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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 211–220 of 233 papers

TitleStatusHype
Model-Based Underwater 6D Pose Estimation from RGB—0
Monocular One-Shot Metric-Depth Alignment for RGB-Based Robot Grasping—0
MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models—0
MSDA: Monocular Self-supervised Domain Adaptation for 6D Object Pose Estimation—0
Multi-Modal 3D Mesh Reconstruction from Images and Text—0
Multistream ValidNet: Improving 6D Object Pose Estimation by Automatic Multistream Validation—0
Multi-View Keypoints for Reliable 6D Object Pose Estimation—0
NeRF-Feat: 6D Object Pose Estimation using Feature Rendering—0
NeRF-Pose: A First-Reconstruct-Then-Regress Approach for Weakly-supervised 6D Object Pose Estimation—0
Object Level Depth Reconstruction for Category Level 6D Object Pose Estimation From Monocular RGB Image—0
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