Awesome work on object 6 DoF pose estimation
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Updated
Jul 29, 2024
Awesome work on object 6 DoF pose estimation
Single-Stage Keypoint-based Category-level Object Pose Estimation from an RGB Image (ICRA 2022)
[ICCV 2023 R6D] PyTorch implementation of CNOS: A Strong Baseline for CAD-based Novel Object Segmentation based on Segmenting Anything and DINOv2
Project Page for Paper "Deep Learning-Based Object Pose Estimation: A Comprehensive Survey"
[CVPR 2022] Pytorch implementation of "Templates for 3D Object Pose Estimation Revisited: Generalization to New objects and Robustness to Occlusions" paper
[CVPR 2024] PyTorch implementation of GigaPose: Fast and Robust Novel Object Pose Estimation via One Correspondence
Real-time robotic object pose estimation with deep learning
Self6D++: Occlusion-Aware Self-Supervised Monocular 6D Object Pose Estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2021.
SurfEmb (CVPR 2022)
Code for "EPOS: Estimating 6D Pose of Objects with Symmetries", CVPR 2020.
SLAM-Supported Semi-Supervised Learning for 6D Object Pose Estimation
🚀 A neural network for monocular spacecraft 6D pose estimation: 3rd place solution of the European Space Agency’s pose estimation challenge
moai is a PyTorch-based AI Model Development Kit (MDK) created to improve data-driven model workflows, design and reproducibility.
CASAPose: Class-Adaptive and Semantic-Aware Multi-Object Pose Estimation (BMVC 2022)
[CVPR 2024] Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3)
Instance Segmentation Aided 6D Object Pose and Velocity Tracking using an Unscented Kalman Filter
Parallel Inversion of Neural Radiance Fields for Robust Pose Estimation (ICRA 2023)
Automate bin-picking tasks using the Dobot CR5 robotic arm. The system combines YOLOv5 for object detection and FAST/BRISK for feature detection and matching. With a depth sensor camera, we achieve real-time object detection and precise pose estimation, improving industrial automation and operational efficiency.
A single-shot learning-based approach to hand and object pose estimation, made available on a head-mounted display.
Toolbox to evaluate categorical pose and shape estimation methods
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