An empirical study of context in object detection

@article{Divvala2009AnES,
  title={An empirical study of context in object detection},
  author={Santosh Kumar Divvala and Derek Hoiem and James Hays and Alexei A. Efros and Martial Hebert},
  journal={2009 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2009},
  pages={1271-1278}
}
This paper presents an empirical evaluation of the role of context in a contemporary, challenging object detection task - the PASCAL VOC 2008. Previous experiments with context have mostly been done on home-grown datasets, often with non-standard baselines, making it difficult to isolate the contribution of contextual information. In this work, we present our analysis on a standard dataset, using top-performing local appearance detectors as baseline. We evaluate several different sources of… CONTINUE READING

Figures, Tables, and Topics from this paper.

References

Publications referenced by this paper.
SHOWING 1-10 OF 40 REFERENCES

The PASCAL Visual Object Classes Challenge

VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Names and faces in the news

VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL

A discriminatively trained, multiscale, deformable part model

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition
  • 2008
VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL

IM2GPS: estimating geographic information from a single image

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition
  • 2008
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Recovering Occlusion Boundaries from a Single Image

  • 2007 IEEE 11th International Conference on Computer Vision
  • 2007
VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL

Using Segmentation to Verify Object Hypotheses

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition
  • 2007
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Recovering Surface Layout from an Image

  • International Journal of Computer Vision
  • 2006
VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL

On the semantics of a glance at a scene

VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Using contours to detect and localize junctions in natural images

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition
  • 2008
VIEW 3 EXCERPTS
HIGHLY INFLUENTIAL

Similar Papers

Loading similar papers…