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Greatest papers with code

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.

DEPTH AND CAMERA MOTION

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.

DEPTH AND CAMERA MOTION MOTION ESTIMATION POSE ESTIMATION

Learning Depth from Monocular Videos using Direct Methods

CVPR 2018 yzcjtr/GeoNet

The ability to predict depth from a single image - using recent advances in CNNs - is of increasing interest to the vision community.

DEPTH AND CAMERA MOTION VISUAL ODOMETRY

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.

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

BA-Net: Dense Bundle Adjustment Network

13 Jun 2018frobelbest/BANet

The network first generates several basis depth maps according to the input image and optimizes the final depth as a linear combination of these basis depth maps via feature-metric BA.

DEPTH AND CAMERA MOTION STRUCTURE FROM MOTION

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.

DEPTH AND CAMERA MOTION OPTICAL FLOW ESTIMATION

Unsupervised Learning of Depth, Optical Flow and Pose with Occlusion from 3D Geometry

arXiv 2020 guangmingw/DOPlearning

In the occluded region, as depth and camera motion can provide more reliable motion estimation, they can be used to instruct unsupervised learning of optical flow.

AUTONOMOUS DRIVING DEPTH AND CAMERA MOTION MONOCULAR DEPTH ESTIMATION MOTION ESTIMATION OPTICAL FLOW ESTIMATION