Matrix Nets: A New Deep Architecture for Object Detection

2019-08-13 · Abdullah Rashwan, Agastya Kalra, Pascal Poupart

We present Matrix Nets (xNets), a new deep architecture for object detection. xNets map objects with different sizes and aspect ratios into layers where the sizes and the aspect ratios of the objects within their layers are nearly uniform. Hence, xNets provide a scale and aspect ratio aware architecture. We leverage xNets to enhance key-points based object detection. Our architecture achieves mAP of 47.8 on MS COCO, which is higher than any other single-shot detector while using half the number of parameters and training 3x faster than the next best architecture.

📄 PDF Abstract BibTeX arXiv:1908.04646

Code (2)

arashwan/matrixnet pytorch

lizhe960118/CenterNet pytorch

Tasks

Objectobject-detection Object Detection

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