel, Melanie Tory, Margaret-Anne D. Store...