Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

@article{Girshick2013RichFH,
  title={Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation},
  author={Ross B. Girshick and Jeff Donahue and Trevor Darrell and Jitendra Malik},
  journal={2014 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2013},
  pages={580-587}
}
Object detection performance, as measured on the canonical PASCAL VOC dataset, has plateaued in the last few years. [] Key Method Our approach combines two key insights: (1) one can apply high-capacity convolutional neural networks (CNNs) to bottom-up region proposals in order to localize and segment objects and (2) when labeled training data is scarce, supervised pre-training for an auxiliary task, followed by domain-specific fine-tuning, yields a significant performance boost.

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