Pixel-Level Encoding and Depth Layering for Instance-Level Semantic Labeling

@inproceedings{Uhrig2016PixelLevelEA,
  title={Pixel-Level Encoding and Depth Layering for Instance-Level Semantic Labeling},
  author={Jonas Uhrig and Marius Cordts and Uwe Franke and Thomas Brox},
  booktitle={German Conference on Pattern Recognition},
  year={2016}
}
Recent approaches for instance-aware semantic labeling have augmented convolutional neural networks (CNNs) with complex multi-task architectures or computationally expensive graphical models. We present a method that leverages a fully convolutional network (FCN) to predict semantic labels, depth and an instance-based encoding using each pixel’s direction towards its corresponding instance center. Subsequently, we apply low-level computer vision techniques to generate state-of-the-art instance… 

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