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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…
gSLICr: SLIC superpixels at over 250Hz
Carl Yuheng Ren, Victor Adrian Prisacariu, Ian D Reid
We introduce a parallel GPU implementation of the Simple Linear Iterative Clustering (SLIC) superpixel segmentation. Using a single graphic card, our implementation achieves speedu…
Deeply Learning the Messages in Message Passing Inference
Guosheng Lin, Chunhua Shen, Ian Reid +1
Deep structured output learning shows great promise in tasks like semantic image segmentation. We proffer a new, efficient deep structured model learning scheme, in which we show h…
MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking
Laura Leal-Taixé, Anton Milan, Ian Reid +2
In the recent past, the computer vision community has developed centralized benchmarks for the performance evaluation of a variety of tasks, including generic object and pedestrian…
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…
Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields
Fayao Liu, Chunhua Shen, Guosheng Lin +1
In this article, we tackle the problem of depth estimation from single monocular images. Compared with depth estimation using multiple images such as stereo depth perception, depth…