An Efficient Shared Multi-Class Detection Cascade
By Philipp Zehnder, Esther Koller-Meier, Luc Van Gool. 2008
19 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition, Media Technology
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
- Piotr Doll'ar
- Lorenzo Torresani
- Christoph H. Lampert
- Rodrigo Benenson
- Bernt Schiele
- Juergen Gall
- Cordelia Schmid
- Mykhaylo Andriluka
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Bernt Schiele
- Trevor Darrell
- Xiaogang Wang
- Jitendra Malik
- Andrew Zisserman
- Dacheng Tao
- Ming-Hsuan Yang
In Media Technology
- Bernt Schiele
- Rodrigo Benenson
- Lorenzo Torresani
- Jan Hendrik Hosang
- Stefan Harmeling
- Hannes Nickisch
- Martin Szummer
- Christoph H. Lampert
Citations in the corpus
- What Makes for Effective Detection Proposals? (2015, background): “The key distinction between traditional cascades and proposal methods is that the latter is required to generalise beyond object classes observed during training.”
- Efficient Object Category Recognition Using Classemes (2010, background): “[27] build a classifier cascade which encourages feature sharing, but again requires the set of classes to be predefined, as is true for Griffin and Perona [7] and Torralba et al.”
- Learning to detect unseen object classes by between-class attribute transfer (2009, background): “Combinations of both approaches are also possible [39].”
- Attribute-Based Classification for Zero-Shot Visual Object Categorization (background): “Combinations of both approaches are also possible [25].”