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03/30/2021
Exploiting Invariance in Training Deep Neural Networks
Inspired by two basic mechanisms in animal visual systems, we introduce ...
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05/28/2019
Network Deconvolution
Convolution is a central operation in Convolutional Neural Networks (CNN...
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03/18/2019
EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras
We present the first event-based learning approach for motion segmentati...
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09/23/2018
Unsupervised Learning of Dense Optical Flow and Depth from Sparse Event Data
In this work we present unsupervised learning of depth and motion from s...
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07/02/2018
Evenly Cascaded Convolutional Networks
In this paper we demonstrate that state-of-the-art convolutional neural ...
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08/02/2017
On the Importance of Consistency in Training Deep Neural Networks
We explain that the difficulties of training deep neural networks come f...
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05/09/2016
LightNet: A Versatile, Standalone Matlab-based Environment for Deep Learning
LightNet is a lightweight, versatile and purely Matlab-based deep learni...
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01/29/2016
What Can I Do Around Here? Deep Functional Scene Understanding for Cognitive Robots
For robots that have the capability to interact with the physical enviro...
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05/17/2013
Sparse Norm Filtering
Optimization-based filtering smoothes an image by minimizing a fidelity ...
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05/20/2012