Video de-raining is of significant importance problem in computer vision as rain streaks adversely affect the visual quality of images and hinder subsequent vision-related tasks. Existing video de-raining methods still face challenges such as black shadows and loss of details. In this paper, we introduced a novel de-raining framework called STVDNet, which effectively solves the issues of black shadows and detail loss after de-raining. STVDNet utilizes a Spatial Detail Feature Extraction Module based on an auto-encoder to capture the spatial characteristics of the video. Additionally, we introd...
