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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 125 of 233 papers

TitleStatusHype
FoundationPose: Unified 6D Pose Estimation and Tracking of Novel ObjectsCode4
EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose EstimationCode3
EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose EstimationCode3
Instance-Adaptive and Geometric-Aware Keypoint Learning for Category-Level 6D Object Pose EstimationCode2
YOLOv5-6D: Advancing 6-DoF Instrument Pose Estimation in Variable X-Ray Imaging GeometriesCode2
SAM-6D: Segment Anything Model Meets Zero-Shot 6D Object Pose EstimationCode2
BOP Challenge 2020 on 6D Object LocalizationCode2
Particle-based 6D Object Pose Estimation from Point Clouds using Diffusion ModelsCode1
Omni6D: Large-Vocabulary 3D Object Dataset for Category-Level 6D Object Pose EstimationCode1
NeuSurfEmb: A Complete Pipeline for Dense Correspondence-based 6D Object Pose Estimation without CAD ModelsCode1
Real-time Holistic Robot Pose Estimation with Unknown StatesCode1
SE(3) Diffusion Model-based Point Cloud Registration for Robust 6D Object Pose EstimationCode1
DR-Pose: A Two-stage Deformation-and-Registration Pipeline for Category-level 6D Object Pose EstimationCode1
Pseudo Flow Consistency for Self-Supervised 6D Object Pose EstimationCode1
VI-Net: Boosting Category-level 6D Object Pose Estimation via Learning Decoupled Rotations on the Spherical RepresentationsCode1
Deep Fusion Transformer Network with Weighted Vector-Wise Keypoints Voting for Robust 6D Object Pose EstimationCode1
Revisiting Fully Convolutional Geometric Features for Object 6D Pose EstimationCode1
SyMFM6D: Symmetry-aware Multi-directional Fusion for Multi-View 6D Object Pose EstimationCode1
Shape-Constraint Recurrent Flow for 6D Object Pose EstimationCode1
Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3)Code1
Rigidity-Aware Detection for 6D Object Pose EstimationCode1
Linear-Covariance Loss for End-to-End Learning of 6D Pose EstimationCode1
Depth-based 6DoF Object Pose Estimation using Swin TransformerCode1
3D Neural Embedding Likelihood: Probabilistic Inverse Graphics for Robust 6D Pose EstimationCode1
Learning Symmetry-Aware Geometry Correspondences for 6D Object Pose EstimationCode1
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