3 accepted papers
Image dehazing, an important image restoration problem, aims to recover clear scene content from images degraded by atmospheric haze. Existing dehazing methods rely on observing the distribution of hazy images during training: supervised approaches typically depend on synthetic datasets, leading to …
Real-time image dehazmg is crucial for applications such as autonomous driving, surveillance, and remote sensing, where haze can significantly reduce visibility. However, many deep learning algorithms are hindered by large model sizes, making real-time processing difficult to achieve. Several fast a…
The utilization of generative adversarial networks (GANs) for image-to-image translation has undergone extensive scholarly exploration. Nonetheless, prevailing unidirectional image translation tasks remain intricate and computationally inefficient due to the employment of complex computational metho…