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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 131–140 of 233 papers

TitleStatusHype
Uncertainty-Driven 6D Pose Estimation of Objects and Scenes From a Single RGB Image—0
Uncertainty Quantification with Deep Ensembles for 6D Object Pose Estimation—0
Weakly Supervised Learning of Keypoints for 6D Object Pose Estimation—0
YOLOPose: Transformer-based Multi-Object 6D Pose Estimation using Keypoint Regression—0
YOLOPose V2: Understanding and Improving Transformer-based 6D Pose Estimation—0
Certifying Robustness of Learning-Based Keypoint Detection and Pose Estimation Methods—0
ZS6D: Zero-shot 6D Object Pose Estimation using Vision Transformers—0
Classification of Single-View Object Point Clouds—0
6D-Diff: A Keypoint Diffusion Framework for 6D Object Pose Estimation—0
6D Object Pose Estimation Based on 2D Bounding Box—0
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