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ICCV
2011
IEEE
12 years 7 months ago
Adaptive Deconvolutional Networks for Mid and High Level Feature Learning
We present a hierarchical model that learns image decompositions via alternating layers of convolutional sparse coding and max pooling. When trained on natural images, the layers ...
Matthew D. Zeiler, Graham W. Taylor, Rob Fergus
GRAPHICSINTERFACE
2004
13 years 9 months ago
Object Representation using 1D Displacement Mapping
In this paper, we propose a new method for rendering image-based objects. An object is decomposed into a set of 1D displacement textures in a preprocessing stage. During rendering...
Yi Xu, Yee-Hong Yang
IEEECGIV
2006
IEEE
14 years 1 months ago
Synthesizing Free-Viewpoint Images from Multiple View Videos in Soccer Stadium
We propose a new method for synthesizing freeviewpoint images from multiple view videos in soccer stadium. The previous method[1] can synthesize virtual viewpoint images at only i...
Kunihiko Hayashi, Hideo Saito
PAMI
2011
13 years 2 months ago
Coded Strobing Photography: Compressive Sensing of High Speed Periodic Videos
—We show that, via temporal modulation, one can observe and capture a high-speed periodic video well beyond the abilities of a low-frame-rate camera. By strobing the exposure wit...
Ashok Veeraraghavan, Dikpal Reddy, Ramesh Raskar
NIPS
2007
13 years 9 months ago
Sparse Feature Learning for Deep Belief Networks
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun