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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 201–210 of 233 papers

TitleStatusHype
Instance- and Category-level 6D Object Pose Estimation—0
Investigations on Output Parameterizations of Neural Networks for Single Shot 6D Object Pose Estimation—0
iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects—0
KDFNet: Learning Keypoint Distance Field for 6D Object Pose Estimation—0
Knowledge Distillation for 6D Pose Estimation by Aligning Distributions of Local Predictions—0
Learning Analysis-by-Synthesis for 6D Pose Estimation in RGB-D Images—0
MatchNorm: Learning-based Point Cloud Registration for 6D Object Pose Estimation in the Real World—0
Learning Object Localization and 6D Pose Estimation from Simulation and Weakly Labeled Real Images—0
Learning Stereopsis from Geometric Synthesis for 6D Object Pose Estimation—0
MBAPose: Mask and Bounding-Box Aware Pose Estimation of Surgical Instruments with Photorealistic Domain Randomization—0
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