40 citations · 49 across the 8 of their papers we have counts for
8 papers
Toward fast and accurate human pose estimation via soft-gated skip connections
Adrian Bulat, Jean Kossaifi, Georgios Tzimiropoulos +1
This paper is on highly accurate and highly efficient human pose estimation. Recent works based on Fully Convolutional Networks (FCNs) have demonstrated excellent results for this…
Matrix and tensor decompositions for training binary neural networks
Adrian Bulat, Jean Kossaifi, Georgios Tzimiropoulos +1
This paper is on improving the training of binary neural networks in which both activations and weights are binary. While prior methods for neural network binarization binarize eac…
Improved training of binary networks for human pose estimation and image recognition
Adrian Bulat, Georgios Tzimiropoulos, Jean Kossaifi +1
Big neural networks trained on large datasets have advanced the state-of-the-art for a large variety of challenging problems, improving performance by a large margin. However, unde…
T-Net: Parametrizing Fully Convolutional Nets with a Single High-Order Tensor
Jean Kossaifi, Adrian Bulat, Georgios Tzimiropoulos +1
Recent findings indicate that over-parametrization, while crucial for successfully training deep neural networks, also introduces large amounts of redundancy. Tensor methods have t…
Features Extraction Based on an Origami Representation of 3D Landmarks
Juan Manuel Fernandez Montenegro, Mahdi Maktab Dar Oghaz, Athanasios Gkelias +2
Feature extraction analysis has been widely investigated during the last decades in computer vision community due to the large range of possible applications. Significant work has…
A CNN Cascade for Landmark Guided Semantic Part Segmentation
Aaron Jackson, Michel Valstar, Georgios Tzimiropoulos
This paper proposes a CNN cascade for semantic part segmentation guided by pose-specific information encoded in terms of a set of landmarks (or keypoints). There is large amount of…