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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 131–140 of 233 papers

TitleStatusHype
Collision-aware In-hand 6D Object Pose Estimation using Multiple Vision-based Tactile SensorsCode0
SMOC-Net: Leveraging Camera Pose for Self-Supervised Monocular Object Pose Estimation—0
Center-Based Decoupled Point-cloud Registration for 6D 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
Review on 6D Object Pose Estimation with the focus on Indoor Scene Understanding—0
LocPoseNet: Robust Location Prior for Unseen Object Pose Estimation—0
A mixed-reality dataset for category-level 6D pose and size estimation of hand-occluded containers—0
Towards real-time 6D pose estimation of objects in single-view cone-beam X-ray—0
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