{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/regularizing-nighttime-weirdness-efficient","title":"Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark","arxiv_id":"2108.03830","date":"2021-08-09","proceeding":"ICCV 2021 10","authors":["Kun Wang","Zhenyu Zhang","Zhiqiang Yan","Xiang Li","Baobei Xu","Jun Li","Jian Yang"],"abstract":"Monocular depth estimation aims at predicting depth from a single image or video. 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