Papers with Code 아카이브

Optical Character Recognition (OCR)

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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/yangyucheng000/papercode-2/tree/main/lstm-gaf

LSTM: A Search Space Odyssey

https://github.com/yangyucheng000/psenet

Shape Robust Text Detection with Progressive Scale Expansion Network

https://github.com/yanxp/ASM

Cost-effective Object Detection: Active Sample Mining with Switchable Selection Criteria

https://github.com/yeungchenwa/hdr

Reviving Cultural Heritage: A Novel Approach for Comprehensive Historical Document Restoration

https://github.com/yincheng/GGP

Bayesian Semi-supervised Learning with Graph Gaussian Processes

https://github.com/ykrmm/ICLR_2020

Segmental Recurrent Neural Networks

https://github.com/ykrmm/TREMBA

Segmental Recurrent Neural Networks

https://github.com/yrahul3910/symnet

LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence

https://github.com/yuyq96/texthawk

TextHawk2: A Large Vision-Language Model Excels in Bilingual OCR and Grounding with 16x Fewer Tokens

https://github.com/zaeemzadeh/Active-Learning-UCF101-IPM

Iterative Projection and Matching: Finding Structure-preserving Representatives and Its Application to Computer Vision

https://github.com/zaeemzadeh/IPM

Iterative Projection and Matching: Finding Structure-preserving Representatives and Its Application to Computer Vision

https://github.com/zahinsufiyan/flow-networks-fault-adaptation

CFlowNets: Continuous Control with Generative Flow Networks

https://github.com/zahrakhoshdel/realtime-text-detection-and-recognition

EAST: An Efficient and Accurate Scene Text Detector

https://github.com/zchenry/ambiguity-comparison

Active Classification with Uncertainty Comparison Queries

https://github.com/zhaoolee/garss

Probabilistic Artificial Intelligence

https://github.com/zhengy09/SysId

Learning Linear Dynamical Systems with Semi-Parametric Least Squares

https://github.com/zhiqwang/crnn.pytorch

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/zhiqwang/image-captioning

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/ztoString/CRNN_CTC_OCR_TensorFlow

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/zwenwang/CTPN_Pytorch

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/zxytim/EAST

EAST: An Efficient and Accurate Scene Text Detector

https://github.com/zyasjtu/CNN-RNN-CTC

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/zyasjtu/EAST

EAST: An Efficient and Accurate Scene Text Detector

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.