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» Adapting Object Recognition across Domains: A Demonstration
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CVPR
2012
IEEE
13 years 2 months ago
Discovering localized attributes for fine-grained recognition
Attributes are visual concepts that can be detected by machines, understood by humans, and shared across categories. They are particularly useful for fine-grained domains where c...
Kun Duan, Devi Parikh, David J. Crandall, Kristen ...
NAACL
2010
14 years 9 months ago
Automatic Domain Adaptation for Parsing
Current statistical parsers tend to perform well only on their training domain and nearby genres. While strong performance on a few related domains is sufficient for many situatio...
David McClosky, Eugene Charniak, Mark Johnson
CVPR
2010
IEEE
15 years 8 months ago
Optimizing One-Shot Recognition with Micro-Set Learning
For object category recognition to scale beyond a small number of classes, it is important that algorithms be able to learn from a small amount of labeled data per additional clas...
Kevin Tang, Marshall Tappen, Rahul Sukthankar, Chr...
NIPS
2007
15 years 1 months ago
Object Recognition by Scene Alignment
Current object recognition systems can only recognize a limited number of object categories; scaling up to many categories is the next challenge. We seek to build a system to reco...
Bryan C. Russell, Antonio Torralba, Ce Liu, Robert...
CVPR
2007
IEEE
16 years 1 months ago
Principal Curvature-Based Region Detector for Object Recognition
This paper presents a new structure-based interest region detector called Principal Curvature-Based Regions (PCBR) which we use for object class recognition. The PCBR interest ope...
Hongli Deng, Wei Zhang, Eric N. Mortensen, Thomas ...