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[IROS 2021] BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Models
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.
深度ĺ¦äą 和三维视觉相关的论文
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.
Pytorch code for ICRA'22 paper: "Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimation"
A Perspective-n-Points-and-Lines method.
Python scripts for performing 6D pose estimation and shape reconstruction using the CenterSnap model in ONNX
semantic mapping module of vision lab slam system
A Python 3 implementation of "A Stable Algebraic Camera Pose Estimation for Minimal Configurations of 2D/3D Point and Line Correspondences." by Zhou et al. ACCV 2018
EgoNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale
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"
Code for DronePose: Photorealistic UAV-Assistant Dataset Synthesis for 3D Pose Estimation via a Smooth Silhouette Loss (ECCVW 2020)
This is my Master thesis which evaluates 6D pose estimating deep learning methods for usage in an AR use case. It includes 2 new proxies for Gabriel in order to make the Deep Learning methods usable in AR-enabled devices.
Official project website for the AAAI 2022 paper "Stereo Neural Vernier Caliper"
This research project implements a real-time object detection and pose estimation method as described in the paper, Tekin et al. "Real-Time Seamless Single Shot 6D Object Pose Prediction", CVPR 2018. (https://arxiv.org/abs/1711.08848).