C++ Helper Class for Deep Learning Inference Frameworks: TensorFlow Lite, TensorRT, OpenCV, OpenVINO, ncnn, MNN, SNPE, Arm NN, NNabla, ONNX Runtime, LibTorch, TensorFlow

PyTorch implementation of EfficientNetV2 family

My master thesis about optimizing Deep Learning Face recognition models using quantization, pruning and knowledge distillation.

[TNNLS] A Comprehensive Survey of Awesome Visual Transformer Literatures.

New flexible and efficient image generation framework that sets new SOTA on FFHQ-256 with FID 2.05, 2022

A method to increase the speed and lower the memory footprint of existing vision transformers.

[IEEE FG'23] T2V-DDPM: Thermal to Visible Face Translation using Denoising Diffusion Probabilistic Models

Face Super-resolution Using Stochastic Differential Equations

Recognition of Various Common Seal Scans in Complex Environments

rotation detection based on yolov5

Git Re-Basin: Merging Models modulo Permutation Symmetries in PyTorch

Adaface with PartialFC

使用 PyWebIO 部署 PaddleOCR 应用

Curated demo apps made with PyWebIO

基于图像的游戏AI自动化框架

A framework for high-performance medical image processing, neural network inference and visualization

YOLOv5 in PyTorch > ONNX > CoreML > iOS

안녕하세요, 본 공간은 Variational Autoencoder based Anomaly Detection using Reconstruction Probability 논문을 Pytorch로 구현한 코드를 공유하기 위해 설립된 공간입니다.

This page is for the SlimYOLOv3: Narrower, Faster and Better for UAV Real-Time Applications

A collection of popular Data Science Challenges/Competitions || Countdown timers to keep track of the entry deadlines.

codes for ai challenger 2018 machine reading comprehension

🐥A PyTorch implementation of OpenAI's finetuned transformer language model with a script to import the weights pre-trained by OpenAI

Google AI 2018 BERT pytorch implementation

📡 Organized Resources for Deep Learning in Natural Language Processing

Various models and code (Manhattan LSTM, Siamese LSTM + Matching Layer, BiMPM) for the paraphrase identification task, specifically with the Quora Question Pairs dataset.

Deep learning system course

Assignment 1: automatic differentiation