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Titlebook: Computer Vision – ECCV 2022; 17th European Confer Shai Avidan,Gabriel Brostow,Tal Hassner Conference proceedings 2022 The Editor(s) (if app

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,Adaptive Co-teaching for Unsupervised Monocular Depth Estimation,ent, which effectively improves the ability of the student to jump out of the local minimum. Our method is shown to significantly benefit unsupervised depth estimation and sets new state of the art on both KITTI and Nuscenes datasets.
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Lidar Point Cloud Guided Monocular 3D Object Detection,3D object detection (LPCG). This framework is capable of either reducing the annotation costs or considerably boosting the detection accuracy without introducing extra annotation costs. Specifically, It generates pseudo labels from unlabeled LiDAR point clouds. Thanks to accurate LiDAR 3D measuremen
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,PanoFormer: Panorama Transformer for Indoor 360, Depth Estimation,ents demonstrate that our approach significantly outperforms the state-of-the-art (SOTA) methods. Furthermore, the proposed method can be effectively extended to solve semantic panorama segmentation, a similar pixel2pixel task.
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