6D Pose Estimation using RGBD

13 papers with code • 6 benchmarks • 2 datasets

Image: Zeng et al

Libraries

Use these libraries to find 6D Pose Estimation using RGBD 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.

The CoSTAR Block Stacking Dataset: Learning with Workspace Constraints

jhu-lcsr/costar_plan 27 Oct 2018

We show that a mild relaxation of the task and workspace constraints implicit in existing object grasping datasets can cause neural network based grasping algorithms to fail on even a simple block stacking task when executed under more realistic circumstances.

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.

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.

6-PACK: Category-level 6D Pose Tracker with Anchor-Based Keypoints

j96w/6-PACK 23 Oct 2019

We present 6-PACK, a deep learning approach to category-level 6D object pose tracking on RGB-D data.

CenterSnap: Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimation

zubair-irshad/CenterSnap 3 Mar 2022

This paper studies the complex task of simultaneous multi-object 3D reconstruction, 6D pose and size estimation from a single-view RGB-D observation.

BOP: Benchmark for 6D Object Pose Estimation

thodan/bop_toolkit ECCV 2018

We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image.

MaskedFusion: Mask-based 6D Object Pose Estimation

kroglice/MaskedFusion 18 Nov 2019

MaskedFusion is a framework to estimate the 6D pose of objects using RGB-D data, with an architecture that leverages multiple sub-tasks in a pipeline to achieve accurate 6D poses.