  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.
