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pyntcloud is a Python library for working with 3D point clouds.
EMNLP 2018: Multi-Head Attention with Disagreement Regularization; NAACL 2019: Information Aggregation for Multi-Head Attention with Routing-by-Agreement
✨ 易上手的多平台 LLM 聊天机器人及开发框架 ✨ 平台支持 QQ、QQ频道、Telegram、微信、企微、飞书 | MCP 服务器、OpenAI、DeepSeek、Gemini、硅基流动、月之暗面、Ollama、OneAPI、Dify 等。附带 WebUI。
PointNAT: Large Scale Point Cloud Semantic Segmentation via Neighbor Aggregation with Transformer
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
Implementation of the OPPGC algorithm
Official repository for paper "Attention-based Point Cloud Edge Sampling" (APES), Highlight@CVPR 2023
This project aims to enhance the working environment on Windows
这是一个用于显示当前网速、CPU及内存利用率的桌面悬浮窗软件，并支持任务栏显示，支持更换皮肤。
OpenPoints: a library for easily reproducing point-based methods for point cloud understanding. The engine for [PointNeXt](https://arxiv.org/abs/2206.04670)
Official pytorch implementation of "Self-positioning Point-based Transformer for Point Cloud Understanding" (CVPR 2023).
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
Ranger - a synergistic optimizer using RAdam (Rectified Adam), Gradient Centralization and LookAhead in one codebase
Experiments with Pointnet and GAPNet/GAPointNet. Attention and transformers for point clouds.
🎉 (RuoYi)官方仓库 基于SpringBoot的权限管理系统 易读易懂、界面简洁美观。 核心技术采用Spring、MyBatis、Shiro没有任何其它重度依赖。直接运行即可用
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An interactive NVIDIA-GPU process viewer and beyond, the one-stop solution for GPU process management.
This is a net speed monitor just like 360 for windows user.
3D-ReConstnet: A Single-View 3D-Object Point Cloud Reconstruction Network for more details,please see this link:and please cite our paper: https://ieeexplore.ieee.org/document/9086481?source=author…
Split audio using the .srt file, clean up annotations, then merge and package into a format suitable for bert-vits2 in a standard manner. 使用.srt文件分割音频并清洗标注，合并封装至适用于bert-vits2的一个较为标准的格式
Handwriting Synthesis with RNNs ✏️
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
3D point cloud datasets in HDF5 format, containing uniformly sampled 2048 points per shape.