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Shual's Projects

chinese-ocr icon 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

cliquenet icon cliquenet

Convolutional Neural Networks with Alternately Updated Clique (to appear in CVPR 2018)

clustergcn icon clustergcn

A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

cnchar icon cnchar

功能全面的汉字工具库 (拼音 笔画 笔顺 偏旁 成语等) (Chinese character util)

conta icon conta

Implementation for NeurIPS oral paper: Causal Intervention for Weakly-Supervised Semantic Segmentation

contournet icon contournet

A PyTorch implementation of "ContourNet: Taking a Further Step toward Accurate Arbitrary-shaped Scene Text Detection"

cutblur icon cutblur

Rethinking Data Augmentation for Image Super-resolution (CVPR 2020)

cv-backbones icon cv-backbones

CV backbones including GhostNet, TinyNet and TNT, developed by Huawei Noah's Ark Lab.

cvpr2019 icon cvpr2019

cvpr2019/cvpr2018/cvpr2019 papers,极市团队整理

detectron2 icon detectron2

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

differnet icon differnet

This is the official repository to the WACV 2021 paper "Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows" by Marco Rudolph, Bastian Wandt and Bodo Rosenhahn.

drrg icon drrg

Deep relational reasoning graph network for arbitrary shape text detection; Accepted by CVPR 2020 (Oral). http://arxiv.org/abs/2003.07493

east icon east

PyTorch Re-Implementation of EAST: An Efficient and Accurate Scene Text Detector

efifstr icon efifstr

[ACM MM 2020] Exploring Font-independent Features for Scene Text Recognition

electron-ssr-backup icon electron-ssr-backup

electron-ssr原作者删除了这个伟大的项目,故备份了下来,不继续开发,且用且珍惜

faceqnet icon faceqnet

FaceQnet: Quality Assessment for Face Recognition based on Deep Learning

gpt-2 icon gpt-2

Code for the paper "Language Models are Unsupervised Multitask Learners"

gpt2-chinese icon gpt2-chinese

Chinese version of GPT2 training code, using BERT tokenizer.

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