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• W3113117059 abstract "The Feature Pyramid Network (FPN) presents a remarkable approach to alleviate the scale variance in object representation by performing instance-level assignments. Nevertheless, this strategy ignores the distinct characteristics of different sub-regions in an instance. To this end, we propose a fine-grained dynamic head to conditionally select a pixel-level combination of FPN features from different scales for each instance, which further releases the ability of multi-scale feature representation. Moreover, we design a spatial gate with the new activation function to reduce computational complexity dramatically through spatially sparse convolutions. Extensive experiments demonstrate the effectiveness and efficiency of the proposed method on several state-of-the-art detection benchmarks. Code is available at https://github.com/StevenGrove/DynamicHead." @default.
• W3113117059 created "2020-12-21" @default.
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• W3113117059 date "2020-12-07" @default.
• W3113117059 modified "2023-10-18" @default.
• W3113117059 title "Fine-Grained Dynamic Head for Object Detection" @default.
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• W3113117059 doi "https://doi.org/10.48550/arxiv.2012.03519" @default.
• W3113117059 hasPublicationYear "2020" @default.
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