Supervised Only 3D Point Cloud Classification
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Benchmarks
ScanObjectNN
Most implemented
Attention Is All You Need
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
Dynamic Graph CNN for Learning on Point Clouds
Papers
Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model
Existing Transformer-based models for point cloud analysis suffer from quadratic complexity, leading to compromised point cloud resolution and information loss. In contrast, the newly proposed Mamba model, based on state…
3D Point Cloud ClassificationMambaState Space ModelsSupervised Only 3D Point Cloud ClassificationPoint Cloud Mamba: Point Cloud Learning via State Space Model
Recently, state space models have exhibited strong global modeling capabilities and linear computational complexity in contrast to transformers. This research focuses on applying such architecture to more efficiently and…
MambaState Space ModelsSupervised Only 3D Point Cloud ClassificationDecoupled Local Aggregation for Point Cloud Learning
The unstructured nature of point clouds demands that local aggregation be adaptive to different local structures. Previous methods meet this by explicitly embedding spatial relations into each aggregation process. Althou…
3D Point Cloud ClassificationSemantic SegmentationSupervised Only 3D Point Cloud ClassificationSelf-positioning Point-based Transformer for Point Cloud Understanding
Transformers have shown superior performance on various computer vision tasks with their capabilities to capture long-range dependencies. Despite the success, it is challenging to directly apply Transformers on point clo…
3D Part Segmentation3D Point Cloud ClassificationScene SegmentationSemantic Segmentation+1Parameter is Not All You Need: Starting from Non-Parametric Networks for 3D Point Cloud Analysis
We present a Non-parametric Network for 3D point cloud analysis, Point-NN, which consists of purely non-learnable components: farthest point sampling (FPS), k-nearest neighbors (k-NN), and pooling operations, with trigon…
3D Point Cloud ClassificationAllSupervised Only 3D Point Cloud ClassificationTraining-free 3D Part Segmentation+1Point Cloud Classification Using Content-based Transformer via Clustering in Feature Space
Recently, there have been some attempts of Transformer in 3D point cloud classification. In order to reduce computations, most existing methods focus on local spatial attention, but ignore their content and fail to estab…
3D Point Cloud ClassificationClassificationClusteringPoint Cloud Classification+1