6D Pose Estimation

55 papers with code • 5 benchmarks • 6 datasets

Image: Zeng et al

Libraries

Use these libraries to find 6D Pose Estimation models and implementations

Most implemented papers

PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

yuxng/PoseCNN 1 Nov 2017

We conduct extensive experiments on our YCB-Video dataset and the OccludedLINEMOD dataset to show that PoseCNN is highly robust to occlusions, can handle symmetric objects, and provide accurate pose estimation using only color images as input.

DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion

j96w/DenseFusion CVPR 2019

A key technical challenge in performing 6D object pose estimation from RGB-D image is to fully leverage the two complementary data sources.

Estimating 6D Pose From Localizing Designated Surface Keypoints

sjtuytc/betapose 4 Dec 2018

In this paper, we present an accurate yet effective solution for 6D pose estimation from an RGB image.

Segmentation-driven 6D Object Pose Estimation

cvlab-epfl/segmentation-driven-pose CVPR 2019

The most recent trend in estimating the 6D pose of rigid objects has been to train deep networks to either directly regress the pose from the image or to predict the 2D locations of 3D keypoints, from which the pose can be obtained using a PnP algorithm.

Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation

hughw19/NOCS_CVPR2019 CVPR 2019

The goal of this paper is to estimate the 6D pose and dimensions of unseen object instances in an RGB-D image.

Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimation

kirumang/Pix2Pose ICCV 2019

Estimating the 6D pose of objects using only RGB images remains challenging because of problems such as occlusion and symmetries.

PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimation

ethnhe/PVN3D CVPR 2020

Our method is a natural extension of 2D-keypoint approaches that successfully work on RGB based 6DoF estimation.

BOP Challenge 2020 on 6D Object Localization

thodan/bop_toolkit 15 Sep 2020

This paper presents the evaluation methodology, datasets, and results of the BOP Challenge 2020, the third in a series of public competitions organized with the goal to capture the status quo in the field of 6D object pose estimation from an RGB-D image.

FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation

ethnhe/FFB6D CVPR 2021

Moreover, at the output representation stage, we designed a simple but effective 3D keypoints selection algorithm considering the texture and geometry information of objects, which simplifies keypoint localization for precise pose estimation.

Multi-view Self-supervised Deep Learning for 6D Pose Estimation in the Amazon Picking Challenge

andyzeng/apc-vision-toolbox 29 Sep 2016

The approach was part of the MIT-Princeton Team system that took 3rd- and 4th- place in the stowing and picking tasks, respectively at APC 2016.