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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 201–210 of 233 papers

TitleStatusHype
6D Object Pose Estimation Based on 2D Bounding Box—0
Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size EstimationCode1
PVNet: Pixel-wise Voting Network for 6DoF Pose EstimationCode1
Segmentation-driven 6D Object Pose EstimationCode0
Estimating 6D Pose From Localizing Designated Surface KeypointsCode0
Real-Time 6D Object Pose Estimation on CPU—0
A Summary of the 4th International Workshop on Recovering 6D Object Pose—0
Robust 6D Object Pose Estimation in Cluttered Scenes using Semantic Segmentation and Pose Regression Networks—0
Conscious Inference for Object Detection—0
SilhoNet: An RGB Method for 6D Object Pose EstimationCode0
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