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ruabliuqiu's Projects

6drepnet

Official Pytorch implementation of 6DRepNet: 6D Rotation representation for unconstrained head pose estimation.

awesome-object-detection

Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html

bag_of_tricks_for_image_classification_with_convolutional_neural_networks

experiments on Paper <Bag of Tricks for Image Classification with Convolutional Neural Networks> and other useful tricks to improve CNN acc

Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.

centernet

Object detection, 3D detection, and pose estimation using center point detection:

centertrack

Simultaneous object detection and tracking using center points.

codeformer

[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer

crnn_plate_recognition

车牌识别 crnn 中文车牌支持12种中文车牌识别

cv-books

These are open and classic books for computer version engineers, it can help us from entry to practice.

data-enhancement

Support data enhancement when there are few data sets（支持数据集较少的情况进行数据增强，包含随机的多种变化）

deep-learning-for-image-processing

deep learning for image processing including classification and object-detection etc.

github-chinese-top-charts

:cn: GitHub中文排行榜，帮助你发现高分优秀中文项目、更高效地吸收国人的优秀经验成果；榜单每周更新一次，敬请关注！

hyperspectral-anomaly-detection-lsunrsorad-and-lsad-cr-idw-

This is the code for the paper nemed 'Anomaly Detection for Hyperspectral Imagery Based on the Regularized Subspace Method and Collaborative Representation'

jetson-cloudnative-demo

Multi-container demo for Jetson Xavier NX and Jetson AGX Xavier

keras-yolov4

yolov4 42.0% mAP.ppyolo 45.1% mAP.

mobilenetv3

An implementation of MobileNetV3 with pyTorch

mtcnn

face detection and alignment with mtcnn

mtcnn_tutorial

As a series of tutorials on the most popular deep learning algorithms for new-entry deep learning research engineers, MTCNN has been widely adopted in industry for human face detection task which is an essential step for subsquential face recognition and facial expression analysis. This tutorial is designed to explain how to implement the algorithm. In this tutorial, developers will learn how to build MTCNN model for face detection task.

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