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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

Showing 2130 of 233 papers

TitleStatusHype
Level-Set Parameters: Novel Representation for 3D Shape AnalysisCode0
Category Level 6D Object Pose Estimation from a Single RGB Image using Diffusion0
Targeted Hard Sample Synthesis Based on Estimated Pose and Occlusion Error for Improved Object Pose Estimation0
6DOPE-GS: Online 6D Object Pose Estimation using Gaussian Splatting0
Particle-based 6D Object Pose Estimation from Point Clouds using Diffusion ModelsCode1
GMFlow: Global Motion-Guided Recurrent Flow for 6D Object Pose Estimation0
GS2Pose: Two-stage 6D Object Pose Estimation Guided by Gaussian Splatting0
CVAM-Pose: Conditional Variational Autoencoder for Multi-Object Monocular Pose EstimationCode0
Omni6D: Large-Vocabulary 3D Object Dataset for Category-Level 6D Object Pose EstimationCode1
FAST GDRNPP: Improving the Speed of State-of-the-Art 6D Object Pose Estimation0
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