Depth And Camera Motion
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Greatest papers with code
Unsupervised Monocular Depth and Ego-motion Learning with Structure and Semantics
We present an approach which takes advantage of both structure and semantics for unsupervised monocular learning of depth and ego-motion.
Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos
Models and examples built with TensorFlow
#16 best model for
Monocular Depth Estimation
on KITTI Eigen split
Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints
CVPR 2018
• tensorflow/models
• 
We present a novel approach for unsupervised learning of depth and ego-motion from monocular video.
Unsupervised Learning of Depth and Ego-Motion from Video
CVPR 2017
• tinghuiz/SfMLearner
•
We present an unsupervised learning framework for the task of monocular depth and camera motion estimation from unstructured video sequences.
Learning Depth from Monocular Videos using Direct Methods
The ability to predict depth from a single image - using recent advances in CNNs - is of increasing interest to the vision community.
DeMoN: Depth and Motion Network for Learning Monocular Stereo
CVPR 2017
• lmb-freiburg/demon
•
In this paper we formulate structure from motion as a learning problem.
DeMoN: Depth and Motion Network for Learning Monocular Stereo
CVPR 2017
• lmb-freiburg/demon
•
In this paper we formulate structure from motion as a learning problem.
Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video
NeurIPS 2019
• JiawangBian/SC-SfMLearner-Release
• 
To the best of our knowledge, this is the first work to show that deep networks trained using unlabelled monocular videos can predict globally scale-consistent camera trajectories over a long video sequence.
#10 best model for
Monocular Depth Estimation
on KITTI Eigen split
DEPTH AND CAMERA MOTION MONOCULAR DEPTH ESTIMATION VISUAL ODOMETRY
Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction
CVPR 2018
• Huangying-Zhan/Depth-VO-Feat
• 
Despite learning based methods showing promising results in single view depth estimation and visual odometry, most existing approaches treat the tasks in a supervised manner.
DEPTH AND CAMERA MOTION MONOCULAR DEPTH ESTIMATION VISUAL ODOMETRY
DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency
ECCV 2018
• vt-vl-lab/DF-Net
•
We present an unsupervised learning framework for simultaneously training single-view depth prediction and optical flow estimation models using unlabeled video sequences.