Researchers are exploring various methods for detecting road cracks using semantic segmentation models. Different approaches are being investigated, including the use of channel-space convolution, frequency feature aggregation, and attention mechanisms, as well as various architectures such as U-Net and its extensions. The goal of these efforts appears to be improving the accuracy and efficiency of crack detection in different infrastructure, including roads, bridges, and airport pavements.