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(ICCV 2023) Uni-3D: A Universal Model for Panoptic 3D Scene Reconstruction
Vector (and Scalar) Quantization, in Pytorch
LaVIT: Empower the Large Language Model to Understand and Generate Visual Content
Implementation of MagViT2 Tokenizer in Pytorch
Official JAX implementation of MAGVIT: Masked Generative Video Transformer
[ACL 2023] Reasoning with Language Model Prompting: A Survey
ImageBind One Embedding Space to Bind Them All
An open source implementation of CLIP.
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.
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
A curated list of reinforcement learning with human feedback resources (continually updated)
为GPT/GLM等LLM大语言模型提供实用化交互接口,特别优化论文阅读/润色/写作体验,模块化设计,支持自定义快捷按钮&函数插件,支持Python和C++等项目剖析&自译解功能,PDF/LaTex论文翻译&总结功能,支持并行问询多种LLM模型,支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, m…
Sports_Game_tracker是基于飞桨深度学习框架的实时行人分析工具PP-Human进行功能扩展的球赛识别追踪工具,目前的功能有:足球球员追踪、足球控球检测、足球检测。
pytorch implementation of openpose including Hand and Body Pose Estimation.
This repo includes ChatGPT prompt curation to use ChatGPT better.
Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.
YOLOv7 Pose estimation using OpenCV, PyTorch
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
Real-Time Spatio-Temporally Localized Activity Detection by Tracking Body Keypoints
Repository containing all necessary codes to get started on the SoccerNet Action Spotting challenge. This repository also contains several benchmark methods.
Conditional diffusion model to generate MNIST. Minimal script. Based on 'Classifier-Free Diffusion Guidance'.
A minimal yet resourceful implementation of diffusion models (along with pretrained models + synthetic images for nine datasets)