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6D Pose Estimation using RGB

6D Pose Estimation using RGB refers to the task of determining the six degree-of-freedom (6D) pose of an object in 3D space based on RGB images. This involves estimating the position and orientation of an object in a scene, and is a fundamental problem in computer vision and robotics. In this task, the goal is to estimate the 6D pose of an object given an RGB image of the object and the scene, which can be used for tasks such as robotic manipulation, augmented reality, and scene reconstruction.

( Image credit: Segmentation-driven 6D Object Pose Estimation )

Papers

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Showing 121–130 of 233 papers

TitleStatusHype
Hierarchical Graph Neural Networks for Proprioceptive 6D Pose Estimation of In-hand Objects—0
PoseMatcher: One-shot 6D Object Pose Estimation by Deep Feature MatchingCode0
Multi-View Keypoints for Reliable 6D Object Pose Estimation—0
6D Object Pose Estimation from Approximate 3D Models for Orbital Robotics—0
SOCS: Semantically-aware Object Coordinate Space for Category-Level 6D Object Pose Estimation under Large Shape Variations—0
Modular Quantization-Aware Training for 6D Object Pose EstimationCode0
BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objects—0
Open Challenges for Monocular Single-shot 6D Object Pose Estimation—0
MSDA: Monocular Self-supervised Domain Adaptation for 6D Object Pose Estimation—0
Model-Based Underwater 6D Pose Estimation from RGB—0
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