CornerNet: Detecting Objects as Paired Keypoints

2018-08-03 · ECCV 2018 9 · Hei Law, Jia Deng

We propose CornerNet, a new approach to object detection where we detect an object bounding box as a pair of keypoints, the top-left corner and the bottom-right corner, using a single convolution neural network. By detecting objects as paired keypoints, we eliminate the need for designing a set of anchor boxes commonly used in prior single-stage detectors. In addition to our novel formulation, we introduce corner pooling, a new type of pooling layer that helps the network better localize corners. Experiments show that CornerNet achieves a 42.2% AP on MS COCO, outperforming all existing one-stage detectors.

📄 PDF Abstract BibTeX arXiv:1808.01244

Code (5)

princeton-vl/CornerNet 공식 구현 pytorch

PaddlePaddle/PaddleDetection paddle

egeonat/MS-CornerNet pytorch

gau-nernst/CenterNet pytorch

open-mmlab/mmdetection pytorch

Tasks

Objectobject-detection Object Detection

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