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William's note

啃遍华科图书馆

      突然想起来自己也算是自幼长在书堆里。卧室一个不大不小的书架。底层放的是我的注音版小说,童话书,漫画书等等。中层全是姐姐的书,第一篇古文读的是姐姐的初中课本里的《小石潭记》,那时自然是读不懂的,看标题以为是童话故事,翻开来看得只皱眉头。旁边一格全是《少年月刊》《青年文摘》等等,可喜的是一期不差,连载小说总能看个齐全,金钟罩,铁布衫,航天器,遁地机,武侠科幻样样俱全。哦,自然也少不了《黄岗兵法》这样的习题参考书,讨厌至极。暑假借了邻居的《成语大全》,想据为己有,干脆手抄一整本装订成册。《唐诗宋词三百首》里看了大量中国水墨画,书...

      突然想起来自己也算是自幼长在书堆里。卧室一个不大不小的书架。底层放的是我的注音版小说,童话书,漫画书等等。中层全是姐姐的书,第一篇古文读的是姐姐的初中课本里的《小石潭记》,那时自然是读不懂的,看标题以为是童话故事,翻开来看得只皱眉头。旁边一格全是《少年月刊》《青年文摘》等等,可喜的是一期不差,连载小说总能看个齐全,金钟罩,铁布衫,航天器,遁地机,武侠科幻样样俱全。哦,自然也少不了《黄岗兵法》这样的习题参考书,讨厌至极。暑假借了邻居的《成语大全》,想据为己有,干脆手抄一整本装订成册。《唐诗宋词三百首》里看了大量中国水墨画,书架底层的一沓沓账本给我当了稿纸,拆了爷爷加工厂的零件当镇纸,拿毛笔装模做样随意绘画。锯了厨房里偷来的竹筷,拿毛线捆成竹简抄录宋词。买新书舍不得一次读完,拿爷爷的老算盘计算着每天应读的页数,《格列佛游记》每天看30页,《汤姆逊漂流记》每天看28页。书架顶层全是父亲的书,落灰虫蛀老朽,也够我折腾一番,拿父亲的外科医学书探寻男女身体的奥秘,偷走《鬼谷子》换了同学的《三国演义》,剪了风扇叶子给《真实毛泽东》当书签,去亲戚家做客借走《三个火枪手》。早读课偷看《少年周恩来》,午休偷看《战国故事》被当小黄书抓...幼时书少,遇到总是如饥似渴。如今书多了,反倒日渐懒惰,高中只看点杂志,厚实的书,没机会也不再爱读了。刚至大学,有着啃遍华中大图书馆的宏愿,哪知快毕业了也不知检书码为何意?哀哉!哀哉!所幸,浮生偷得半年清闲,尚可驻扎图书馆!

William's note
谁说历史不重演? ——中国旧式...

谁说历史不重演?
        ——中国旧式家庭的历史周期律

谁说历史不重演?
        ——中国旧式家庭的历史周期律

William's note
功绩归自己,失败怨别人 ——失...

功绩归自己,失败怨别人
                    ——失败者的亚子

功绩归自己,失败怨别人
                    ——失败者的亚子

William's note
英雄迟暮,不提年少之勇。

英雄迟暮,不提年少之勇。

英雄迟暮,不提年少之勇。

William's note
我有两样东西不会,这也不会,那...

我有两样东西不会,这也不会,那也不会。
                                        ————《历史荷尔蒙》

可我不是富二代

我有两样东西不会,这也不会,那也不会。
                                        ————《历史荷尔蒙》

可我不是富二代

湛天雲海碧波影

ICDAR 2019 Robust Reading Challenge on Scanned Receipts OCR and Information Extraction Results


SROIE Introduction:

Scanned receipts OCR is a process of recognizing text from scanned structured and semi-structured receipts, and invoices in general. On the other hand, extracting key texts from receipts...

