Neural Architecture Search
Hit-Detector
Introduced by Guo et al. in Hit-Detector: Hierarchical Trinity Architecture Search for Object DetectionHit-Detector is a neural architectures search algorithm that simultaneously searches all components of an object detector in an end-to-end manner. It is a hierarchical approach to mine the proper subsearch space from the large volume of operation candidates. It consists of two main procedures. First, given a large search space containing all the operation candidates, we screen out the customized sub search space suitable for each part of detector with the help of group sparsity regularization. Secondly, we search the architectures for each part within the corresponding sub search space by adopting the differentiable manner.
Source: Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection
Papers
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Usage Over Time
Components
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| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
