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» Visual Object Recognition Through One-Class Learning
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CVPR
2011
IEEE
14 years 7 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
ICCV
2011
IEEE
13 years 11 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...
ECCV
2004
Springer
16 years 1 months ago
Weak Hypotheses and Boosting for Generic Object Detection and Recognition
In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique...
Andreas Opelt, Michael Fussenegger, Axel Pinz, Pet...
ICCV
2007
IEEE
16 years 1 months ago
A Scalable Approach to Activity Recognition based on Object Use
We propose an approach to activity recognition based on detecting and analyzing the sequence of objects that are being manipulated by the user. In domains such as cooking, where m...
Jianxin Wu, Adebola Osuntogun, Tanzeem Choudhury, ...
ECCV
2008
Springer
16 years 1 months ago
Beyond Nouns: Exploiting Prepositions and Comparative Adjectives for Learning Visual Classifiers
Learning visual classifiers for object recognition from weakly labeled data requires determining correspondence between image regions and semantic object classes. Most approaches u...
Abhinav Gupta, Larry S. Davis