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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 181–190 of 233 papers

TitleStatusHype
Pose Proposal Critic: Robust Pose Refinement by Learning Reprojection Errors—0
Single Shot 6D Object Pose Estimation—0
MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models—0
A Pose Proposal and Refinement Network for Better Object Pose Estimation—0
Introducing Pose Consistency and Warp-Alignment for Self-Supervised 6D Object Pose Estimation in Color Images—0
SilhoNet-Fisheye: Adaptation of A ROI Based Object Pose Estimation Network to Monocular Fisheye Images—0
A Review on Object Pose Recovery: from 3D Bounding Box Detectors to Full 6D Pose Estimators—0
P^2GNet: Pose-Guided Point Cloud Generating Networks for 6-DoF Object Pose Estimation—0
ConvPoseCNN: Dense Convolutional 6D Object Pose Estimation—0
LatentFusion: End-to-End Differentiable Reconstruction and Rendering for Unseen Object Pose EstimationCode0
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