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 1026–1050 of 1209 papers

TitleStatusHype
SAR-Net: Shape Alignment and Recovery Network for Category-level 6D Object Pose and Size Estimation—0
DONUT-hole: DONUT Sparsification by Harnessing Knowledge and Optimizing Learning Efficiency—0
DoPTA: Improving Document Layout Analysis using Patch-Text Alignment—0
DOTA: Deformable Optimized Transformer Architecture for End-to-End Text Recognition with Retrieval-Augmented Generation—0
DUBLIN -- Document Understanding By Language-Image Network—0
Dynamic Low-Resolution Distillation for Cost-Efficient End-to-End Text Spotting—0
Dynamic Programming Approach to Template-based OCR—0
E2E Process Automation Leveraging Generative AI and IDP-Based Automation Agent: A Case Study on Corporate Expense Processing—0
EASTER: Efficient and Scalable Text Recognizer—0
Éclair -- Extracting Content and Layout with Integrated Reading Order for Documents—0
Effectiveness of Mining Audio and Text Pairs from Public Data for Improving ASR Systems for Low-Resource Languages—0
Effective search space reduction for spell correction using character neural embeddings—0
Efficient End-to-End Visual Document Understanding with Rationale Distillation—0
Efficient few-shot learning for pixel-precise handwritten document layout analysis—0
Efficient, Lexicon-Free OCR using Deep Learning—0
Efficient Media Retrieval from Non-Cooperative Queries—0
Efficient Medical VIE via Reinforcement Learning—0
EfficientOCR: An Extensible, Open-Source Package for Efficiently Digitizing World Knowledge—0
Embedding Similarity Guided License Plate Super Resolution—0
Endangered Data for Endangered Languages: Digitizing Print dictionaries—0
Real-time Bangla License Plate Recognition System for Low Resource Video-based Applications—0
End-to-End Piece-Wise Unwarping of Document Images—0
End-to-End Unsupervised Document Image Blind Denoising—0
Engineering RAG Systems for Real-World Applications: Design, Development, and Evaluation—0
Enhancement of Bengali OCR by Specialized Models and Advanced Techniques for Diverse Document Types—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