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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 101–150 of 233 papers

TitleStatusHype
Recovering 6D Object Pose and Predicting Next-Best-View in the Crowd—0
Recovering 6D Object Pose: A Review and Multi-modal Analysis—0
Review on 6D Object Pose Estimation with the focus on Indoor Scene Understanding—0
ZS6D: Zero-shot 6D Object Pose Estimation using Vision Transformers—0
Classification of Single-View Object Point Clouds—0
6D-Diff: A Keypoint Diffusion Framework for 6D Object Pose Estimation—0
6D Object Pose Estimation Based on 2D Bounding Box—0
6D Object Pose Estimation from Approximate 3D Models for Orbital Robotics—0
6D Object Pose Estimation using Keypoints and Part Affinity Fields—0
6D Object Pose Estimation with Depth Images: A Seamless Approach for Robotic Interaction and Augmented Reality—0
6D Object Pose Estimation without PnP—0
6DOPE-GS: Online 6D Object Pose Estimation using Gaussian Splatting—0
6D Pose Estimation using an Improved Method based on Point Pair Features—0
6D Pose Estimation with Correlation Fusion—0
6D Robotic Assembly Based on RGB-only Object Pose Estimation—0
6D-ViT: Category-Level 6D Object Pose Estimation via Transformer-based Instance Representation Learning—0
Accurate 6D Object Pose Estimation by Pose Conditioned Mesh Reconstruction—0
ACR-Pose: Adversarial Canonical Representation Reconstruction Network for Category Level 6D Object Pose Estimation—0
A mixed-reality dataset for category-level 6D pose and size estimation of hand-occluded containers—0
A Novel Convolution and Attention Mechanism-based Model for 6D Object Pose Estimation—0
A Pose Proposal and Refinement Network for Better Object Pose Estimation—0
Any6D: Model-free 6D Pose Estimation of Novel Objects—0
A Review on Object Pose Recovery: from 3D Bounding Box Detectors to Full 6D Pose Estimators—0
A Summary of the 4th International Workshop on Recovering 6D Object Pose—0
AxisPose: Model-Free Matching-Free Single-Shot 6D Object Pose Estimation via Axis Generation—0
Object Pose Estimation in Robotics Revisited—0
BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objects—0
BOP Challenge 2023 on Detection, Segmentation and Pose Estimation of Seen and Unseen Rigid Objects—0
BOP Challenge 2024 on Model-Based and Model-Free 6D Object Pose Estimation—0
Category Level 6D Object Pose Estimation from a Single RGB Image using Diffusion—0
Category-Level 6D Object Pose Estimation in the Wild: A Semi-Supervised Learning Approach and A New Dataset—0
Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data—0
Category-Level 6D Object Pose Estimation via Cascaded Relation and Recurrent Reconstruction Networks—0
Category-Level 6D Object Pose Estimation with Flexible Vector-Based Rotation Representation—0
Category-level 6D Object Pose Recovery in Depth Images—0
Category-Level and Open-Set Object Pose Estimation for Robotics—0
CDPN: Coordinates-Based Disentangled Pose Network for Real-Time RGB-Based 6-DoF Object Pose Estimation—0
Center-Based Decoupled Point-cloud Registration for 6D Object Pose Estimation—0
Challenges for Monocular 6D Object Pose Estimation in Robotics—0
Conscious Inference for Object Detection—0
Context-aware 6D Pose Estimation of Known Objects using RGB-D data—0
ConvPoseCNN: Dense Convolutional 6D Object Pose Estimation—0
COPE: End-to-end trainable Constant Runtime Object Pose Estimation—0
Deep Learning of Local RGB-D Patches for 3D Object Detection and 6D Pose Estimation—0
EfficientPose 6D: Scalable and Efficient 6D Object Pose Estimation—0
End-to-End Differentiable 6DoF Object Pose Estimation with Local and Global Constraints—0
End-to-End Probabilistic Geometry-Guided Regression for 6DoF Object Pose Estimation—0
Enhancing Transparent Object Pose Estimation: A Fusion of GDR-Net and Edge Detection—0
Exploiting Point-Wise Attention in 6D Object Pose Estimation Based on Bidirectional Prediction—0
Extending 6D Object Pose Estimators for Stereo Vision—0
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