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arXiv · 2107.00818

1st Place Solutions for UG2+ Challenge 2021 -- (Semi-)supervised Face detection in the low light condition

Pengcheng Wang·Lingqiao Ji·Zhilong Ji·Yuan Gao·Xiao Liu
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Abstract

In this technical report, we briefly introduce the solution of our team "TAL-ai" for (Semi-) supervised Face detection in the low light condition in UG2+ Challenge in CVPR 2021. By conducting several experiments with popular image enhancement methods and image transfer methods, we pulled the low light image and the normal image to a more closer domain. And it is observed that using these data to training can achieve better performance. We also adapt several popular object detection frameworks, e.g., DetectoRS, Cascade-RCNN, and large backbone like Swin-transformer. Finally, we ensemble several models which achieved mAP 74.89 on the testing set, ranking 1st on the final leaderboard.

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Pengcheng Wang, Lingqiao Ji, Zhilong Ji, Yuan Gao, Xiao Liu. 2021-07-02. 1st Place Solutions for UG2+ Challenge 2021 -- (Semi-)supervised Face detection in the low light condition. https://arxiv.org/abs/2107.00818

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