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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 201–233 of 233 papers

TitleStatusHype
Instance- and Category-level 6D Object Pose Estimation—0
Investigations on Output Parameterizations of Neural Networks for Single Shot 6D Object Pose Estimation—0
iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects—0
KDFNet: Learning Keypoint Distance Field for 6D Object Pose Estimation—0
Knowledge Distillation for 6D Pose Estimation by Aligning Distributions of Local Predictions—0
Learning Analysis-by-Synthesis for 6D Pose Estimation in RGB-D Images—0
MatchNorm: Learning-based Point Cloud Registration for 6D Object Pose Estimation in the Real World—0
Learning Object Localization and 6D Pose Estimation from Simulation and Weakly Labeled Real Images—0
Learning Stereopsis from Geometric Synthesis for 6D Object Pose Estimation—0
MBAPose: Mask and Bounding-Box Aware Pose Estimation of Surgical Instruments with Photorealistic Domain Randomization—0
Model-Based Underwater 6D Pose Estimation from RGB—0
Monocular One-Shot Metric-Depth Alignment for RGB-Based Robot Grasping—0
MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models—0
MSDA: Monocular Self-supervised Domain Adaptation for 6D Object Pose Estimation—0
Multi-Modal 3D Mesh Reconstruction from Images and Text—0
Multistream ValidNet: Improving 6D Object Pose Estimation by Automatic Multistream Validation—0
Multi-View Keypoints for Reliable 6D Object Pose Estimation—0
NeRF-Feat: 6D Object Pose Estimation using Feature Rendering—0
NeRF-Pose: A First-Reconstruct-Then-Regress Approach for Weakly-supervised 6D Object Pose Estimation—0
Object Level Depth Reconstruction for Category Level 6D Object Pose Estimation From Monocular RGB Image—0
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
Pos3R: 6D Pose Estimation for Unseen Objects Made Easy—0
PoseAgent: Budget-Constrained 6D Object Pose Estimation via Reinforcement Learning—0
Pose Estimation of Specific Rigid Objects—0
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