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Target-Relevant Knowledge Preservation for Multi-Source Domain Adaptive Object Detection
[article]
2022
arXiv
pre-print
Domain adaptive object detection (DAOD) is a promising way to alleviate performance drop of detectors in new scenes. Albeit great effort made in single source domain adaptation, a more generalized task with multiple source domains remains not being well explored, due to knowledge degradation during their combination. To address this issue, we propose a novel approach, namely target-relevant knowledge preservation (TRKP), to unsupervised multi-source DAOD. Specifically, TRKP adopts the
arXiv:2204.07964v1
fatcat:f5wogrhjargn7fbg45wdboco4q