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We present an approach which takes advantage of both structure and semantics for unsupervised monocular learning of depth and ego-motion.
Models and examples built with TensorFlow
#15 best model for Monocular Depth Estimation on KITTI Eigen split
We present a novel approach for unsupervised learning of depth and ego-motion from monocular video.
Learning based methods have shown very promising results for the task of depth estimation in single images.
#9 best model for Monocular Depth Estimation on KITTI Eigen split
This paper addresses the problem of estimating the depth map of a scene given a single RGB image.
Per-pixel ground-truth depth data is challenging to acquire at scale.
#7 best model for Monocular Depth Estimation on KITTI Eigen split
Despite the progress on monocular depth estimation in recent years, we show that the gap between monocular and stereo depth accuracy remains large$-$a particularly relevant result due to the prevalent reliance upon monocular cameras by vehicles that are expected to be self-driving.
The spatial pyramid pooling module takes advantage of the capacity of global context information by aggregating context in different scales and locations to form a cost volume.
Deployment of deep learning models in robotics as sensory information extractors can be a daunting task to handle, even using generic GPU cards.