Label-Efficient Object Detection via Region Proposal Network Pre-Training

arXiv:2211.09022v2 Announce Type: replace
Abstract: Self-supervised pre-training, based on the pretext task of instance discrimination, has fueled the recent advance in label-efficient object detection. However, existing studies focus on pre-training only a feature extractor network to learn transferable representations for downstream detection tasks. This leads to the necessity of training multiple detection-specific modules from scratch in the fine-tuning phase. We argue that the region proposal network (RPN), a common detection-specific module, can additionally be pre-trained towards reducing the localization error …

abstract advance arxiv cs.cv detection discrimination feature focus instance leads learn multiple network pre-training studies tasks training type via