https://github.com/sanakhamekhem/GAN-HTR
공식 코드Enhance to Read Better: A Multi-Task Adversarial Network for Handwritten Document Image Enhancement
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Handwritten Text Recognition (HTR) is the task of automatically identifying and transcribing handwritten text from images or scanned documents into machine-readable text. The goal is to develop a system capable of accurately interpreting diverse handwriting styles, accounting for variations in alignment, stroke, spacing, and noise. This task involves detecting handwritten regions within an image, extracting the text content, and converting it into a structured digital format, enabling further search, indexing, or data analysis.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Enhance to Read Better: A Multi-Task Adversarial Network for Handwritten Document Image Enhancement
StackMix and Blot Augmentations for Handwritten Text Recognition
Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth Evaluation
Writer adaptation for offline text recognition: An exploration of neural network-based methods
HANA: A HAndwritten NAme Database for Offline Handwritten Text Recognition
The Learnable Typewriter: A Generative Approach to Text Analysis
HTR-VT: Handwritten Text Recognition with Vision Transformer
Full Page Handwriting Recognition via Image to Sequence Extraction
Full Page Handwriting Recognition via Image to Sequence Extraction
Data Generation for Post-OCR correction of Cyrillic handwriting
Stylometry for Noisy Medieval Data: Evaluating Paul Meyer's Hagiographic Hypothesis
TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models
ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation
Sequence-to-Sequence Contrastive Learning for Text Recognition
Sequence-to-Sequence Contrastive Learning for Text Recognition
ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation
ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation
DTrOCR: Decoder-only Transformer for Optical Character Recognition
TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models
TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models
Evaluating Sequence-to-Sequence Models for Handwritten Text Recognition
Full Page Handwriting Recognition via Image to Sequence Extraction
HTR-VT: Handwritten Text Recognition with Vision Transformer
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.