|Trend||Dataset||Best Method||Paper title||Paper||Code||Compare|
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
#5 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.
#7 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.
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.
Per-pixel ground-truth depth data is challenging to acquire at scale.
#4 best model for Monocular Depth Estimation on KITTI Eigen split
Deployment of deep learning models in robotics as sensory information extractors can be a daunting task to handle, even using generic GPU cards.