[ECCV2022] Gen6D: Generalizable Model-Free 6-DoF Object Pose Estimation from RGB Images
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Updated
Apr 9, 2023 - Python
[ECCV2022] Gen6D: Generalizable Model-Free 6-DoF Object Pose Estimation from RGB Images
Computer vision utils for Blender (generate instance annoatation, depth and 6D pose by one line code)
[IROS 2020] se(3)-TrackNet: Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domains
[CVPR2021 Oral] FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation.
Pytorch code for ECCV'22 paper. ShAPO: Implicit Representations for Multi-Object Shape, Appearance and Pose Optimization
Official code of ECCV 2020 paper "GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision". GSNet performs joint vehicle pose estimation and vehicle shape reconstruction with single RGB image as input.
DFNet: Enhance Absolute Pose Regression with Direct Feature Matching (ECCV 2022)
[CVPR 2022] Focal Length and Object Pose Estimation via Render and Compare
Code for "EPOS: Estimating 6D Pose of Objects with Symmetries", CVPR 2020.
A Perspective-n-Points-and-Lines method.
Python scripts for performing 6D pose estimation and shape reconstruction using the CenterSnap model in ONNX
EgoNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale
Code for "Robotic Continuous Grasping System by Shape Transformer-Guided Multi-Object Category-Level 6D Pose Estimation" (TII 2023).
[IROS24] Offical repository for "PEGASUS: Physically Enhanced Gaussian Splatting Simulation System for 6DoF Object Pose Dataset Generation"
CASAPose: Class-Adaptive and Semantic-Aware Multi-Object Pose Estimation (BMVC 2022)
Code for "MH6D: Multi-Hypothesis Consistency Learning for Category-Level 6D Object Pose Estimation" (TNNLS 2024).
Code for DronePose: Photorealistic UAV-Assistant Dataset Synthesis for 3D Pose Estimation via a Smooth Silhouette Loss (ECCVW 2020)
DOPE (Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects)
Code implementation of our paper "CullNet: Calibrated and Pose Aware Confidence Scores for Object Pose Estimation"
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