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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 71–80 of 233 papers

TitleStatusHype
Deep Learning of Local RGB-D Patches for 3D Object Detection and 6D Pose Estimation—0
BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objects—0
Accurate 6D Object Pose Estimation by Pose Conditioned Mesh Reconstruction—0
GenFlow: Generalizable Recurrent Flow for 6D Pose Refinement of Novel Objects—0
6D-ViT: Category-Level 6D Object Pose Estimation via Transformer-based Instance Representation Learning—0
6D Object Pose Estimation using Keypoints and Part Affinity Fields—0
Global Hypothesis Generation for 6D Object Pose Estimation—0
Object Pose Estimation in Robotics Revisited—0
6D Robotic Assembly Based on RGB-only Object Pose Estimation—0
6D Object Pose Estimation from Approximate 3D Models for Orbital Robotics—0
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