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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 91–100 of 233 papers

TitleStatusHype
Category Level 6D Object Pose Estimation from a Single RGB Image using Diffusion—0
Targeted Hard Sample Synthesis Based on Estimated Pose and Occlusion Error for Improved Object Pose Estimation—0
6DOPE-GS: Online 6D Object Pose Estimation using Gaussian Splatting—0
GMFlow: Global Motion-Guided Recurrent Flow for 6D Object Pose Estimation—0
GS2Pose: Two-stage 6D Object Pose Estimation Guided by Gaussian Splatting—0
CVAM-Pose: Conditional Variational Autoencoder for Multi-Object Monocular Pose EstimationCode0
FAST GDRNPP: Improving the Speed of State-of-the-Art 6D Object Pose Estimation—0
End-to-End Probabilistic Geometry-Guided Regression for 6DoF Object Pose Estimation—0
From Words to Poses: Enhancing Novel Object Pose Estimation with Vision Language Models—0
Certifying Robustness of Learning-Based Keypoint Detection and Pose Estimation Methods—0
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