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

• URL: http://arxiv.org/abs/2107.00818v1
• Date: Fri, 2 Jul 2021 04:12:23 GMT
• Title: 1st Place Solutions for UG2+ Challenge 2021 -- (Semi-)supervised Face detection in the low light condition
• Authors: Pengcheng Wang, Lingqiao Ji, Zhilong Ji, Yuan Gao, Xiao Liu
• Abstract summary: "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. We ensemble several models which achieved mAP 74.89 on the testing set, ranking 1st on the final leaderboard.
• Score: 13.241328369629453
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• 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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