Relative Pose from Deep Learned Depth and a Single Affine Correspondence (original) (raw)

DeMoN: Depth and Motion Network for Learning Monocular Stereo

Jonas Uhrig

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017

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DeepSFM: Structure From Motion Via Deep Bundle Adjustment

Xingkui Wei

ArXiv, 2020

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LFM-3D: Learnable Feature Matching Across Wide Baselines Using 3D Signals

Howard Zhou

arXiv (Cornell University), 2023

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Scene Coordinate and Correspondence Learning for Image-Based Localization

Mai Bui

2018

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GP2C: Geometric Projection Parameter Consensus for Joint 3D Pose and Focal Length Estimation in the Wild

Peter Roth

2019

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Learning Dense Correspondence from Synthetic Environments

Nuredin Habili

arXiv (Cornell University), 2022

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Learning Structure-from-Motion from Motion

Antoine Manzanera

Lecture Notes in Computer Science, 2019

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Distilled Visual and Robot Kinematics Embeddings for Metric Depth Estimation in Monocular Scene Reconstruction

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2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Single-Stage 6D Object Pose Estimation

Mathieu Salzmann

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020

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DiffPoseNet: Direct Differentiable Camera Pose Estimation

Gokul Hari

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

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Dual-Resolution Correspondence Networks

Shuda Li

ArXiv, 2020

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Softposit: Simultaneous pose and correspondence determination

Ramani Duraiswami

2002

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When Perspective Comes for Free: Improving Depth Prediction with Camera Pose Encoding

Shu Kong

ArXiv, 2020

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Atlas: End-to-End 3D Scene Reconstruction from Posed Images

Ayan sinha

Computer Vision – ECCV 2020, 2020

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C3DPO: Canonical 3D Pose Networks for Non-Rigid Structure From Motion

Nikhila Ravi

2019 IEEE/CVF International Conference on Computer Vision (ICCV)

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DeepIM: Deep Iterative Matching for 6D Pose Estimation

Gu Wang

International Journal of Computer Vision

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Graph-Based Consistent Matching for Structure-from-Motion

Runze Zhang

Computer Vision – ECCV 2016

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Deep Camera Pose Regression Using Pseudo-LiDAR

Alfonso Dela Cruz

2022

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Multi range real-time depth inference from a monocular stabilized footage using a fully convolutional neural network

Antoine Manzanera

2017 European Conference on Mobile Robots (ECMR)

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Learning Optical Flow, Depth, and Scene Flow Without Real-World Labels

Vitor Guizilini

IEEE robotics and automation letters, 2022

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6-DoF object pose from semantic keypoints

Kostas Daniilidis

2017 IEEE International Conference on Robotics and Automation (ICRA), 2017

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Matching RGB Images to CAD Models for Object Pose Estimation

Jana Kosecka

2018

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YCB-M: A Multi-Camera RGB-D Dataset for Object Recognition and 6DoF Pose Estimation

Martin Günther

2020 IEEE International Conference on Robotics and Automation (ICRA)

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UnDEMoN: Unsupervised Deep Network for Depth and Ego-Motion Estimation

Anima Majumder

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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GCNDepth: Self-supervised monocular depth estimation based on graph convolutional network

Hatem A . Rashwan

Neurocomputing, 2023

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Learning Local RGB-to-CAD Correspondences for Object Pose Estimation

Jana Kosecka

arXiv (Cornell University), 2018

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Generalised pose estimation using depth

Simon Hadfield

Proceedings, International Workshop on Sign, Gesture and Activity at ECCV 2010, 2010

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CNN Based Monocular Depth Estimation

Hima Valiveti

E3S Web of Conferences, 2021

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