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arXiv · 2012.13563

Implicit Feature Pyramid Network for Object Detection

Tiancai Wang·Xiangyu Zhang·Jian Sun
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Abstract

In this paper, we present an implicit feature pyramid network (i-FPN) for object detection. Existing FPNs stack several cross-scale blocks to obtain large receptive field. We propose to use an implicit function, recently introduced in deep equilibrium model (DEQ), to model the transformation of FPN. We develop a residual-like iteration to updates the hidden states efficiently. Experimental results on MS COCO dataset show that i-FPN can significantly boost detection performance compared to baseline detectors with ResNet-50-FPN: +3.4, +3.2, +3.5, +4.2, +3.2 mAP on RetinaNet, Faster-RCNN, FCOS, ATSS and AutoAssign, respectively.

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Tiancai Wang, Xiangyu Zhang, Jian Sun. 2020-12-25. Implicit Feature Pyramid Network for Object Detection. https://arxiv.org/abs/2012.13563

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