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
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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
CosyPose: Consistent multi-view multi-object 6D pose estimation
Second, we develop a robust method for matching individual 6D object pose hypotheses across different input images in order to jointly estimate camera viewpoints and 6D poses of all objects in a single consistent scene.
EfficientPose: An efficient, accurate and scalable end-to-end 6D multi object pose estimation approach
Through the inherent handling of multiple objects and instances and the fused single shot 2D object detection as well as 6D pose estimation, our approach runs even with multiple objects (eight) end-to-end at over 26 FPS, making it highly attractive to many real world scenarios.
GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise Voting
lolrudy/gpv_pose
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CVPR 2022
While 6D object pose estimation has recently made a huge leap forward, most methods can still only handle a single or a handful of different objects, which limits their applications.
T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objects
There are approximately 39K training and 10K test images from each sensor.
BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depth
Microsoft/singleshotpose
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ICCV 2017
We introduce a novel method for 3D object detection and pose estimation from color images only.
DeepIM: Deep Iterative Matching for 6D Pose Estimation
liyi14/mx-DeepIM
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ECCV 2018
Estimating the 6D pose of objects from images is an important problem in various applications such as robot manipulation and virtual reality.
SilhoNet: An RGB Method for 6D Object Pose Estimation
gidobot/SilhoNet
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Autonomous robot manipulation involves estimating the translation and orientation of the object to be manipulated as a 6-degree-of-freedom (6D) pose.
DPOD: 6D Pose Object Detector and Refiner
An additional RGB pose refinement of the initial pose estimates is performed using a custom deep learning-based refinement scheme.
End-to-End Learnable Geometric Vision by Backpropagating PnP Optimization
To seamlessly combine deep learning and geometric vision, it is vital to perform learning and geometric optimization end-to-end.
FS-Net: Fast Shape-based Network for Category-Level 6D Object Pose Estimation with Decoupled Rotation Mechanism
In this paper, we focus on category-level 6D pose and size estimation from monocular RGB-D image.
