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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 11–20 of 233 papers

TitleStatusHype
CullNet: Calibrated and Pose Aware Confidence Scores for Object Pose EstimationCode1
Depth-based 6DoF Object Pose Estimation using Swin TransformerCode1
DR-Pose: A Two-stage Deformation-and-Registration Pipeline for Category-level 6D Object Pose EstimationCode1
EfficientPose: An efficient, accurate and scalable end-to-end 6D multi object pose estimation approachCode1
CRT-6D: Fast 6D Object Pose Estimation with Cascaded Refinement TransformersCode1
DCL-Net: Deep Correspondence Learning Network for 6D Pose EstimationCode1
CASAPose: Class-Adaptive and Semantic-Aware Multi-Object Pose EstimationCode1
BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D ModelsCode1
Coupled Iterative Refinement for 6D Multi-Object Pose EstimationCode1
Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3)Code1
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