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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 111–120 of 233 papers

TitleStatusHype
YOLOPose: Transformer-based Multi-Object 6D Pose Estimation using Keypoint Regression—0
Coupled Iterative Refinement for 6D Multi-Object Pose EstimationCode1
HRPose: Real-Time High-Resolution 6D Pose Estimation Network Using Knowledge Distillation—0
Sim-to-Real 6D Object Pose Estimation via Iterative Self-training for Robotic Bin Picking—0
Object Level Depth Reconstruction for Category Level 6D Object Pose Estimation From Monocular RGB Image—0
Templates for 3D Object Pose Estimation Revisited: Generalization to New Objects and Robustness to OcclusionsCode1
MatchNorm: Learning-based Point Cloud Registration for 6D Object Pose Estimation in the Real World—0
FS6D: Few-Shot 6D Pose Estimation of Novel ObjectsCode1
RNNPose: Recurrent 6-DoF Object Pose Refinement with Robust Correspondence Field Estimation and Pose OptimizationCode1
EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose EstimationCode3
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