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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 41–50 of 233 papers

TitleStatusHype
GenFlow: Generalizable Recurrent Flow for 6D Pose Refinement of Novel Objects—0
GS-Pose: Generalizable Segmentation-based 6D Object Pose Estimation with 3D Gaussian Splatting—0
BOP Challenge 2023 on Detection, Segmentation and Pose Estimation of Seen and Unseen Rigid Objects—0
Uncertainty Quantification with Deep Ensembles for 6D Object Pose Estimation—0
Improving 2D-3D Dense Correspondences with Diffusion Models for 6D Object Pose Estimation—0
Real-time Holistic Robot Pose Estimation with Unknown StatesCode1
Extending 6D Object Pose Estimators for Stereo Vision—0
6D-Diff: A Keypoint Diffusion Framework for 6D Object Pose Estimation—0
Three-Filters-to-Normal+: Revisiting Discontinuity Discrimination in Depth-to-Normal Translation—0
FoundationPose: Unified 6D Pose Estimation and Tracking of Novel ObjectsCode4
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