https://github.com/nhh1501/E2E_MLT_VN
E2E-MLT - an Unconstrained End-to-End Method for Multi-Language Scene Text
Papers with Code 아카이브
Optical Character Recognition (OCR)
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 10
- 평가표
- 6
- 보존된 평가 기록
- 20
Optical Character Recognition or Optical Character Reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo (for example the text on signs and billboards in a landscape photo, license plates in cars...) or from subtitle text superimposed on an image (for example: from a television broadcast)
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/nithyadurai87/pottan-ocr-tamil
https://github.com/nnadagouda/Chinese-Word-Detection
https://github.com/ofnt/real_anot
https://github.com/oleehyo/texteller
TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models
https://github.com/open-starlab/trackid3x3
Enhanced Multi-Object Tracking Using Pose-based Virtual Markers in 3x3 Basketball
https://github.com/openbmb/minicpm-v
https://github.com/openeventdata/PLOVER
Creating Custom Event Data Without Dictionaries: A Bag-of-Tricks
https://github.com/opengvlab/llama-adapter
LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
https://github.com/opennmt/im2text
https://github.com/owseaman/Text-Detection-in-an-Image
https://github.com/oyxhust/CNN-LSTM-CTC-text-recognition
https://github.com/parthasarathy-ss/newspaper-navigator
https://github.com/pavlo-melnyk/offline-HCCR
https://github.com/pdebench/pdebench
https://github.com/peregilk/north-t5
Operationalizing a National Digital Library: The Case for a Norwegian Transformer Model
https://github.com/peymanbateni/simple-cnaps
https://github.com/phantrdat/cvpr20-scatter-text-recognizer
Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition
https://github.com/philipperemy/tensorflow-multi-dimensional-lstm
https://github.com/pinakinathc/phocnet_keras
PHOCNet: A Deep Convolutional Neural Network for Word Spotting in Handwritten Documents
https://github.com/pjlab-adg/3dtrans
Bi3D: Bi-domain Active Learning for Cross-domain 3D Object Detection
https://github.com/pokalaanirudh/Text-spotting-in-wild-using-YOLO.
STN-OCR: A single Neural Network for Text Detection and Text Recognition
https://github.com/pps-lab/fl-analysis
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
https://github.com/prathameshza/TrOCR_FineTuning
TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models
https://github.com/ptrckhmmr/DEAL
DEAL: Deep Evidential Active Learning for Image Classification
https://github.com/pwc-1/Paper-10/tree/main/table_transformer
TableFormer: Table Structure Understanding with Transformers
https://github.com/pwc-1/Paper-10/tree/main/trocr
TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models
https://github.com/pwc-1/Paper-9/tree/main/1/trocr
TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models
https://github.com/pwc-1/Paper-9/tree/main/2/nougat
https://github.com/qarchli/pytorch-gan-for-outlier-detection
Generative Adversarial Active Learning for Unsupervised Outlier Detection
https://github.com/qijindou/CRAB
Multi-Label Bayesian Active Learning with Inter-Label Relationships
https://github.com/qingyu95/ICDAR2017-DATASET
https://github.com/qingzhenduyu/ical
When Counting Meets HMER: Counting-Aware Network for Handwritten Mathematical Expression Recognition
https://github.com/qjadud1994/CRNN-Keras
https://github.com/rajmuchhala/Raj-Muchhala---Sr.-ML-Engineer--ML-Assignmen
https://github.com/rapfff/jajapy
Active Learning of Markov Decision Processes using Baum-Welch algorithm (Extended)
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.