xinxd1's Stars
Srameo/LED
[ICCV 2023] Lighting Every Darkness in Two Pairs: A Calibration-Free Pipeline for RAW Denoising && [Arxiv 2023] Make Explicit Calibration Implicit: Calibrate Denoiser Instead of the Noise Model
hlh981029/megcup-feedback
RAW-based blind denoising, 1st place in MegCup 2022 (Team Feedback)
DavidQiuChao/PBNFM
An implementation for noise model estimation method of "A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising", CVPR 2020.
Srameo/megcup-feedforward
RAW-based blind denoising, 3rd place in MegCup 2022 (Team Feedforward)
Volcanoscar/HalideRawDenoise
Halide based multi-frame raw domain denoise
nagejacob/RecurrentMobileNet
Light parameters raw image denoising, 2nd place in MegCup 2022
tomassykora/retina-optic-disc-detector
Optic disc detection in a retina image using a fully connected convolutional neural network.
eragonruan/text-detection-ctpn
text detection mainly based on ctpn model in tensorflow, id card detect, connectionist text proposal network
HAIbingshuai/chinese_ocr
中文自然场景文字检测及识别
CodeREWorld/CV-OCR
基于tensorflow、keras/pytorch框架实现图片文字检测及端到端的OCR文字识别
aabbcc1234mxd/OCR
[python3.6] 自然场景文字检测,tf+pytorch实现vgg+ctpn+crnn实现不定长场景文字OCR识别
jakeywu/ocr_torch
ocr_torch是基于Torch1.8实现的DBNet(2.2M) + CRNN(3.8M)实现的轻量级文字检测识别项目(支持onnx推理).
xiaofengShi/CHINESE-OCR
[python3.6] 运用tf实现自然场景文字检测,keras/pytorch实现ctpn+crnn+ctc实现不定长场景文字OCR识别
breezedeus/CnSTD
CnSTD: 基于 PyTorch/MXNet 的 中文/英文 场景文字检测(Scene Text Detection)、数学公式检测(Mathematical Formula Detection, MFD)、篇章分析(Layout Analysis)的Python3 包
chineseocr/chineseocr
yolo3+ocr
Keldos-Li/typora-latex-theme
将Typora伪装成LaTeX的中文样式主题,本科生轻量级课程论文撰写的好帮手。This is a theme disguising Typora into Chinese LaTeX style.
alexklwong/subpixel-embedding-segmentation
PyTorch Implementation of Small Lesion Segmentation in Brain MRIs with Subpixel Embedding (ORAL, MICCAIW 2021)
zhaocc1106/machine_learn
机器学习与深度学习
zhaocc1106/end2end_ml
end-to-end machine learning\deep learning model.
hanghang2333/emotionrecognition
表情识别
Lornatang/machine_learning_in_action_py3
Important book about the machine learning algorithms, and introduces the application of those who use these algorithms and tools, and how to use them in a real environment. This book and other books, behind the other books are long on machine learning theory knowledge, the book happened to be more discussion on how to use coded machine learning algorithms.
MIC-DKFZ/nnUNet
bigmb/Unet-Segmentation-Pytorch-Nest-of-Unets
Implementation of different kinds of Unet Models for Image Segmentation - Unet , RCNN-Unet, Attention Unet, RCNN-Attention Unet, Nested Unet
ShusenTang/Dive-into-DL-PyTorch
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
mrgloom/awesome-semantic-segmentation
:metal: awesome-semantic-segmentation