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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 151–160 of 233 papers

TitleStatusHype
FAST GDRNPP: Improving the Speed of State-of-the-Art 6D Object Pose Estimation—0
LocPoseNet: Robust Location Prior for Unseen Object Pose Estimation—0
From Words to Poses: Enhancing Novel Object Pose Estimation with Vision Language Models—0
GenFlow: Generalizable Recurrent Flow for 6D Pose Refinement of Novel Objects—0
Global Hypothesis Generation for 6D Object Pose Estimation—0
GMFlow: Global Motion-Guided Recurrent Flow for 6D Object Pose Estimation—0
Going Further with Point Pair Features—0
GS2Pose: Two-stage 6D Object Pose Estimation Guided by Gaussian Splatting—0
GS-Pose: Generalizable Segmentation-based 6D Object Pose Estimation with 3D Gaussian Splatting—0
Hierarchical Graph Neural Networks for Proprioceptive 6D Pose Estimation of In-hand Objects—0
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