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ICCV
2011
IEEE
10 years 5 months ago
Domain Adaptation for Object Recognition: An Unsupervised Approach
Adapting the classifier trained on a source domain to recognize instances from a new target domain is an important problem that is receiving recent attention. In this paper, we p...
Raghuraman Gopalan, Ruonan Li, Rama Chellappa
ICMCS
2007
IEEE
208views Multimedia» more  ICMCS 2007»
11 years 9 months ago
A Cognitive and Unsupervised Map Adaptation Approach to the Recognition of the Focus of Attention from Head Pose
In this paper, the recognition of the visual focus of attention (VFOA) of meeting participants (as defined by their eye gaze direction) from their head pose is addressed. To this ...
Jean-Marc Odobez, Sileye O. Ba
CVPR
2012
IEEE
9 years 7 months ago
Geodesic flow kernel for unsupervised domain adaptation
In real-world applications of visual recognition, many factors—such as pose, illumination, or image quality—can cause a significant mismatch between the source domain on whic...
Boqing Gong, Yuan Shi, Fei Sha, Kristen Grauman
ICVS
2001
Springer
11 years 9 months ago
Adapting Object Recognition across Domains: A Demonstration
High-level vision systems use object, scene or domain specific knowledge to interpret images. Unfortunately, this knowledge has to be acquired for every domain. This makes it diffi...
Bruce A. Draper, Ulrike Ahlrichs, Dietrich Paulus
ACCV
2010
Springer
11 years 11 days ago
Unsupervised Selective Transfer Learning for Object Recognition
Abstract. We propose a novel unsupervised transfer learning framework that utilises unlabelled auxiliary data to quantify and select the most relevant transferrable knowledge for r...
Wei-Shi Zheng, Shaogang Gong, Tao Xiang
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