Multiple Component Learning for Object Detection

  title={Multiple Component Learning for Object Detection},
  author={Piotr Doll{\'a}r and Boris Babenko and Serge J. Belongie and Pietro Perona and Zhuowen Tu},
Object detection is one of the key problems in computer vision. In the last decade, discriminative learning approaches have proven effective in detecting rigid objects, achieving very low false positives rates. The field has also seen a resurgence of part-based recognition methods, with impressive results on highly articulated, diverse object categories. In this paper we propose a discriminative learning approach for detection that is inspired by part-based recognition approaches. Our method… CONTINUE READING
Highly Cited
This paper has 165 citations. REVIEW CITATIONS

8 Figures & Tables



Citations per Year

166 Citations

Semantic Scholar estimates that this publication has 166 citations based on the available data.

See our FAQ for additional information.