About

6D pose estimation is the task of detecting the 6D pose of an object, which include its location and orientation. This is an important task in robotics, where a robotic arm needs to know the location and orientation to detect and move objects in its vicinity successfully. This allows the robot to operate safely and effectively alongside humans. The awareness of the position and orientation of objects in a scene is sometimes referred to as 6D, where the D stands for degrees of freedom pose.

( Image credit: Segmentation-driven 6D Object Pose Estimation )

Benchmarks

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Datasets

Greatest papers with code

PVNet: Pixel-wise Voting Network for 6DoF Pose Estimation

CVPR 2019 zju3dv/pvnet

We further create a Truncation LINEMOD dataset to validate the robustness of our approach against truncation.

 Ranked #1 on 6D Pose Estimation using RGB on YCB-Video (Mean AUC metric)

6D POSE ESTIMATION USING RGB

BOP Challenge 2020 on 6D Object Localization

15 Sep 2020DLR-RM/BlenderProc

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.

6D POSE ESTIMATION 6D POSE ESTIMATION USING RGB 6D POSE ESTIMATION USING RGBD DATA AUGMENTATION OBJECT LOCALIZATION

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

1 Nov 2017yuxng/PoseCNN

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.

6D POSE ESTIMATION 6D POSE ESTIMATION USING RGB 6D POSE ESTIMATION USING RGBD

Real-Time Seamless Single Shot 6D Object Pose Prediction

CVPR 2018 Microsoft/singleshotpose

For single object and multiple object pose estimation on the LINEMOD and OCCLUSION datasets, our approach substantially outperforms other recent CNN-based approaches when they are all used without post-processing.

6D POSE ESTIMATION USING RGB DRONE POSE ESTIMATION POSE PREDICTION

HybridPose: 6D Object Pose Estimation under Hybrid Representations

CVPR 2020 chensong1995/HybridPose

Compared to a unitary representation, our hybrid representation allows pose regression to exploit more and diverse features when one type of predicted representation is inaccurate (e. g., because of occlusion).

6D POSE ESTIMATION USING RGB

SSD-6D: Making RGB-based 3D detection and 6D pose estimation great again

ICCV 2017 wadimkehl/ssd-6d

We present a novel method for detecting 3D model instances and estimating their 6D poses from RGB data in a single shot.

6D POSE ESTIMATION 6D POSE ESTIMATION USING RGB

Implicit 3D Orientation Learning for 6D Object Detection from RGB Images

ECCV 2018 DLR-RM/AugmentedAutoencoder

Our novel 3D orientation estimation is based on a variant of the Denoising Autoencoder that is trained on simulated views of a 3D model using Domain Randomization.

 Ranked #1 on 6D Pose Estimation using RGB on T-LESS (Mean Recall metric)

6D POSE ESTIMATION 6D POSE ESTIMATION USING RGB DENOISING OBJECT DETECTION

DeepIM: Deep Iterative Matching for 6D Pose Estimation

ECCV 2018 liyi14/mx-DeepIM

Estimating the 6D pose of objects from images is an important problem in various applications such as robot manipulation and virtual reality.

6D POSE ESTIMATION 6D POSE ESTIMATION USING RGB