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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 181–190 of 233 papers

TitleStatusHype
ConvPoseCNN: Dense Convolutional 6D Object Pose Estimation—0
Large-scale 6D Object Pose Estimation Dataset for Industrial Bin-PickingCode1
LatentFusion: End-to-End Differentiable Reconstruction and Rendering for Unseen Object Pose EstimationCode0
Single-Stage 6D Object Pose EstimationCode0
Accurate 6D Object Pose Estimation by Pose Conditioned Mesh Reconstruction—0
CDPN: Coordinates-Based Disentangled Pose Network for Real-Time RGB-Based 6-DoF Object Pose Estimation—0
CullNet: Calibrated and Pose Aware Confidence Scores for Object Pose EstimationCode1
6D Pose Estimation with Correlation Fusion—0
End-to-End Learnable Geometric Vision by Backpropagating PnP OptimizationCode0
Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose EstimationCode0
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