Improving spatial codification in semantic segmentation

@article{Ventura2015ImprovingSC,
  title={Improving spatial codification in semantic segmentation},
  author={Carles Ventura and Xavier Gir{\'o} and Ver{\'o}nica Vilaplana and Kevin McGuinness and Ferran Marqu{\'e}s and Noel E. O'Connor},
  journal={2015 IEEE International Conference on Image Processing (ICIP)},
  year={2015},
  pages={3605-3609}
}
This paper explores novel approaches for improving the spatial codification for the pooling of local descriptors to solve the semantic segmentation problem. We propose to partition the image into three regions for each object to be described: Figure, Border and Ground. This partition aims at minimizing the influence of the image context on the object description and vice versa by introducing an intermediate zone around the object contour. Furthermore, we also propose a richer visual descriptor… CONTINUE READING
1
Twitter Mention

Similar Papers

Figures, Tables, and Topics from this paper.

References

Publications referenced by this paper.
SHOWING 1-10 OF 23 REFERENCES

Multiscale Combinatorial Grouping

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition
  • 2014
VIEW 9 EXCERPTS
HIGHLY INFLUENTIAL

The Visual Extent of an Object

  • International Journal of Computer Vision
  • 2011
VIEW 10 EXCERPTS
HIGHLY INFLUENTIAL

Composite Statistical Inference for Semantic Segmentation

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition
  • 2013
VIEW 1 EXCERPT

Discriminative Re-ranking of Diverse Segmentations

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition
  • 2013
VIEW 1 EXCERPT

CPMC: Automatic Object Segmentation Using Constrained Parametric Min-Cuts

  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2012
VIEW 3 EXCERPTS