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Learning Local Image Descriptors with Deep Siamese and Triplet Convolutional Networks by Minimising Global Loss Functions
Vijay Kumar B G, Gustavo Carneiro, Ian Reid
Recent innovations in training deep convolutional neural network (ConvNet) models have motivated the design of new methods to automatically learn local image descriptors. The lates…
Competitive Multi-scale Convolution
Zhibin Liao, Gustavo Carneiro
In this paper, we introduce a new deep convolutional neural network (ConvNet) module that promotes competition among a set of multi-scale convolutional filters. This new module is…
On the Importance of Normalisation Layers in Deep Learning with Piecewise Linear Activation Units
Zhibin Liao, Gustavo Carneiro
Deep feedforward neural networks with piecewise linear activations are currently producing the state-of-the-art results in several public datasets. The combination of deep learning…
Robust Optimization for Deep Regression
Vasileios Belagiannis, Christian Rupprecht, Gustavo Carneiro +1
Convolutional Neural Networks (ConvNets) have successfully contributed to improve the accuracy of regression-based methods for computer vision tasks such as human pose estimation,…