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 encoder-decoder network and self-supervised learning


Depth Estimation Using Encoder-Decoder Networks and Self-Supervised Learning

#artificialintelligence

Modern autonomous mobile robots (including self-driving cars) require a strong understanding of their environment in order to operate safely and effectively. Comprehensive and accurate models of the surrounding environment are crucial for solving the challenges of autonomous operation. However, only a limited amount of information is perceived through the sensors which are limited regarding their capabilities, the field of view and the kind of data they provide. While sensors like LIDAR, Radar, Kinect provide 3D data including all spatial dimensions, cameras on the other hand only provide a 2D view of the surrounding. In the past, many attempts have been made to actually extract the 3D data out of 2D images coming from the camera.