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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 171–180 of 233 papers

TitleStatusHype
Center-Based Decoupled Point-cloud Registration for 6D Object Pose Estimation—0
Challenges for Monocular 6D Object Pose Estimation in Robotics—0
Conscious Inference for Object Detection—0
Context-aware 6D Pose Estimation of Known Objects using RGB-D data—0
ConvPoseCNN: Dense Convolutional 6D Object Pose Estimation—0
COPE: End-to-end trainable Constant Runtime Object Pose Estimation—0
Deep Learning of Local RGB-D Patches for 3D Object Detection and 6D Pose Estimation—0
EfficientPose 6D: Scalable and Efficient 6D Object Pose Estimation—0
End-to-End Differentiable 6DoF Object Pose Estimation with Local and Global Constraints—0
End-to-End Probabilistic Geometry-Guided Regression for 6DoF Object Pose Estimation—0
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