11 citations · 11 across the 1 of their papers we have counts for
7 papers
Lightweight Multi-View 3D Pose Estimation through Camera-Disentangled Representation
Edoardo Remelli, Shangchen Han, Sina Honari +2
We present a lightweight solution to recover 3D pose from multi-view images captured with spatially calibrated cameras. Building upon recent advances in interpretable representatio…
U-Net Fixed-Point Quantization for Medical Image Segmentation
MohammadHossein AskariHemmat, Sina Honari, Lucas Rouhier +4
Model quantization is leveraged to reduce the memory consumption and the computation time of deep neural networks. This is achieved by representing weights and activations with a l…
On Adversarial Mixup Resynthesis
Christopher Beckham, Sina Honari, Vikas Verma +5
In this paper, we explore new approaches to combining information encoded within the learned representations of auto-encoders. We explore models that are capable of combining the a…
Distribution Matching Losses Can Hallucinate Features in Medical Image Translation
Joseph Paul Cohen, Margaux Luck, Sina Honari
This paper discusses how distribution matching losses, such as those used in CycleGAN, when used to synthesize medical images can lead to mis-diagnosis of medical conditions. It se…
Unsupervised Depth Estimation, 3D Face Rotation and Replacement
Joel Ruben Antony Moniz, Christopher Beckham, Simon Rajotte +2
We present an unsupervised approach for learning to estimate three dimensional (3D) facial structure from a single image while also predicting 3D viewpoint transformations that mat…
Learning to Generate Samples from Noise through Infusion Training
Florian Bordes, Sina Honari, Pascal Vincent
In this work, we investigate a novel training procedure to learn a generative model as the transition operator of a Markov chain, such that, when applied repeatedly on an unstructu…