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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 121–130 of 233 papers

TitleStatusHype
Synthetic Data Generation for Bridging Sim2Real Gap in a Production Environment—0
Introducing Pose Consistency and Warp-Alignment for Self-Supervised 6D Object Pose Estimation in Color Images—0
Targeted Hard Sample Synthesis Based on Estimated Pose and Occlusion Error for Improved Object Pose Estimation—0
TexPose: Neural Texture Learning for Self-Supervised 6D Object Pose Estimation—0
Three-Filters-to-Normal+: Revisiting Discontinuity Discrimination in Depth-to-Normal Translation—0
Towards real-time 6D pose estimation of objects in single-view cone-beam X-ray—0
Towards Two-view 6D Object Pose Estimation: A Comparative Study on Fusion Strategy—0
TransPose: 6D Object Pose Estimation with Geometry-Aware Transformer—0
TransPose: A Transformer-based 6D Object Pose Estimation Network with Depth Refinement—0
UA-Pose: Uncertainty-Aware 6D Object Pose Estimation and Online Object Completion with Partial References—0
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