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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 101–110 of 233 papers

TitleStatusHype
Accurate 6D Object Pose Estimation by Pose Conditioned Mesh Reconstruction—0
6D-ViT: Category-Level 6D Object Pose Estimation via Transformer-based Instance Representation Learning—0
6D Object Pose Estimation using Keypoints and Part Affinity Fields—0
KDFNet: Learning Keypoint Distance Field for 6D Object Pose Estimation—0
iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects—0
Investigations on Output Parameterizations of Neural Networks for Single Shot 6D Object Pose Estimation—0
Object Pose Estimation in Robotics Revisited—0
Instance- and Category-level 6D Object Pose Estimation—0
Improving 6D Pose Estimation of Objects in Clutter via Physics-aware Monte Carlo Tree Search—0
Improving 6D Object Pose Estimation of metallic Household and Industry Objects—0
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