3D Point Cloud Classification
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Benchmarks
Most implemented
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
Point Transformer
Dynamic Graph CNN for Learning on Point Clouds
PointCNN: Convolution On $\mathcal{X}$-Transformed Points
Perceiver: General Perception with Iterative Attention
PCT: Point cloud transformer
Papers
Benchmarking Federated Learning and Knowledge Distillation for Point Cloud Classification
Deploying 3D point cloud analysis in privacy-sensitive, resource-constrained settings faces two barriers: data cannot be centralized, and models must run on limited edge hardware. We present a multi-seed benchmark jointl…
3D Point Cloud ClassificationKnowledge DistillationFederated LearningTSNN: A Non-parametric and Interpretable Framework for Traffic Time Series Forecasting
Although many complex models were proposed to analyze time series data, some studies have demonstrated remarkable performance with simpler structures. A recent study proposed a non-parametric framework for 3D point cloud…
3D Point Cloud ClassificationTime Series ForecastingLIDARLearn: A Unified Deep Learning Library for 3D Point Cloud Classification, Segmentation, and Self-Supervised Representation Learning
Three-dimensional (3D) point cloud analysis has become central to applications ranging from autonomous driving and robotics to forestry and ecological monitoring. Although numerous deep learning methods have been propose…
parameter-efficient fine-tuning3D Point Cloud ClassificationRepresentation LearningSemantic SegmentationLayered Quantum Architecture Search for 3D Point Cloud Classification
We introduce layered Quantum Architecture Search (layered-QAS), a strategy inspired by classical network morphism that designs Parametrised Quantum Circuit (PQC) architectures by progressively growing and adapting them. …
3D Point Cloud ClassificationHyQuRP: Hybrid quantum-classical neural network with rotational and permutational equivariance
Group-equivariant quantum machine learning has emerged as a promising paradigm by incorporating symmetry into quantum models. However, constructing models simultaneously equivariant to both rotational and permutational s…
3D Point Cloud ClassificationQuantum Machine LearningMapper-GIN: Lightweight Structural Graph Abstraction for Corrupted 3D Point Cloud Classification
Robust 3D point cloud classification is often pursued by scaling up backbones or relying on specialized data augmentation. We instead ask whether structural abstraction alone can improve robustness, and study a simple to…
3D Point Cloud ClassificationGraph ClassificationData Augmentation