Synthesize Hazy/Foggy Images using Monodepth and Atmospheric Scattering Models

The recent era of deep learning and computer vision leads to the rapid development of autonomous driving technology where object detection plays an extremely important role. Various object detectors such as R-CNN family (R-CNN, Fast R-CNN, Faster R-CNN, Cascade R-CNN), YOLO series (YOLOv1-v4) have been proposed, and abundant driving object detection datasets including BDD100K, WAYMO, etc. are also available. However, there still exists a huge gap between academic research and realistic deployment. The performances of object detectors in practice usually drop despite being trained well with almost 99.99% accuracy during offline training. One of the most popular reasons for that unexpected incident is because domain shift problem.