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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…
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…
CRF Learning with CNN Features for Image Segmentation
Fayao Liu, Guosheng Lin, Chunhua Shen
Conditional Random Rields (CRF) have been widely applied in image segmentations. While most studies rely on hand-crafted features, we here propose to exploit a pre-trained large co…
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…