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Unsupervised learning of clutter-resistant visual representations from natural videos 

Liao, Qianli; Leibo, Joel Z; Poggio, Tomaso (Center for Brains, Minds and Machines (CBMM), arXiv, 2015-04-27)
Populations of neurons in inferotemporal cortex (IT) maintain an explicit code for object identity that also tolerates transformations of object appearance e.g., position, scale, viewing angle [1, 2, 3]. Though the learning ...
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Semantic Part Segmentation using Compositional Model combining Shape and Appearance 

Wang, Jianyu; Yuille, Alan L. (Center for Brains, Minds and Machines (CBMM), arXiv, 2015-06-08)
In this paper, we study the problem of semantic part segmentation for animals. This is more challenging than standard object detection, object segmentation and pose estimation tasks because semantic parts of animals often ...
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Seeing is Worse than Believing: Reading People’s Minds Better than Computer-Vision Methods Recognize Actions 

Barbu, Andrei; Barrett, Daniel P.; Chen, Wei; Narayanaswamy, Siddharth; Xiong, Caiming; e.a. (2015-12-10)
We had human subjects perform a one-out-of-six class action recognition task from video stimuli while undergoing functional magnetic resonance imaging (fMRI). Support-vector machines (SVMs) were trained on the recovered ...

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AuthorBarbu, Andrei (1)Barrett, Daniel P. (1)Chen, Wei (1)Corso, Jason J. (1)Fellbaum, Christiane D. (1)Hanson, Catherine (1)Hanson, Stephen Jose (1)Helie, Sebastien (1)Leibo, Joel Z (1)Liao, Qianli (1)... View MoreSubject
Object Recognition (3)
Artificial Intelligence (2)Compositional Models (1)Computer vision (1)Machine Learning (1)Semantic Part Segmentation (1)Support-Vector Machines (SVMs) (1)Vision (1)... View MoreDate Issued
2015 (3)
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