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» Learning Features by Contrasting Natural Images with Noise
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NIPS
2008
13 years 8 months ago
Natural Image Denoising with Convolutional Networks
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
Viren Jain, H. Sebastian Seung
CVPR
2007
IEEE
14 years 8 months ago
What makes a good model of natural images?
Many low-level vision algorithms assume a prior probability over images, and there has been great interest in trying to learn this prior from examples. Since images are very non G...
Yair Weiss, William T. Freeman
ICCV
2007
IEEE
14 years 8 months ago
Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes
We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
CVPR
2010
IEEE
14 years 2 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...
CVPR
2003
IEEE
14 years 8 months ago
Learning Affinity Functions for Image Segmentation: Combining Patch-based and Gradient-based Approaches
This paper studies the problem of combining region and boundary cues for natural image segmentation. We employ a large database of manually segmented images in order to learn an o...
Charless Fowlkes, David R. Martin, Jitendra Malik