𝗗𝗮𝘆-𝟰𝟭𝟵 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗔𝗻 𝗘𝗻𝗱-𝘁𝗼-𝗘𝗻𝗱 𝗖𝗮𝘀𝗰𝗮𝗱𝗲𝗱 𝗜𝗺𝗮𝗴𝗲 𝗗𝗲𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗢𝗯𝗷𝗲𝗰𝘁 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝗡𝗲𝘂𝗿𝗮𝗹 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 𝗯𝘆 𝗞𝗮𝗿𝗹𝘀𝗿𝘂𝗵𝗲 𝗜𝗻𝘀𝘁𝗶𝘁𝘂𝘁𝗲 𝗼𝗳 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 Follow me for a similar post: Ashish Patel ------------------------------------------------------------------- 𝗜𝗻𝘁𝗲𝗿𝗲𝘀𝘁𝗶𝗻𝗴 𝗙𝗮𝗰𝘁𝘀 : 🔸 This paper is published arxiv2022. 🔸 what is Image Deraining? The goal of single image de- raining algorithms is to generate sharp images from a rainy image input. Image deraining can potentially benefit both the human visual perception quality of images, and many computer vision applications, such as outdoor surveillance systems and intelligent vehicles. ------------------------------------------------------------------- 𝗜𝗠𝗣𝗢𝗥𝗧𝗔𝗡𝗖𝗘 🔸 While the deep learning-based image deraining methods have made great progress in recent years, there are two major shortcomings in their application in real-world situations. 🔸 Firstly, the gap between the low-level vision task represented by rain removal and the high-level vision task represented by object detection is significant, and the low-level vision task can hardly contribute to the high-level vision task. Secondly, the quality of the deraining dataset needs to be improved. 🔸 In fact, the rain lines in many baselines have a large gap with the real rain lines, and the resolution of the deraining dataset images is generally not ideally. Meanwhile, there are few common datasets for both the low-level vision task and the high-level vision task. 🔸 In this paper, we explore the combination of the low-level vision task with the high-level vision task. Specifically, we propose an end-to-end object detection network for reducing the impact of rainfall, which consists of two cascaded networks, an improved image deraining network and an object detection network, respectively. 🔸 We also design the components of the loss function to accommodate the characteristics of the different sub-networks. 🔸 We then propose a dataset based on the KITTI dataset for rainfall removal and object detection, on which our network surpasses the state-of-the-art with a significant improvement in metrics. 🔸 Besides, our proposed network is measured on driving videos collected by self-driving vehicles and shows positive results for rain removal and object detection. #deeplearning #objectdetection #computervision #artificialintelligence
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