A unified random field model based neural approach to pixel labeling problems in computer vision

In this paper, we establish a nexus between the Gibbs random field models and recurrent neural networks and present a unified neural network approach based on this to pixel labeling problems in computer vision. We also present a case study with photometric stereo problem for demonstrating the viability of the present approach.<
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