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mtcnn-pytorch

使用pytorch实现mtcnn的训练及预测，并用pytorch的c++ api实现了前向预测的功能化

multihead_joint_entity_relation_extraction

Implementation of our papers Joint entity recognition and relation extraction as a multi-head selection problem (Expert Syst. Appl, 2018) and Adversarial training for multi-context joint entity and relation extraction (EMNLP, 2018).

nacos-python-sdk

python使用nacos的微服务sdk，以及python的熔断器和限流器

named_entity_recognition

中文命名实体识别（包括多种模型：HMM，CRF，BiLSTM，BiLSTM+CRF的具体实现）

nbce

Naive Bayes-based Context Extension

ncnn

ncnn is a high-performance neural network inference framework optimized for the mobile platform

ner

nerf

Code release for NeRF (Neural Radiance Fields)

nerf-1

nerf

nerf-pytorch

A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.

neuralangelo

Official implementation of "Neuralangelo: High-Fidelity Neural Surface Reconstruction" (CVPR 2023)

nlp-interview-notes

本项目是作者们根据个人面试和经验总结出的自然语言处理(NLP)面试准备的学习笔记与资料，该资料目前包含 自然语言处理各领域的 面试题积累。

nlp-notebook

NLP 领域常见任务的实现，包括新词发现、以及基于pytorch的词向量、中文文本分类、实体识别、摘要文本生成、句子相似度判断等。

nlp-tutorial

Natural Language Processing Tutorial for Deep Learning Researchers

nlp_base

自然语言处理基础，包括文本分类、命名实体识别、机器翻译、阅读理解等

nngen

nni-student-program-2020

NNI Student Program 2020 team repo.

ntk-aware-scaled-rope-exp

nutonomy_pointpillars

Convert pointpillars Pytorch Model To ONNX for TensorRT Inference

oeip

ue4 unity3d ffmpeg cuda dx11

onnx-tensorrt

ONNX-TensorRT: TensorRT backend for ONNX

open_clip

An open source implementation of CLIP.

opencuda

openpcdet

OpenPCDet Toolbox for LiDAR-based 3D Object Detection.

openpcdet-noted

OpenPCDet代码分析与注释

openprompt

An Open-Source Framework for Prompt-Learning.

openpromptstudio

🥣 AIGC 提示词可视化编辑器 | OPS | Open Prompt Studio

optimization-in-a-nutshell

深入浅出最优化系列博客代码 Code of Optimization in a Nutshell

orb_slam2

Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

p-tuning-v2

An optimized deep prompt tuning strategy comparable to fine-tuning across scales and tasks