ICDAR 2019 Robust Reading Challenge on Scanned Receipts OCR and Information Extraction Results


SROIE Introduction:

Scanned receipts OCR is a process of recognizing text from scanned structured and semi-structured receipts, and invoices in general. On the other hand, extracting key texts from receipts and invoices and save the texts to structured documents can serve many applications and services, such as efficient archiving, fast indexing and document analytics. Scanned receipts OCR and information extraction (SROIE) play critical roles in streamlining document-intensive processes and office automation in many financial, accounting and taxation areas. However, SROIE also faces big challenges. With performance greatly boosted by recent breakthroughs in deep learning technologies in terms of accuracy and processing speed, OCR is becoming mature for many practical tasks (such as name card recognition, license plate recognition and hand-written text recognition). However, receipts OCR has much higher accuracy requirements than the general OCR tasks for many commercial applications. And SROIE becomes more challenging when the scanned receipts have low quality. Therefore, in the existing SROIE systems, human resources are still heavily used in SROIE. There is an urgent need to research and develop fast, efficient and robust SROIE systems to reduce and even eliminate manual work.


 

Task 1 - Scanned Receipt Text Localisation
Hmean Ranking Table
Rank Team Name Team Members Insititute Recall Precision Hmean
1 SCUT-DLVC-Lab-Refinement Jiapeng Wang*, Yan Li*, Tianwei Wang, Jiaxin Zhang, Yichao Huang, Canjie Luo, Kai Ding, Lianwen Jin (*equal contribution) South China University of Technology, INTSIG Information Co. Ltd 98.64% 98.53% 98.59%
2 Ping An Property & Casualty Insurance Company Xianbiao Qi, Ning Lu, Yuan Gao, Yihao Chen, Shaoqiong Chen, Wenwen Yu, Rong Xiao Ping An Property & Casualty Insurance Company 98.60% 98.40% 98.50%
3 H&H Lab HUST_VLRGROUP(Mengde Xu, Zhen Zhu, Hui Zhang, Mingkun Yang, Jiehua Yang) & HUAWEI_CLOUD_EI(Jing Wang, Yibin Ye, Shenggao Zhu, Dandan Tu) Huazhong University of Science and Technology & Huawei Technologies Co. Ltd Joint Laboratory 97.93% 97.95% 97.94%
4 Psenet_dcn Xiufeng Jiang - 96.62% 96.21% 96.42%
5 BOE_IOT_AIBD v5 BOE_IOT_AIBD - 95.95% 95.99% 95.97%
6 EM_ocr Hao Wu, Na He, Zhou Shen, Dan Meng, Qingfeng Wang - 95.85% 96.08% 95.97%
7 Clova OCR Seung Shin, Sungrae Park, Seonghyeon Kim, Jaeheung Surh, Junyeop Lee, Hwalsuk Lee Clova AI Research, NAVER Corp 96.04% 95.79% 95.92%
8 IFLYTEK-textDet_v3 IFLYTEK IFLYTEK 93.77% 95.89% 94.81%
9 A Single-Shot Model for Robust Text Localization Hanqin Wang, Jie Qin, Fan Zhu, Li Liu, and Ling Shao Inception Institute of Artificial Intelligence 93.93% 94.80% 94.37%
10 SituTech_OCR Kui Lyu, Tianhao Tang, Minghao Wang SituTech 93.81% 94.18% 94.00%

 


Task 2 - Scanned Receipt OCR
Hmean Ranking Table
Rank Team Name Team Members Insititute Recall Precision Hmean
1 H&H Lab HUST_VLRGROUP(Hui Zhang, Mingkun Yang, Mengde Xu, Zhen Zhu, Jiehua Yang) & HUAWEI_CLOUD_EI(Jing Wang, Yibin Ye, Shenggao Zhu, Dandan Tu) Huazhong University of Science and Technology & Huawei Technologies Co. Ltd Joint Laboratory 96.35% 96.52% 96.43%
2 HeReceipt-Ensemble Yichao Huang*, Tianwei Wang*, Jiaxin Zhang*, Yan Li, Jiapeng Wang, Canjie Luo, Kai Ding, Lianwen Jin (*equal contribution) INTSIG Information Co. Ltd, South China University of Technology 94.56% 95.10% 94.82%
3 Ping An Property & Casualty Insurance Company Xianbiao Qi, Yihao Chen, Shaoqiong Chen, Ning Lu, Yuan Gao, Wenwen Yu, Rong Xiao Ping An Property & Casualty Insurance Company 94.48% 94.86% 94.67%
4 CLOVA OCR Sungrae Park, Seung Shin, Seonghyeon Kim, Jaeheung Surh, Junyeop Lee, Hwalsuk Lee Clova AI Research, NAVER Corp 94.30% 94.88% 94.59%
5 SCUT-DLVC-Lab-Lexicon Tianwei Wang*, Jiaxin Zhang*, Yichao Huang*, Jiapeng Wang, Yan Li, Canjie Luo, Kai Ding, Lianwen Jin (*equal contribution) South China University of Technology, INTSIG Information Co. Ltd 94.18% 94.88% 94.53%
6 DenseNet-Attention Recognition PINGAN Tech PINGAN Tech 94.29% 94.58% 94.44%
7 CITlab Argus Text Recognition Tobias Grüning, Gundram Leifert, Jochen Zöllner, Tobias Strauß, Roger Labahn CITlab 93.55% 93.61% 93.58%
8 Unet followed by CRNN with CTC Roberto Lotufo, Ramon Pires - 88.58% 87.30% 87.93%
9 BOE_IOT_AIBD T2 V5 BOE_IOT_AIBD - 87.84% 86.66% 87.24%
10 CRNN after UNet Segmentation Roberto Lotufo, Ramon Pires, Israel Campiotti, Rubens Machado, Luis Serrano, Giovanni Garuffi - 85.77% 86.48% 86.12

