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MTTrans: Cross-Domain Object Detection with Mean-Teacher Transformer. (arXiv:2205.01643v2 [cs.CV] UPDATED)
Aug. 17, 2022, 1:12 a.m. | Jinze Yu, Jiaming Liu, Xiaobao Wei, Haoyi Zhou, Yohei Nakata, Denis Gudovskiy, Tomoyuki Okuno, Jianxin Li, Kurt Keutzer, Shanghang Zhang
cs.CV updates on arXiv.org arxiv.org
Recently, DEtection TRansformer (DETR), an end-to-end object detection
pipeline, has achieved promising performance. However, it requires large-scale
labeled data and suffers from domain shift, especially when no labeled data is
available in the target domain. To solve this problem, we propose an end-to-end
cross-domain detection Transformer based on the mean teacher framework,
MTTrans, which can fully exploit unlabeled target domain data in object
detection training and transfer knowledge between domains via pseudo labels. We
further propose the comprehensive multi-level feature …
More from arxiv.org / cs.CV updates on arXiv.org
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