3D Shape Recognition
13 papers with code • 0 benchmarks • 1 datasets
Image: Wei et al
Benchmarks
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Libraries
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Hypersim
Latest papers with no code
Group Multi-View Transformer for 3D Shape Analysis with Spatial Encoding
The large model GMViT achieves excellent 3D classification and retrieval results on the benchmark datasets ModelNet, ShapeNetCore55, and MCB.
MV-CLIP: Multi-View CLIP for Zero-shot 3D Shape Recognition
Consequently, this paper aims to improve the confidence with view selection and hierarchical prompts.
ViewFormer: View Set Attention for Multi-view 3D Shape Understanding
This paper presents ViewFormer, a simple yet effective model for multi-view 3d shape recognition and retrieval.
Contrastive Learning of 3D Shape Descriptor with Dynamic Adversarial Views
In addition, CoLAV introduces a novel mechanism for the dynamic generation of shape-instance-dependent adversarial views as positive pairs to adversarially train robust contrastive learning models towards the learning of more informative 3D shape representation.
LATFormer: Locality-Aware Point-View Fusion Transformer for 3D Shape Recognition
To investigate this, we propose a novel Locality-Aware Point-View Fusion Transformer (LATFormer) for 3D shape retrieval and classification.
Auto-MVCNN: Neural Architecture Search for Multi-view 3D Shape Recognition
In 3D shape recognition, multi-view based methods leverage human's perspective to analyze 3D shapes and have achieved significant outcomes.
Invariant 3D Shape Recognition using Predictive Modular Neural Networks
It is presented in the context of 3D invariant shape recognition and texture recognition.
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.
MANet: Multimodal Attention Network based Point- View fusion for 3D Shape Recognition
More specifically, we obtain the enhanced multi-view features by mining the contribution of each multi-view image to the overall shape recognition, and then fuse the point-cloud features and the enhanced multi-view features to obtain a more discriminative 3D shape descriptor.
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.