 


Task 3 - Key Information Extraction from Scanned Receipts
Hmean Ranking Table
Rank Team Name Team Members Insititute Recall Precision Hmean
1 Ping An Property & Casualty Insurance Company Xianbiao Qi, Wenwen Yu, Ning Lu, Yihao Chen, Shaoqiong Chen, Yuan Gao, Rong Xiao Ping An Property & Casualty Insurance Company 90.49% 90.49% 90.49%
2 EAST det + Multi-class classification liyulin, v_huangju, xiequnyi, qinxiameng Baidu 89.70% 89.70% 89.70%
3 H&H Lab HUST_VLRGROUP(Hui Zhang, Mengde Xu, Mingkun Yang, Zhen Zhu, Jiehua Yang) & HUAWEI_CLOUD_EI(Jing Wang, Yibin Ye, Shenggao Zhu, Dandan Tu) Huazhong University of Science and Technology & Huawei Technologies Co. Ltd Joint Laboratory 89.63% 89.63% 89.63%
4 CLOVA OCR Sungrae Park, Seonghyeon Kim, Seung Shin, Jaeheung Surh, Junyeop Lee, Hwalsuk Lee Clova AI Research, NAVER Corp 89.05% 89.05% 89.05%
5 NiuBiHongHong Ge daye - 87.61% 87.61% 87.61%
6 HeReceipt-withoutRM Hanmin Duan, Zhiqin Lu, Yang Chang, Yan Li, Yichao Huang, Kai Ding INTSIG Information Co. Ltd, South China University of Technology 83.00% 83.24% 83.12%
7 BOE_IOT_AIBD_v3 BOE_IOT_AIBD - 82.71% 82.71% 82.71%
8 PATECH_CHENGDU_OCR JunKun Zhou, Ming Guan, ZhengNan Luo, MingTao Wang, YuBin Xiao, MingBin Hou - 81.70% 82.29% 82.00%
9 NER with spaCy model Roberto Lotufo, Giovani Garuffi, Israel Campiotti, Ramon Pires, Rubens Machado, Luis Serrano - 78.96% 79.02% 78.99%
10 CITlab Argus Information Extraction (positional & line features, enhanced gt) Tobias Strauß, Tobias Grüning, Gundram Leifert, Jochen Zöllner, Roger Labahn CITlab 77.38% 77.38% 77.38%

 

Result Link:
http://www.onlyou.com/sroie/index.html

 

噪郁青年
十一不喝酒,返校徒伤悲

十一不喝酒,返校徒伤悲

十一不喝酒,返校徒伤悲

William's note

《天黑以后》——村上春树
——————————————————————————
话说,遇到了一个在书上胡乱评注的、极其自大的家伙。

《天黑以后》——村上春树
——————————————————————————
话说,遇到了一个在书上胡乱评注的、极其自大的家伙。

William's note

回到月亮上去,你!
    ——《舞舞舞》

回到月亮上去,你!
    ——《舞舞舞》

William's note
死后百年,谁不是化为蝼蚁草芥?

死后百年,谁不是化为蝼蚁草芥?

死后百年,谁不是化为蝼蚁草芥?

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