CF-YOLO: Cross Fusion YOLO for Object Detection in Adverse Weather with a High-quality Real Snow Dataset. (arXiv:2206.01381v1 [cs.CV])

Snow is one of the toughest adverse weather conditions for object detection
(OD). Currently, not only there is a lack of snowy OD datasets to train
cutting-edge detectors, but also these detectors have difficulties learning
latent information beneficial for detection in snow. To alleviate the two above
problems, we first establish a real-world snowy OD dataset, named RSOD.
Besides, we develop an unsupervised training strategy with a distinctive
activation function, called $Peak \ Act$, to quantitatively evaluate the effect
of …

arxiv cv dataset detection fusion quality snow weather yolo