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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 211–220 of 233 papers

TitleStatusHype
A Summary of the 4th International Workshop on Recovering 6D Object Pose—0
Robust 6D Object Pose Estimation in Cluttered Scenes using Semantic Segmentation and Pose Regression Networks—0
Conscious Inference for Object Detection—0
SilhoNet: An RGB Method for 6D Object Pose EstimationCode0
Category-level 6D Object Pose Recovery in Depth Images—0
Learning Object Localization and 6D Pose Estimation from Simulation and Weakly Labeled Real Images—0
Robust 6D Object Pose Estimation with Stochastic Congruent Sets—0
6D Pose Estimation using an Improved Method based on Point Pair Features—0
iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects—0
PointFusion: Deep Sensor Fusion for 3D Bounding Box EstimationCode0
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