Efficient Likelihood Learning of a Generic CNN-CRF Model for Semantic Segmentation

alexander kirillov
alexander kirillov
walter forkel
walter forkel
anatoly zelenin
anatoly zelenin

CoRR, Volume abs/1511.05067, 2015.

被引用14|浏览42
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摘要

Deep Models, such as Convolutional Neural Networks (CNNs), are omnipresent in computer vision, as well as, structured models, such as Conditional Random Fields (CRFs). Combining them brings many advantages, foremost the ability to in-cooperate prior knowledge into CNNs, e.g. by explicitly modelling the dependencies between output variab...更多

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