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• W3170979227 abstract "Weakly supervised object detection (WSOD) has recently attracted much attention. However, the method, performance and speed gaps between WSOD and fully supervised detection prevent WSOD from being applied in real-world tasks. To bridge the gaps, this paper proposes a new framework, Salvage of Supervision (SoS), with the key idea being to harness every potentially useful supervisory signal in WSOD: the weak image-level labels, the pseudo-labels, and the power of semi-supervised object detection. This paper shows that each type of supervisory signal brings in notable improvements, outperforms existing WSOD methods (which mainly use only the weak labels) by large margins. The proposed SoS-WSOD method achieves 64.4 $mtext{AP}_{50}$ on VOC2007, 61.9 $mtext{AP}_{50}$ on VOC2012 and 16.4 $mtext{AP}_{50:95}$ on MS-COCO, and also has fast inference speed. Ablations and visualization further verify the effectiveness of SoS." @default.
• W3170979227 created "2021-06-22" @default.
• W3170979227 creator A5026012846 @default.
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• W3170979227 date "2021-06-08" @default.
• W3170979227 modified "2023-09-27" @default.
• W3170979227 title "Salvage of Supervision in Weakly Supervised Detection." @default.
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