Conditional Random Fields as Recurrent Neural Networks

Understand

Pixel-level labelling tasks, such as semantic segmentation, play a central role in image understanding.

• Recent approaches have attempted to harness the capabilities of deep learning techniques for image recognition to tackle pixel-level labelling tasks.
• One central issue in this methodology is the limited capacity of deep learning techniques to delineate visual objects.
• To solve this problem, we introduce a new form of convolutional neural network that combines the strengths of Convolutional Neural Networks (CNNs) and Conditional Random Fields (CRFs)-based probabilistic graphical modelling.