3D Shape Classification
29 papers with code • 1 benchmarks • 1 datasets
Image: Sun et al
LibrariesUse these libraries to find 3D Shape Classification models and implementations
With the recent proliferation of deep learning, various deep models with different representations have achieved the state-of-the-art performance.
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).
MVTN exhibits clear performance gains in the tasks of 3D shape classification and 3D shape retrieval without the need for extra training supervision.
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.