6D Pose Estimation using RGB
86 papers with code • 6 benchmarks • 6 datasets
6D Pose Estimation using RGB refers to the task of determining the six degree-of-freedom (6D) pose of an object in 3D space based on RGB images. This involves estimating the position and orientation of an object in a scene, and is a fundamental problem in computer vision and robotics. In this task, the goal is to estimate the 6D pose of an object given an RGB image of the object and the scene, which can be used for tasks such as robotic manipulation, augmented reality, and scene reconstruction.
( Image credit: Segmentation-driven 6D Object Pose Estimation )
Benchmarks
These leaderboards are used to track progress in 6D Pose Estimation using RGB
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
Libraries
Use these libraries to find 6D Pose Estimation using RGB models and implementations
YCB-Video
T-LESS
LM
ApolloCar3D
Fraunhofer IPA Bin-Picking
Drunkard's Dataset
Most implemented papers
Wide-Depth-Range 6D Object Pose Estimation in Space
cvlab-epfl/wide-depth-range-pose
•
•
CVPR 2021
6D pose estimation in space poses unique challenges that are not commonly encountered in the terrestrial setting.
DexYCB: A Benchmark for Capturing Hand Grasping of Objects
NVlabs/dex-ycb-toolkit
•
•
CVPR 2021
We introduce DexYCB, a new dataset for capturing hand grasping of objects.
SO-Pose: Exploiting Self-Occlusion for Direct 6D Pose Estimation
shangbuhuan13/so-pose
•
•
ICCV 2021
Directly regressing all 6 degrees-of-freedom (6DoF) for the object pose (e. g. the 3D rotation and translation) in a cluttered environment from a single RGB image is a challenging problem.
ROFT: Real-Time Optical Flow-Aided 6D Object Pose and Velocity Tracking
In this work, we introduce ROFT, a Kalman filtering approach for 6D object pose and velocity tracking from a stream of RGB-D images.
Templates for 3D Object Pose Estimation Revisited: Generalization to New Objects and Robustness to Occlusions
nv-nguyen/template-pose
•
•
CVPR 2022
It relies on a small set of training objects to learn local object representations, which allow us to locally match the input image to a set of "templates", rendered images of the CAD models for the new objects.
EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation
In this paper, we propose the EPro-PnP, a probabilistic PnP layer for general end-to-end pose estimation, which outputs a distribution of pose with differentiable probability density on the SE(3) manifold.
Rigidity-Aware Detection for 6D Object Pose Estimation
yanghai-1218/radet
•
•
CVPR 2023
To address this, we propose a rigidity-aware detection method exploiting the fact that, in 6D pose estimation, the target objects are rigid.
SSD-6D: Making RGB-based 3D detection and 6D pose estimation great again
wadimkehl/ssd-6d
•
•
ICCV 2017
We present a novel method for detecting 3D model instances and estimating their 6D poses from RGB data in a single shot.
BOP: Benchmark for 6D Object Pose Estimation
We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image.
Implicit 3D Orientation Learning for 6D Object Detection from RGB Images
DLR-RM/AugmentedAutoencoder
•
•
ECCV 2018
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.
