Deep Learning Powered Defect Detection and Temporal Localization in CCTV Pipeline Videos

Automatic vision-based sewer inspection plays a vital role of sewage system in a modern city. Recent advances focus on modelling a deep learning-based methods to realize the sewer inspection system, benefiting from the capability of data-driven feature extraction. Although the acceptable performances of sewer defect classification are achieved, there is still a gap between the emerged methods and actual application scenarios. In this work we focus on implementing a lightweight CNN architecture with reduced number of computations using Ghost Module along with feature fusion technique and attention mechanisms.