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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 141–150 of 233 papers

TitleStatusHype
Ambiguity-Aware Multi-Object Pose Optimization for Visually-Assisted Robot ManipulationCode0
Imitrob: Imitation Learning Dataset for Training and Evaluating 6D Object Pose EstimatorsCode0
6D Robotic Assembly Based on RGB-only Object Pose Estimation—0
COPE: End-to-end trainable Constant Runtime Object Pose Estimation—0
SO(3)-Pose: SO(3)-Equivariance Learning for 6D Object Pose Estimation—0
Towards Two-view 6D Object Pose Estimation: A Comparative Study on Fusion Strategy—0
Category-Level 6D Object Pose Estimation in the Wild: A Semi-Supervised Learning Approach and A New Dataset—0
Knowledge Distillation for 6D Pose Estimation by Aligning Distributions of Local Predictions—0
PhoCaL: A Multi-Modal Dataset for Category-Level Object Pose Estimation with Photometrically Challenging Objects—0
YOLOPose: Transformer-based Multi-Object 6D Pose Estimation using Keypoint Regression—0
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