Vision-based robotic grasping from object localization, object pose estimation to grasp estimation for parallel grippers: a review
This paper presents a comprehensive survey on vision-based robotic grasping. We
conclude three key tasks during vision-based robotic grasping, which are object localization …
conclude three key tasks during vision-based robotic grasping, which are object localization …
Registration of large-scale terrestrial laser scanner point clouds: A review and benchmark
This study had two main aims:(1) to provide a comprehensive review of terrestrial laser
scanner (TLS) point cloud registration methods and a better understanding of their strengths …
scanner (TLS) point cloud registration methods and a better understanding of their strengths …
[HTML][HTML] Image matching from handcrafted to deep features: A survey
As a fundamental and critical task in various visual applications, image matching can identify
then correspond the same or similar structure/content from two or more images. Over the …
then correspond the same or similar structure/content from two or more images. Over the …
Spinnet: Learning a general surface descriptor for 3d point cloud registration
Extracting robust and general 3D local features is key to downstream tasks such as point
cloud registration and reconstruction. Existing learning-based local descriptors are either …
cloud registration and reconstruction. Existing learning-based local descriptors are either …
Rpm-net: Robust point matching using learned features
Abstract Iterative Closest Point (ICP) solves the rigid point cloud registration problem
iteratively in two steps:(1) make hard assignments of spatially closest point …
iteratively in two steps:(1) make hard assignments of spatially closest point …
Fully convolutional geometric features
Extracting geometric features from 3D scans or point clouds is the first step in applications
such as registration, reconstruction, and tracking. State-of-the-art methods require …
such as registration, reconstruction, and tracking. State-of-the-art methods require …
D3feat: Joint learning of dense detection and description of 3d local features
A successful point cloud registration often lies on robust establishment of sparse matches
through discriminative 3D local features. Despite the fast evolution of learning-based 3D …
through discriminative 3D local features. Despite the fast evolution of learning-based 3D …
The perfect match: 3d point cloud matching with smoothed densities
We propose 3DSmoothNet, a full workflow to match 3D point clouds with a siamese deep
learning architecture and fully convolutional layers using a voxelized smoothed density …
learning architecture and fully convolutional layers using a voxelized smoothed density …
Ppfnet: Global context aware local features for robust 3d point matching
Abstract We present PPFNet-Point Pair Feature NETwork for deeply learning a globally
informed 3D local feature descriptor to find correspondences in unorganized point clouds …
informed 3D local feature descriptor to find correspondences in unorganized point clouds …
Epos: Estimating 6d pose of objects with symmetries
We present a new method for estimating the 6D pose of rigid objects with available 3D
models from a single RGB input image. The method is applicable to a broad range of …
models from a single RGB input image. The method is applicable to a broad range of …