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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 121–130 of 233 papers

TitleStatusHype
Occlusion-Aware Self-Supervised Monocular 6D Object Pose EstimationCode1
Perspective Flow Aggregation for Data-Limited 6D Object Pose EstimationCode1
GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise VotingCode1
NeRF-Pose: A First-Reconstruct-Then-Regress Approach for Weakly-supervised 6D Object Pose Estimation—0
Weakly Supervised Learning of Keypoints for 6D Object Pose Estimation—0
OVE6D: Object Viewpoint Encoding for Depth-based 6D Object Pose EstimationCode1
Adversarial samples for deep monocular 6D object pose estimationCode0
Rigidity Preserving Image Transformations and Equivariance in Perspective—0
Pose Estimation of Specific Rigid Objects—0
Polarimetric Pose Prediction—0
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