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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 81–90 of 233 papers

TitleStatusHype
COPE: End-to-end trainable Constant Runtime Object Pose Estimation—0
ConvPoseCNN: Dense Convolutional 6D Object Pose Estimation—0
AxisPose: Model-Free Matching-Free Single-Shot 6D Object Pose Estimation via Axis Generation—0
Context-aware 6D Pose Estimation of Known Objects using RGB-D data—0
Conscious Inference for Object Detection—0
A Summary of the 4th International Workshop on Recovering 6D Object Pose—0
6D Pose Estimation with Correlation Fusion—0
Classification of Single-View Object Point Clouds—0
HomebrewedDB: RGB-D Dataset for 6D Pose Estimation of 3D Objects—0
A Review on Object Pose Recovery: from 3D Bounding Box Detectors to Full 6D Pose Estimators—0
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