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hongminli's Projects

advancedeast icon advancedeast

AdvancedEAST is an algorithm used for Scene image text detect, which is primarily based on EAST, and the significant improvement was also made, which make long text predictions more accurate.

algorithm_interview_notes-chinese icon algorithm_interview_notes-chinese

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

c3d icon c3d

C3D is a modified version of BVLC caffe to support 3D ConvNets.

cartographer icon cartographer

Cartographer is a system that provides real-time simultaneous localization and mapping (SLAM) in 2D and 3D across multiple platforms and sensor configurations.

chinese-ocr icon chinese-ocr

基于CTPN(tensorflow)+CRNN(pytorch)+CTC的不定长文本检测和识别

chinese-ocr-1 icon chinese-ocr-1

[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

chinese_ocr icon chinese_ocr

CTPN + DenseNet + CTC based end-to-end Chinese OCR implemented using tensorflow and keras

cnn-slam icon cnn-slam

The combination of CNN and SLAM, aiming to achieve a better result of traditional geometric-based SLAM architecture.

crnn icon crnn

Convolutional Recurrent Neural Network (CRNN) for image-based sequence recognition.

crnn_tensorflow icon crnn_tensorflow

Convolutional Recurrent Neural Networks(CRNN) for Scene Text Recognition

demon icon demon

DeMoN: Depth and Motion Network

densedepth icon densedepth

High Quality Monocular Depth Estimation via Transfer Learning

detectron2 icon detectron2

Detectron2 is FAIR's next-generation research platform for object detection and segmentation.

dfanet icon dfanet

reimpliment of DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation

dso icon dso

Direct Sparse Odometry

east icon east

A tensorflow implementation of EAST text detector

east-crnn icon east-crnn

An end-to-end scene text detection demo based on EAST and CRNN.

east_icpr icon east_icpr

Forked from argman/EAST for the ICPR MTWI 2018 CHALLENGE

espcn icon espcn

A PyTorch implementation of ESPCN based on CVPR 2016 paper "Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network"

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