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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 101–125 of 233 papers

TitleStatusHype
DCL-Net: Deep Correspondence Learning Network for 6D Pose EstimationCode1
Imitrob: Imitation Learning Dataset for Training and Evaluating 6D Object Pose EstimatorsCode0
6D Robotic Assembly Based on RGB-only Object Pose Estimation—0
COPE: End-to-end trainable Constant Runtime Object Pose Estimation—0
SO(3)-Pose: SO(3)-Equivariance Learning for 6D Object Pose Estimation—0
SC6D: Symmetry-agnostic and Correspondence-free 6D Object Pose EstimationCode1
Towards Two-view 6D Object Pose Estimation: A Comparative Study on Fusion Strategy—0
Category-Level 6D Object Pose Estimation in the Wild: A Semi-Supervised Learning Approach and A New Dataset—0
Knowledge Distillation for 6D Pose Estimation by Aligning Distributions of Local Predictions—0
PhoCaL: A Multi-Modal Dataset for Category-Level Object Pose Estimation with Photometrically Challenging Objects—0
YOLOPose: Transformer-based Multi-Object 6D Pose Estimation using Keypoint Regression—0
Coupled Iterative Refinement for 6D Multi-Object Pose EstimationCode1
HRPose: Real-Time High-Resolution 6D Pose Estimation Network Using Knowledge Distillation—0
Sim-to-Real 6D Object Pose Estimation via Iterative Self-training for Robotic Bin Picking—0
Object Level Depth Reconstruction for Category Level 6D Object Pose Estimation From Monocular RGB Image—0
Templates for 3D Object Pose Estimation Revisited: Generalization to New Objects and Robustness to OcclusionsCode1
MatchNorm: Learning-based Point Cloud Registration for 6D Object Pose Estimation in the Real World—0
FS6D: Few-Shot 6D Pose Estimation of Novel ObjectsCode1
RNNPose: Recurrent 6-DoF Object Pose Refinement with Robust Correspondence Field Estimation and Pose OptimizationCode1
EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose EstimationCode3
Occlusion-Aware Self-Supervised Monocular 6D Object Pose EstimationCode1
Perspective Flow Aggregation for Data-Limited 6D Object Pose EstimationCode1
GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise VotingCode1
NeRF-Pose: A First-Reconstruct-Then-Regress Approach for Weakly-supervised 6D Object Pose Estimation—0
Weakly Supervised Learning of Keypoints for 6D Object Pose Estimation—0
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