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Found 5 papers, 3 papers with code
CaSPR: Learning Canonical Spatiotemporal Point Cloud Representations
We propose CaSPR, a method to learn object-centric Canonical Spatiotemporal Point Cloud Representations of dynamically moving or evolving objects.
Quaternion Equivariant Capsule Networks for 3D Point Clouds
We present a 3D capsule module for processing point clouds that is equivariant to 3D rotations and translations, as well as invariant to permutations of the input points.
3D Point Capsule Networks
In this paper, we propose 3D point-capsule networks, an auto-encoder designed to process sparse 3D point clouds while preserving spatial arrangements of the input data.
Ranked #5 on
3D Object Classification
on ModelNet40
Photometric Redshift Estimation for Quasars by Integration of KNN and SVM
The massive photometric data collected from multiple large-scale sky surveys offer significant opportunities for measuring distances of celestial objects by photometric redshifts.
Instrumentation and Methods for Astrophysics
Linearly Supporting Feature Extraction For Automated Estimation Of Stellar Atmospheric Parameters
On real spectra, we extracted 23 features to estimate $T_{eff}$, 62 features for log$~g$, and 68 features for [Fe/H].
