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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 111–120 of 233 papers

TitleStatusHype
Sim-to-Real 6D Object Pose Estimation via Iterative Self-training for Robotic Bin Picking—0
Single Shot 6D Object Pose Estimation—0
SMOC-Net: Leveraging Camera Pose for Self-Supervised Monocular Object Pose Estimation—0
SO(3)-Pose: SO(3)-Equivariance Learning for 6D Object Pose Estimation—0
SOCS: Semantically-aware Object Coordinate Space for Category-Level 6D Object Pose Estimation under Large Shape Variations—0
Sparse Color-Code Net: Real-Time RGB-Based 6D Object Pose Estimation on Edge Devices—0
Spatial Attention Improves Iterative 6D Object Pose Estimation—0
StablePose: Learning 6D Object Poses from Geometrically Stable Patches—0
StereOBJ-1M: Large-scale Stereo Image Dataset for 6D Object Pose Estimation—0
Stereo Vision Based Single-Shot 6D Object Pose Estimation for Bin-Picking by a Robot Manipulator—0
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