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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 151–160 of 233 papers

TitleStatusHype
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
MatchNorm: Learning-based Point Cloud Registration for 6D Object Pose Estimation in the Real World—0
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
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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