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» A Conditional Random Field for Multiple-Instance Learning
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ECCV
2006
Springer
14 years 9 months ago
Learning and Incorporating Top-Down Cues in Image Segmentation
Abstract. Bottom-up approaches, which rely mainly on continuity principles, are often insufficient to form accurate segments in natural images. In order to improve performance, rec...
Xuming He, Richard S. Zemel, Debajyoti Ray
ECCV
2006
Springer
14 years 9 months ago
Learning to Combine Bottom-Up and Top-Down Segmentation
Bottom-up segmentation based only on low-level cues is a notoriously difficult problem. This difficulty has lead to recent top-down segmentation algorithms that are based on class-...
Anat Levin, Yair Weiss
CVPR
2012
IEEE
11 years 10 months ago
Top-down visual saliency via joint CRF and dictionary learning
Top-down visual saliency facilities object localization by providing a discriminative representation of target objects and a probability map for reducing the search space. In this...
Jimei Yang, Ming-Hsuan Yang
CVPR
2007
IEEE
14 years 9 months ago
Learning to Detect A Salient Object
We study visual attention by detecting a salient object in an input image. We formulate salient object detection as an image segmentation problem, where we separate the salient obj...
Tie Liu, Jian Sun, Nanning Zheng, Xiaoou Tang, Heu...
CVPR
2010
IEEE
14 years 3 months ago
Learning to Recognize Shadows in Monochromatic Natural Images
This paper addresses the problem of recognizing shadows from monochromatic natural images. Without chromatic information, shadow classification is very challenging because the in...
Jiejie Zhu, Kegan Samuel, Syed Zain Masood, Marsha...