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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

Showing 141150 of 233 papers

TitleStatusHype
Context-aware 6D Pose Estimation of Known Objects using RGB-D data0
ConvPoseCNN: Dense Convolutional 6D Object Pose Estimation0
COPE: End-to-end trainable Constant Runtime Object Pose Estimation0
Deep Learning of Local RGB-D Patches for 3D Object Detection and 6D Pose Estimation0
EfficientPose 6D: Scalable and Efficient 6D Object Pose Estimation0
End-to-End Differentiable 6DoF Object Pose Estimation with Local and Global Constraints0
End-to-End Probabilistic Geometry-Guided Regression for 6DoF Object Pose Estimation0
Enhancing Transparent Object Pose Estimation: A Fusion of GDR-Net and Edge Detection0
Exploiting Point-Wise Attention in 6D Object Pose Estimation Based on Bidirectional Prediction0
Extending 6D Object Pose Estimators for Stereo Vision0
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