3D Shape Classification
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Benchmarks
Pix3D
Most implemented
Deep Learning for 3D Point Clouds: A Survey
Masked Discrimination for Self-Supervised Learning on Point Clouds
Learning Equivariant Representations
MVTN: Multi-View Transformation Network for 3D Shape Recognition
Convolutional Neural Networks on non-uniform geometrical signals using Euclidean spectral transformation
MeshNet: Mesh Neural Network for 3D Shape Representation
Papers
Optimizing Multi-Modal Models for Image-Based Shape Retrieval: The Role of Pre-Alignment and Hard Contrastive Learning
Image-based shape retrieval (IBSR) aims to retrieve 3D models from a database given a query image, hence addressing a classical task in computer vision, computer graphics, and robotics. Recent approaches typically rely o…
3D Shape ClassificationContrastive LearningMetric LearningPoint CloudsBenchmark-Ready 3D Anatomical Shape Classification
Progress in anatomical 3D shape classification is limited by the complexity of mesh data and the lack of standardized benchmarks, highlighting the need for robust learning methods and reproducible evaluation. We introduc…
3D Shape ClassificationAttention Maps in 3D Shape Classification for Dental Stage Estimation with Class Node Graph Attention Networks
Deep learning offers a promising avenue for automating many recognition tasks in fields such as medicine and forensics. However, the black-box nature of these models hinders their adoption in high-stakes applications whe…
3D Shape ClassificationA comprehensive overview of deep learning techniques for 3D point cloud classification and semantic segmentation
Point cloud analysis has a wide range of applications in many areas such as computer vision, robotic manipulation, and autonomous driving. While deep learning has achieved remarkable success on image-based tasks, there a…
3D Point Cloud Classification3D Shape ClassificationAutonomous DrivingDeep Learning+2Interpretable3D: An Ad-Hoc Interpretable Classifier for 3D Point Clouds
3D decision-critical tasks urgently require research on explanations to ensure system reliability and transparency. Extensive explanatory research has been conducted on 2D images, but there is a lack in the 3D field. Fur…
3D Shape ClassificationEnsemble Quadratic Assignment Network for Graph Matching
Graph matching is a commonly used technique in computer vision and pattern recognition. Recent data-driven approaches have improved the graph matching accuracy remarkably, whereas some traditional algorithm-based methods…
3D Shape ClassificationGPUGraph MatchingGraph Neural Network