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EMNLP
2008
14 years 11 months ago
Modeling Annotators: A Generative Approach to Learning from Annotator Rationales
A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one ex...
Omar Zaidan, Jason Eisner
CVPR
2007
IEEE
15 years 11 months ago
Simultaneous Detection and Segmentation of Pedestrians using Top-down and Bottom-up Processing
We present a method for the simultaneous detection and segmentation of people from static images. The proposed technique requires no manual segmentation during training, and explo...
Vinay Sharma, James W. Davis
TVCG
2010
183views more  TVCG 2010»
14 years 8 months ago
Exploration and Visualization of Segmentation Uncertainty using Shape and Appearance Prior Information
—We develop an interactive analysis and visualization tool for probabilistic segmentation in medical imaging. The originality of our approach is that the data exploration is guid...
Ahmed Saad, Ghassan Hamarneh, Torsten Möller
BMVC
2010
14 years 7 months ago
Localized fusion of Shape and Appearance features for 3D Human Pose Estimation
This paper presents a learning-based method for combining the shape and appearance feature types for 3D human pose estimation from single-view images. Our method is based on clust...
Suman Sedai, Mohammed Bennamoun, Du Q. Huynh
94
Voted
ICCV
2009
IEEE
16 years 2 months ago
Learning Deformable Action Templates from Crowded Videos
In this paper, we present a Deformable Action Template (DAT) model that is learnable from cluttered real-world videos with weak supervisions. In our generative model, an action ...
Benjamin Yao, Song-Chun Zhu