1k citations · 8k across the 112 of their papers we have counts for
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cs.CV2015★ 116 cited
PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions
Michael Figurnov, Aijan Ibraimova, Dmitry Vetrov +1
We propose a novel approach to reduce the computational cost of evaluation of convolutional neural networks, a factor that has hindered their deployment in low-power devices such a…
cs.CV2015★ 747 cited
Deep Convolutional Inverse Graphics Network
Tejas D. Kulkarni, Will Whitney, Pushmeet Kohli +1
This paper presents the Deep Convolution Inverse Graphics Network (DC-IGN), a model that learns an interpretable representation of images. This representation is disentangled with…