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arcface-caffe

insightface-caffe

awesome-multimodal-large-language-models

:sparkles::sparkles:Latest Papers and Datasets on Multimodal Large Language Models, and Their Evaluation.

cavaface.pytorch

face recognition project(pytorch)

chinese-clip

Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.

chinese-poetry

The most comprehensive database of Chinese poetry 🧶最全中华古诗词数据库, 唐宋两朝近一万四千古诗人, 接近5.5万首唐诗加26万宋诗. 两宋时期1564位词人，21050首词。

clash_for_windows_pkg

A Windows/macOS GUI based on Clash

dancinggaga

AI 尬舞机

darkrank

deeplearning_ai_books

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

diffusion-models-pytorch

Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)

dlcv_for_beginners

《深度学习与计算机视觉》配套代码

erasenet

fsfont

Official PaddlePaddle Implementation of Few-Shot Font Generation by Learning Fine-Grained Local Styles (FsFont)

insightface

Face Recognition Project on MXNet

invoice_fonts

lab

[CVPR 2018] Look at Boundary: A Boundary-Aware Face Alignment Algorithm

lama

🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022

lmdeploy

LMDeploy is a toolkit for compressing, deploying, and serving LLMs.

mtcnn-cpp

C++ implementation of MTCNN

ncnn

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

open-sora-plan

This project aim to reproducing Sora (Open AI T2V model), but we only have limited resource. We deeply wish the all open source community can contribute to this project.

pycorrector

pycorrector is a toolkit for text error correction. 文本纠错，Kenlm，ConvSeq2Seq，BERT，MacBERT，ELECTRA，ERNIE，Transformer，T5等模型实现，开箱即用。

pythonproject

pytorch-ssim

pytorch structural similarity (SSIM) loss

quantizer

这是一个把Caffe模型从浮点转到定点的量化评估工具

resnest

ResNeSt: Split-Attention Network

senet

Squeeze-and-Excitation Networks

senet-caffe

A Caffe Re-Implementation of SENet

some-resources

srnet

A pytorch implementation of the SRNet architecture from the paper Editing text in the wild (Liang Wu et al.)