Abstract:.Self-supervised depth estimation has achieved remarkable results in sunny weather. However, in the foggy scenes, their performance is limited because of the low contrast and limited visibility caused by the fog. To address this problem, an end-to-end feature separation network for self-supervised depth estimation of fog images is proposed. We take paired clear and synthetic foggy images as input, separate the image information into interference information (illumination, fog, etc.) and invariant information (… Show more
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