337 citations · 418 across the 16 of their papers we have counts for
3 papers · 1 filter
C3DPO: Canonical 3D Pose Networks for Non-Rigid Structure From Motion
David Novotny, Nikhila Ravi, Benjamin Graham +2
We propose C3DPO, a method for extracting 3D models of deformable objects from 2D keypoint annotations in unconstrained images. We do so by learning a deep network that reconstruct…
And the Bit Goes Down: Revisiting the Quantization of Neural Networks
Pierre Stock, Armand Joulin, Rémi Gribonval +2
In this paper, we address the problem of reducing the memory footprint of convolutional network architectures. We introduce a vector quantization method that aims at preserving the…
Equi-normalization of Neural Networks
Pierre Stock, Benjamin Graham, Rémi Gribonval +1
Modern neural networks are over-parametrized. In particular, each rectified linear hidden unit can be modified by a multiplicative factor by adjusting input and output weights, wit…