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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 226–233 of 233 papers

TitleStatusHype
Recovering 6D Object Pose: A Review and Multi-modal Analysis—0
BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using DepthCode0
PoseAgent: Budget-Constrained 6D Object Pose Estimation via Reinforcement Learning—0
Global Hypothesis Generation for 6D Object Pose Estimation—0
Deep Learning of Local RGB-D Patches for 3D Object Detection and 6D Pose Estimation—0
Uncertainty-Driven 6D Pose Estimation of Objects and Scenes From a Single RGB Image—0
Recovering 6D Object Pose and Predicting Next-Best-View in the Crowd—0
Learning Analysis-by-Synthesis for 6D Pose Estimation in RGB-D Images—0
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