3D Shape Classification
29 papers with code • 1 benchmarks • 1 datasets
Image: Sun et al
Benchmarks
These leaderboards are used to track progress in 3D Shape Classification
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Libraries
Use these libraries to find 3D Shape Classification models and implementations
Pix3D
Latest papers with no code
Adaptive Wavelet Transformer Network for 3D Shape Representation Learning
We present a novel method for 3D shape representation learning using multi-scale wavelet decomposition.
Point Cloud Learning with Transformer
Remarkable performance from Transformer networks in Natural Language Processing promote the development of these models in dealing with computer vision tasks such as image recognition and segmentation.
Potential Convolution: Embedding Point Clouds into Potential Fields
In this work, rather than defining a continuous or discrete kernel, we directly embed convolutional kernels into the learnable potential fields, giving rise to potential convolution.
RocNet: Recursive Octree Network for Efficient 3D Deep Representation
Our network compresses a voxel grid of any size down to a very small latent space in an autoencoder-like network.
Extending DeepSDF for automatic 3D shape retrieval and similarity transform estimation
Recent advances in computer graphics and computer vision have found successful application of deep neural network models for 3D shapes based on signed distance functions (SDFs) that are useful for shape representation, retrieval, and completion.
Joint Supervised and Self-Supervised Learning for 3D Real-World Challenges
Point cloud processing and 3D shape understanding are very challenging tasks for which deep learning techniques have demonstrated great potentials.
Self-supervised Feature Learning by Cross-modality and Cross-view Correspondences
Specifically, 2D image features of rendered images from different views are extracted by a 2D convolutional neural network, and 3D point cloud features are extracted by a graph convolution neural network.
Shape retrieval of non-rigid 3d human models
In addition, further participants have also taken part, and we provide extra analysis of the retrieval results.
Enhancing 2D Representation via Adjacent Views for 3D Shape Retrieval
Multi-view shape descriptors obtained from various 2D images are commonly adopted in 3D shape retrieval.
HRGE-Net: Hierarchical Relational Graph Embedding Network for Multi-view 3D Shape Recognition
We construct a relational graph with multi-view images as nodes, and design relational graph embedding by modeling pairwise and neighboring relations among views.
