Semantic Hierarchies for Visual Object Recognition

  title={Semantic Hierarchies for Visual Object Recognition},
  author={Marcin Marszalek and Cordelia Schmid},
  journal={2007 IEEE Conference on Computer Vision and Pattern Recognition},
In this paper we propose to use lexical semantic networks to extend the state-of-the-art object recognition techniques. We use the semantics of image labels to integrate prior knowledge about inter-class relationships into the visual appearance learning. We show how to build and train a semantic hierarchy of discriminative classifiers and how to use it to perform object detection. We evaluate how our approach influences the classification accuracy and speed on the Pascal VOC challenge 2006… CONTINUE READING
Highly Influential
This paper has highly influenced 16 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 444 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 181 extracted citations

445 Citations

Citations per Year
Semantic Scholar estimates that this publication has 445 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 19 references

The 2006 PASCAL visual object classes challenge

  • M. Everingham, L. V. Gool, C. Williams, A. Zisserman
  • In The PASCAL Visual Object Classes Challenge…
  • 2006
Highly Influential
4 Excerpts

Similar Papers

Loading similar papers…