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- W4313139298 abstract "Open- vocabulary object detection aims to detect novel object categories beyond the training set. The advanced open- vocabulary two-stage detectors employ instance-level visual-to- visual knowledge distillation to align the visual space of the detector with the semantic space of the Pre-trained Visual-Language Model (PVLM). However, in the more efficient one-stage detector, the absence of class-agnostic object proposals hinders the knowledge distil-lation on unseen objects, leading to severe performance degradation. In this paper, we propose a hierarchical visual-language knowledge distillation method, i.e., Hi-erKD, for open-vocabulary one-stage detection. Specifi-cally, a global-level knowledge distillation is explored to transfer the knowledge of unseen categories from the PVLM to the detector. Moreover, we combine the proposed global-level knowledge distillation and the common instance-level knowledge distillation to learn the knowledge of seen and unseen categories simultaneously. Extensive experiments on MS-COCO show that our method significantly surpasses the previous best one-stage detector with 11.9% and 6.7% AP50 gains under the zero-shot detection and generalized zero-shot detection settings, and reduces the AP <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>50</inf> performance gap from 14% to 7.3% compared to the best two-stage detector. Code will be released at this url <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>1</sup> <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>1</sup> https://qithub.com/menqqiDyanqqe/HierKD." @default.
- W4313139298 created "2023-01-06" @default.
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- W4313139298 date "2022-06-01" @default.
- W4313139298 modified "2023-09-26" @default.
- W4313139298 title "Open-Vocabulary One-Stage Detection with Hierarchical Visual-Language Knowledge Distillation" @default.
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- W4313139298 doi "https://doi.org/10.1109/cvpr52688.2022.01368" @default.
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