Semantic Stixels: Depth is not enough

  title={Semantic Stixels: Depth is not enough},
  author={L. Schneider and Marius Cordts and Timo Rehfeld and D. Pfeiffer and M. Enzweiler and U. Franke and M. Pollefeys and S. Roth},
  journal={2016 IEEE Intelligent Vehicles Symposium (IV)},
  • L. Schneider, Marius Cordts, +5 authors S. Roth
  • Published 2016
  • Computer Science
  • 2016 IEEE Intelligent Vehicles Symposium (IV)
  • In this paper we present Semantic Stixels, a novel vision-based scene model geared towards automated driving. Our model jointly infers the geometric and semantic layout of a scene and provides a compact yet rich abstraction of both cues using Stixels as primitive elements. Geometric information is incorporated into our model in terms of pixel-level disparity maps derived from stereo vision. For semantics, we leverage a modern deep learning-based scene labeling approach that provides an object… CONTINUE READING
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