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 226–250 of 1209 papers

TitleStatusHype
DECDM: Document Enhancement using Cycle-Consistent Diffusion Models—0
Decoding Anagrammed Texts Written in an Unknown Language and Script—0
Artificial Eye for the Blind—0
Classroom Slide Narration System—0
Data Cleaning for XML Electronic Dictionaries via Statistical Anomaly Detection—0
Classification of Contract-Amendment Relationships—0
Chunk-based Chinese Spelling Check with Global Optimization—0
DanProof: Pedagogical Spell and Grammar Checking for Danish—0
DavarOCR: A Toolbox for OCR and Multi-Modal Document Understanding—0
Deductron -- A Recurrent Neural Network—0
CHISPA on the GO: A mobile Chinese-Spanish translation service for travellers in trouble—0
CREPE: Coordinate-Aware End-to-End Document Parser—0
Chinese/English mixed Character Segmentation as Semantic Segmentation—0
A random forest system combination approach for error detection in digital dictionaries—0
A Linked Data Model for Multimodal Sentiment and Emotion Analysis—0
Crowdsourcing an OCR Gold Standard for a German and French Heritage Corpus—0
Classification of Documents Extracted from Images with Optical Character Recognition Methods—0
ChemRxivQuest: A Curated Chemistry Question-Answer Database Extracted from ChemRxiv Preprints—0
A Masked Bounding-Box Selection Based ResNet Predictor for Text Rotation Prediction—0
Cleansing Jewel: A Neural Spelling Correction Model Built On Google OCR-ed Tibetan Manuscripts—0
Arabic Handwritten Document OCR Solution with Binarization and Adaptive Scale Fusion Detection—0
CLIP is Almost All You Need: Towards Parameter-Efficient Scene Text Retrieval without OCR—0
CLIP-ReIdent: Contrastive Training for Player Re-Identification—0
A Scalable Handwritten Text Recognition System—0
Chaurah: A Smart Raspberry Pi based Parking System—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
1DTrOCR 105MAccuracy (%)89.6—Unverified
2DTrOCRAccuracy (%)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