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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 81–90 of 233 papers

TitleStatusHype
Model-Based Underwater 6D Pose Estimation from RGB—0
MSDA: Monocular Self-supervised Domain Adaptation for 6D Object Pose Estimation—0
3D Neural Embedding Likelihood: Probabilistic Inverse Graphics for Robust 6D Pose EstimationCode1
Collision-aware In-hand 6D Object Pose Estimation using Multiple Vision-based Tactile SensorsCode0
Learning Symmetry-Aware Geometry Correspondences for 6D Object Pose EstimationCode1
Center-Based Decoupled Point-cloud Registration for 6D Object Pose Estimation—0
SMOC-Net: Leveraging Camera Pose for Self-Supervised Monocular Object Pose Estimation—0
TexPose: Neural Texture Learning for Self-Supervised 6D Object Pose Estimation—0
Context-aware 6D Pose Estimation of Known Objects using RGB-D data—0
Category-Level 6D Object Pose Estimation with Flexible Vector-Based Rotation Representation—0
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