3D Shape Classification
23 papers with code • 1 benchmarks • 1 datasets
Image: Sun et al
Convolutional Neural Networks on non-uniform geometrical signals using Euclidean spectral transformation
It has been challenging to analyze signals with mixed topologies (for example, point cloud with surface mesh).
Learning Local Descriptors by Optimizing the Keypoint-Correspondence Criterion: Applications to Face Matching, Learning from Unlabeled Videos and 3D-Shape Retrieval
Current best local descriptors are learned on a large dataset of matching and non-matching keypoint pairs.
Most existing 3D object recognition algorithms focus on leveraging the strong discriminative power of deep learning models with softmax loss for the classification of 3D data, while learning discriminative features with deep metric learning for 3D object retrieval is more or less neglected.