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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 221–230 of 233 papers

TitleStatusHype
Omni6DPose: A Benchmark and Model for Universal 6D Object Pose Estimation and Tracking—0
ONDA-Pose: Occlusion-Aware Neural Domain Adaptation for Self-Supervised 6D Object Pose Estimation—0
One2Any: One-Reference 6D Pose Estimation for Any Object—0
Open Challenges for Monocular Single-shot 6D Object Pose Estimation—0
P^2GNet: Pose-Guided Point Cloud Generating Networks for 6-DoF Object Pose Estimation—0
PAM:Point-wise Attention Module for 6D Object Pose Estimation—0
PhoCaL: A Multi-Modal Dataset for Category-Level Object Pose Estimation with Photometrically Challenging Objects—0
Photorealistic Image Synthesis for Object Instance Detection—0
PhysPose: Refining 6D Object Poses with Physical Constraints—0
Polarimetric Pose Prediction—0
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