Web尽管 PointNet++ 的准确性已被 PointMLP 和 Point Transformer 等最近的网络在很大程度上超越，但我们发现很大一部分性能提升是由于改进了训练策略，即数据增强和优化技术，以及增加了模型大小而不是架构创新。. 因此，PointNet++ 的全部潜力还有待探索。. 在这项工作 ... WebPointMLP PointMLP - elite 92.3 92.8 93.3 93.8 94.3 0 30 60 90 120 150 180 y Inference speed (samples/second) Figure 1: Accuracy-speed tradeoff on Model-Net40. Our PointMLP performs best. Please refer to Section4for details. In this paper, we aim at the ambitious goal of build-ing a deep network for point cloud analysis using
PointNeXt: Revisiting PointNet++ with Improved Training and …
WebPointMLP：Rethinking Network Design and Local Geometry in Point Cloud： A Simple Residual MLP Framework . ICLR 20241. 四个问题解决什么问题点云随着CV领域的发展而发展（毕竟点云属于CV领域），先前的工作主要从设计局部特征提取器出发，所用方法有convolution, graph, or attention mechanisms。 WebJul 30, 2024 · PointMLP：Rethinking Network Design and Local Geometry in Point Cloud： A Simple Residual MLP Framework . ICLR 20241. 四个问题解决什么问题点云随着CV领 … ps5 streaming stopping
arXiv:2202.07123v2 [cs.CV] 29 Nov 2024
WebPointNeXt can be flexibly scaled up and outperforms state-of-the-art methods on both 3D classification and segmentation tasks. For classification, PointNeXt reaches an overall accuracy of 87.7% on ScanObjectNN, surpassing PointMLP by 2.3%, while being 10× faster in inference. For semantic segmentation, PointNeXt establishes a new state-of-the ... WebApr 12, 2024 · PointMLP 在多个数据集上大放异彩，刷新了多个数据集的最好成绩。 不仅大幅提高了分类的准确率，还提供了更快的推理速度。 值得注意的是，在 ScanObject NN 上，PointMLP 取得了 85.4% 的分类准确率（该研究给出代码的准确率达到 86.1%），大幅超越第二名的 82.8%。 WebDec 21, 2024 · Extensibility: supports many representative networks for point cloud understanding, such as PointNet, DGCNN, DeepGCN, PointNet++, ASSANet, … retro 7 sweater clothing