SOTAVerified

Optical Character Recognition (OCR)

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)

Papers

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Showing 601–625 of 1209 papers

TitleStatusHype
DEVICE: DEpth and VIsual ConcEpts Aware Transformer for TextCaps—0
Noisy Parallel Data AlignmentCode0
On the feasibility of attacking Thai LPR systems with adversarial examples—0
Improving Inference Performance of Machine Learning with the Divide-and-Conquer Principle—0
Semantic rule Web-based Diagnosis and Treatment of Vector-Borne Diseases using SWRL rules—0
Bengali Handwritten Digit Recognition using CNN with Explainable AI—0
Transferring General Multimodal Pretrained Models to Text Recognition—0
Wukong-Reader: Multi-modal Pre-training for Fine-grained Visual Document UnderstandingCode0
Towards Robust Handwritten Text Recognition with On-the-fly User Participation—0
SceneGATE: Scene-Graph based co-Attention networks for TExt visual question answering—0
Geometric Rectification of Creased Document Images based on Isometric Mapping—0
LOANet: A Lightweight Network Using Object Attention for Extracting Buildings and Roads from UAV Aerial Remote Sensing ImagesCode0
Extending TrOCR for Text Localization-Free OCR of Full-Page Scanned Receipt Images—0
PACMAN: a framework for pulse oximeter digit detection and reading in a low-resource setting—0
OCR-RTPS: An OCR-based real-time positioning system for the valet parking—0
Information Retrieval from the Digitized Books—0
Chart-RCNN: Efficient Line Chart Data Extraction from Camera Images—0
Look, Read and Ask: Learning to Ask Questions by Reading Text in Images—0
Out-of-Candidate Rectification for Weakly Supervised Semantic Segmentation—0
Text-Aware Dual Routing Network for Visual Question Answering—0
ChartParser: Automatic Chart Parsing for Print-Impaired—0
Efficient few-shot learning for pixel-precise handwritten document layout analysis—0
A Late Multi-Modal Fusion Model for Detecting Hybrid Spam E-mail—0
MenuAI: Restaurant Food Recommendation System via a Transformer-based Deep Learning Model—0
Key Information Extraction in Purchase Documents using Deep Learning and Rule-based Corrections—0
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All datasetsBenchmarking Chinese Text Recognition: Datasets, Baselines, and an Empirical StudyVideoDB's OCR Benchmark Public CollectionFSNS - TestI2L-140KSUTim2latex-100k

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DTrOCRAccuracy (%)89.6—Unverified
2DTrOCR 105MAccuracy (%)89.6—Unverified
3MaskOCR-LAccuracy (%)82.6—Unverified
4TransOCRAccuracy (%)72.8—Unverified
5SRNAccuracy (%)65—Unverified
6MORANAccuracy (%)64.3—Unverified
7SEEDAccuracy (%)61.2—Unverified
#ModelMetricClaimedVerifiedStatus
1GPT-4oAverage Accuracy76.22—Unverified
2Gemini-1.5 ProAverage Accuracy76.13—Unverified
3Claude-3 SonnetAverage Accuracy67.71—Unverified
4RapidOCRAverage Accuracy56.98—Unverified
5EasyOCRAverage Accuracy49.3—Unverified
#ModelMetricClaimedVerifiedStatus
1STREETSequence error27.54—Unverified
2SEESequence error22—Unverified
3AttentionOCR_Inception-resnet-v2_LocationSequence error15.8—Unverified
#ModelMetricClaimedVerifiedStatus
1I2L-NOPOOLBLEU89.09—Unverified
2I2L-STRIPSBLEU89—Unverified
#ModelMetricClaimedVerifiedStatus
1TesseractCharacter Error Rate (CER)0.08—Unverified
2EasyOCRCharacter Error Rate (CER)0.07—Unverified
#ModelMetricClaimedVerifiedStatus
1I2L-STRIPSBLEU88.86—Unverified