shaoandy1211

shaoandy1211's Stars

• datawhalechina/llm-universe

  本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/

  Language:Jupyter Notebook5.3k630

• Lordog/dive-into-llms

  《动手学大模型Dive into LLMs》系列编程实践教程

  4.1k364

• jerryfeng2003/PointGST

  Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud Learning

  Language:Python12112

• wangzy22/TAP

  [ICCV 2023] Take-A-Photo: 3D-to-2D Generative Pre-training of Point Cloud Models

  Language:Python401

• NVlabs/RADIO

  Official repository for "AM-RADIO: Reduce All Domains Into One"

  Language:Jupyter Notebook89136

• facebookresearch/segment-anything

  The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  Language:Jupyter Notebook48.5k5.7k

• facebookresearch/sam2

  The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  Language:Jupyter Notebook13.6k1.3k

• openai/CLIP

  CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

  Language:Jupyter Notebook27k3.4k

• xingyul/flownet3d

  FlowNet3D: Learning Scene Flow in 3D Point Clouds (CVPR 2019)

  Language:Python36683

• shaoandy1211/laflow

  Multi-line lateral flow reader app

  Language:Jupyter Notebook1

• SheldonFung98/laflow

  Multi-line lateral flow reader app

  Language:Jupyter Notebook31

• antao97/dgcnn.pytorch

  A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)

  Language:Python731151

• Luhuanz/pytorch_project

  llms 大模型 笔记50篇 此仓库包含关于机器学习、深度学习、计算机视觉、自然语言处理、大模型 爬虫等领域 项目实战

  Language:Jupyter Notebook6414

• onwidget/tailnext

  ⭕️ TailNext: Free template using Next.js 14 app router and Tailwind CSS.

  Language:TypeScript360134

• MohamedAfham/CrossPoint

  Official implementation of "CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding" (CVPR, 2022)

  Language:Python24628

• qizekun/PointVisualizaiton

  A point cloud visualization repo

  Language:Python6711

• qizekun/ShapeLLM

  [ECCV 2024] ShapeLLM: Universal 3D Object Understanding for Embodied Interaction

  Language:Python1639

• Jinec98/DHGCN

  [AAAI 2024] The official implementation of DHGCN

  Language:Python104

• fengzhenHIT/OpenCV_Projects

  OpenCV实现计算机视觉项目

  13423

• xbo1/flutter_smart_cropper

  Language:Dart123

• pqpo/SmartCropper

  🔥 A library for cropping image in a smart way that can identify the border and correct the cropped image. 智能图片裁剪框架。自动识别边框，手动调节选区，使用透视变换裁剪并矫正选区；适用于身份证，名片，文档等照片的裁剪。

  Language:Java4k744

• RunpeiDong/ACT

  [ICLR 2023] Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?

  Language:Python1025

• eleander/SiamMAE

  Language:Jupyter Notebook7

• aweers/replicate_siamMAE

  Language:Jupyter Notebook6

• zyh16143998882/ICCV23-IDPT

  The code for the paper "Instance-aware Dynamic Prompt Tuning for Pre-trained Point Cloud Models" (ICCV'23).

  Language:Python1111

• zyh16143998882/AAAI24-PointFEMAE

  The code for the paper "Towards Compact 3D Representations via Point Feature Enhancement Masked Autoencoders" (AAAI'24).

  Language:Python363

• LTH14/rcg

  PyTorch implementation of RCG https://arxiv.org/abs/2312.03701

  Language:Python89740

• Nixtla/nixtla

  TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

  Language:Jupyter Notebook2.5k204

• XiuzeZhou/NASA

  Analysis for NASA data sets

  Language:Jupyter Notebook13643

• allenai/objaverse-xl

  🪐 Objaverse-XL is a Universe of 10M+ 3D Objects. Contains API Scripts for Downloading and Processing!

  Language:Python82751