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7 papers · 2 filters
Fine-Grained Classification via Mixture of Deep Convolutional Neural Networks
ZongYuan Ge, Alex Bewley, Christopher McCool +3
We present a novel deep convolutional neural network (DCNN) system for fine-grained image classification, called a mixture of DCNNs (MixDCNN). The fine-grained image classification…
Fast detection of multiple objects in traffic scenes with a common detection framework
Qichang Hu, Sakrapee Paisitkriangkrai, Chunhua Shen +2
Traffic scene perception (TSP) aims to real-time extract accurate on-road environment information, which in- volves three phases: detection of objects of interest, recognition of d…
Dictionary Learning and Sparse Coding for Third-order Super-symmetric Tensors
Piotr Koniusz, Anoop Cherian
Super-symmetric tensors - a higher-order extension of scatter matrices - are becoming increasingly popular in machine learning and computer vision for modelling data statistics, co…
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…
Efficient SDP Inference for Fully-connected CRFs Based on Low-rank Decomposition
Peng Wang, Chunhua Shen, Anton van den Hengel
Conditional Random Fields (CRF) have been widely used in a variety of computer vision tasks. Conventional CRFs typically define edges on neighboring image pixels, resulting in a sp…
Efficient piecewise training of deep structured models for semantic segmentation
Guosheng Lin, Chunhua Shen, Anton van dan Hengel +1
Recent advances in semantic image segmentation have mostly been achieved by training deep convolutional neural networks (CNNs). We show how to improve semantic segmentation through…