Overview of Point Transformer V3 (PTv3). Compared to its predecessor, PTv2 [90], our PTv3 shows superiority in the following aspects: 1. Stronger performance. PTv3 achieves state-of …

This repo is the official project repository of the paper Point Transformer V3: Simpler, Faster, Stronger and is mainly used for releasing schedules, updating instructions, sharing experiment …

Dec 16, 2020 · We design self-attention layers for point clouds and use these to construct self-attention networks for tasks such as semantic scene segmentation, object part segmentation, …

Jun 2, 2024 · PT is a 3D point cloud processing network that utilizes ‘Self-Attention’. PT can perform Semantic Segmentation, Part Segmentation and Object Classification of 3D point …

We design self-attention layers for point clouds and use these to construct self-attention networks for tasks such as semantic scene segmentation, object part segmentation, and object …

This repository reproduces Point Transformer. The codebase is provided by the first author of Point Transformer. For shape classification and part segmentation, please use paconv …

Dec 15, 2023 · Therefore, we present Point Transformer V3 (PTv3), which prioritizes simplicity and efficiency over the accuracy of certain mechanisms that are minor to the overall …

We design Point Transformer to extract local and global features and relate both representations by introducing the local-global attention mechanism, which aims to capture spatial point …

Jan 1, 2022 · We propose a novel end-to-end graph autoencoders model for the attributed graph. The proposed model can reconstruct both the graph structure and node attributes. The graph …

In this paper, we present the graph attention auto-encoder (GATE), a neural network architecture for unsupervised representation learning on graph-structured data. Our architecture is able to …