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Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection
[article]
2020
arXiv
pre-print
Neural Architecture Search (NAS) has achieved great success in image classification task. Some recent works have managed to explore the automatic design of efficient backbone or feature fusion layer for object detection. However, these methods focus on searching only one certain component of object detector while leaving others manually designed. We identify the inconsistency between searched component and manually designed ones would withhold the detector of stronger performance. To this end,
arXiv:2003.11818v1
fatcat:udwiiu4s2nchtblhxjqdauflk4