Enhancing Visual Recognition for Autonomous Driving in Real-world Degraded Conditions with Deep Channel Prior

The proposed Deep Channel Prior (DCP) and Unsupervised Feature Enhancement Module (UFEM) can effectively boost the performance of pre-trained visual recognition models in real-world degraded conditions, such as fog, low-light, and motion blur, by restoring latent content, removing artifacts, and modulating global feature correlations in an unsupervised manner.