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» Learning Object Shape: From Drawings to Images
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CVPR
2003
IEEE
16 years 8 months ago
Practical Non-parametric Density Estimation on a Transformation Group for Vision
It is now common practice in machine vision to define the variability in an object's appearance in a factored manner, as a combination of shape and texture transformations. I...
Erik G. Miller, Christophe Chefd'Hotel
VISUALIZATION
1996
IEEE
15 years 10 months ago
Illustrating Transparent Surfaces with Curvature-Directed Strokes
Transparency can be a useful device for simultaneously depicting multiple superimposed layers of information in a single image. However, in computer-generated pictures -as in phot...
Victoria Interrante, Henry Fuchs, Stephen M. Pizer
SSPR
2010
Springer
15 years 4 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...
WWW
2009
ACM
16 years 7 months ago
Learning to tag
Social tagging provides valuable and crucial information for large-scale web image retrieval. It is ontology-free and easy to obtain; however, irrelevant tags frequently appear, a...
Lei Wu, Linjun Yang, Nenghai Yu, Xian-Sheng Hua
ICCV
2011
IEEE
14 years 6 months ago
Human Action Recognition by Learning Bases of Action Attributes and Parts
In this work, we propose to use attributes and parts for recognizing human actions in still images. We define action attributes as the verbs that describe the properties of human...
Bangpeng Yao, Xiaoye Jiang, Aditya Khosla, Andy La...