Methods › General › Neural Architecture Search › Hit-Detector
Hit-Detector
Introduced by Jianyuan Guo et al. in Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Hit-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.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
-
Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection 26 Mar 2020 · 1 repository · arXiv:2003.11818
Tasks archive 2025-07-28
6 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Image Classification | 1 |
| Neural Architecture Search | 1 |
| Object | 1 |
| Object Detection | 1 |
| image-classification | 1 |
| object-detection | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections