Fast Edge Detection Using Structured Forests

By Bindu M Nair. 2016

55 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Luc Van Gool
2. Xiang Bai
3. Alan L. Yuille
4. Trevor Darrell
5. Chunhua Shen
6. Dacheng Tao
7. Xinggang Wang
8. Xiaogang Wang

Citations in the corpus

• DeepContour: A deep convolutional feature learned by positive-sharing loss for contour detection (2015, methodology): “We take the computationally efficient structured forest [11, 12] as the contour versus non-contour classifier for our deep features, which achieves the-state-of-the-art result on the popular Berkeley Segmentation Dataset and Benchmark (BSDS500) [2].”
• Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review (2016, background): “The split function h(x, θ θ θ n ) is often chosen as a stump function for efficiency [139].”
• Cross-modal adaptation for RGB-D detection (2016, background): “Techniques for domain adaptation [10], [11] combine examples from a source domain with a small number of examples from the actual test environment, but require an expensive training step.”