Depth And Camera Motion

13 papers with code • 0 benchmarks • 1 datasets

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Most implemented papers

DeMoN: Depth and Motion Network for Learning Monocular Stereo

lmb-freiburg/demon CVPR 2017

In this paper we formulate structure from motion as a learning problem.

Unsupervised Learning of Depth and Ego-Motion from Video

tinghuiz/SfMLearner CVPR 2017

We present an unsupervised learning framework for the task of monocular depth and camera motion estimation from unstructured video sequences.

Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints

tensorflow/models CVPR 2018

We present a novel approach for unsupervised learning of depth and ego-motion from monocular video.

Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video

JiawangBian/sc_depth_pl NeurIPS 2019

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.

Learning Depth from Monocular Videos using Direct Methods

MightyChaos/LKVOLearner CVPR 2018

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

Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction

Huangying-Zhan/Depth-VO-Feat CVPR 2018

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.

BA-Net: Dense Bundle Adjustment Network

frobelbest/BANet 13 Jun 2018

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.

DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency

vt-vl-lab/DF-Net ECCV 2018

We present an unsupervised learning framework for simultaneously training single-view depth prediction and optical flow estimation models using unlabeled video sequences.

Sparse Representations for Object and Ego-motion Estimation in Dynamic Scenes

hkashyap/SparseMotion 9 Mar 2019

Dynamic scenes that contain both object motion and egomotion are a challenge for monocular visual odometry (VO).