The recently developed pure transformer architectures have attained promising accuracy on point cloud learning benchmarks compared to convolutional neural networks. However, existing Transformers are computationally expensive because they waste a significant amount of time structuring irregular data. To solve this shortcoming, we present the Sparse Window Attention module gather coarse-grained ...

A remotely pumped Erbium-doped system for the amplification of an optical signal long-reach (LR) next-generation passive networks (NG-PONs) is presented in this paper. The will be deployed with/over current point to multi-point technology with/without backward compatibility. Remote pumping allows extending reach distribution and magnification splitting ratio as well, which most important increa...

In this work, we present Point Transformer, a deep neural network that operates directly on unordered and unstructured point sets. We design Transformer to extract local global features relate both representations by introducing the local-global attention mechanism, which aims capture spatial relations shape information. For purpose, propose SortNet, as part of induces input permutation invaria...