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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 41–50 of 233 papers

TitleStatusHype
FS-Net: Fast Shape-based Network for Category-Level 6D Object Pose Estimation with Decoupled Rotation MechanismCode1
G2L-Net: Global to Local Network for Real-time 6D Pose Estimation with Embedding Vector FeaturesCode1
GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise VotingCode1
Ground-aware Monocular 3D Object Detection for Autonomous DrivingCode1
CullNet: Calibrated and Pose Aware Confidence Scores for Object Pose EstimationCode1
Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3)Code1
CRT-6D: Fast 6D Object Pose Estimation with Cascaded Refinement TransformersCode1
NeuSurfEmb: A Complete Pipeline for Dense Correspondence-based 6D Object Pose Estimation without CAD ModelsCode1
Occlusion-Aware Self-Supervised Monocular 6D Object Pose EstimationCode1
Deep Fusion Transformer Network with Weighted Vector-Wise Keypoints Voting for Robust 6D Object Pose EstimationCode1
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