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Found 12 papers, 6 papers with code
TrackAgent: 6D Object Tracking via Reinforcement Learning
Tracking an object's 6D pose, while either the object itself or the observing camera is moving, is important for many robotics and augmented reality applications.
COPE: End-to-end trainable Constant Runtime Object Pose Estimation
We present an approach that learns an intermediate geometric representation of multiple objects to directly regress 6D poses of all instances in a test image.
SporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement
Observational noise, inaccurate segmentation and ambiguity due to symmetry and occlusion lead to inaccurate object pose estimates.
ReAgent: Point Cloud Registration using Imitation and Reinforcement Learning
Point cloud registration is a common step in many 3D computer vision tasks such as object pose estimation, where a 3D model is aligned to an observation.
Sim2Real 3D Object Classification using Spherical Kernel Point Convolution and a Deep Center Voting Scheme
While object semantic understanding is essential for most service robotic tasks, 3D object classification is still an open problem.
PyraPose: Feature Pyramids for Fast and Accurate Object Pose Estimation under Domain Shift
We also perform grasping experiments in the real world to demonstrate the advantage of using synthetic data to generalize to novel environments.
Neural Object Learning for 6D Pose Estimation Using a Few Cluttered Images
Recent methods for 6D pose estimation of objects assume either textured 3D models or real images that cover the entire range of target poses.
DGCM-Net: Dense Geometrical Correspondence Matching Network for Incremental Experience-based Robotic Grasping
This article presents a method for grasping novel objects by learning from experience.
Robotics
Addressing the Sim2Real Gap in Robotic 3D Object Classification
In this work, we examine this gap in a robotic context by specifically addressing the problem of classification when transferring from artificial CAD models to real reconstructed objects.
VeREFINE: Integrating Object Pose Verification with Physics-guided Iterative Refinement
The generality of the approach is shown by using three state-of-the-art pose estimators and three baseline refiners.
Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimation
Estimating the 6D pose of objects using only RGB images remains challenging because of problems such as occlusion and symmetries.
Ranked #1 on
6D Pose Estimation using RGB
on T-LESS
EasyLabel: A Semi-Automatic Pixel-wise Object Annotation Tool for Creating Robotic RGB-D Datasets
This paper presents the EasyLabel tool for easily acquiring high quality ground truth annotation of objects at the pixel-level in densely cluttered scenes.
