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Teach-DETR: Better Training DETR with Teachers. (arXiv:2211.11953v2 [cs.CV] UPDATED)
Nov. 24, 2022, 7:17 a.m. | Linjiang Huang, Kaixin Lu, Guanglu Song, Liang Wang, Si Liu, Yu Liu, Hongsheng Li
cs.CV updates on arXiv.org arxiv.org
In this paper, we present a novel training scheme, namely Teach-DETR, to
learn better DETR-based detectors from versatile teacher detectors. We show
that the predicted boxes from teacher detectors are effective medium to
transfer knowledge of teacher detectors, which could be either RCNN-based or
DETR-based detectors, to train a more accurate and robust DETR model. This new
training scheme can easily incorporate the predicted boxes from multiple
teacher detectors, each of which provides parallel supervisions to the student
DETR. Our …
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