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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 201–210 of 233 papers

TitleStatusHype
Rigidity Preserving Image Transformations and Equivariance in Perspective—0
Robust 6D Object Pose Estimation in Cluttered Scenes using Semantic Segmentation and Pose Regression Networks—0
Robust 6D Object Pose Estimation with Stochastic Congruent Sets—0
SCFlow2: Plug-and-Play Object Pose Refiner with Shape-Constraint Scene Flow—0
SGPA: Structure-Guided Prior Adaptation for Category-Level 6D Object Pose Estimation—0
[Re] On end-to-end 6DoF object pose estimation and robustness to object scaleCode0
BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using DepthCode0
Real-Time Seamless Single Shot 6D Object Pose PredictionCode0
PoseRBPF: A Rao-Blackwellized Particle Filter for 6D Object Pose TrackingCode0
DPOD: 6D Pose Object Detector and RefinerCode0
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