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 326–350 of 1209 papers

TitleStatusHype
Advanced Knowledge Extraction of Physical Design Drawings, Translation and conversion to CAD formats using Deep Learning—0
TextBlockV2: Towards Precise-Detection-Free Scene Text Spotting with Pre-trained Language Model—0
Eyes Closed, Safety On: Protecting Multimodal LLMs via Image-to-Text Transformation—0
Adversarial Training with OCR Modality Perturbation for Scene-Text Visual Question AnsweringCode0
Rich Semantic Knowledge Enhanced Large Language Models for Few-shot Chinese Spell Checking—0
The future of document indexing: GPT and Donut revolutionize table of content processing—0
Open-Vocabulary Scene Text Recognition via Pseudo-Image Labeling and Margin Loss—0
DeepSeek-VL: Towards Real-World Vision-Language UnderstandingCode7
TextMonkey: An OCR-Free Large Multimodal Model for Understanding DocumentCode5
Multimodal Transformer for Comics Text-Cloze—0
LOCR: Location-Guided Transformer for Optical Character Recognition—0
Large Language Models for Simultaneous Named Entity Extraction and Spelling Correction—0
ODM: A Text-Image Further Alignment Pre-training Approach for Scene Text Detection and SpottingCode1
Advancing Generative Model Evaluation: A Novel Algorithm for Realistic Image Synthesis and Comparison in OCR System—0
Representing Online Handwriting for Recognition in Large Vision-Language Models—0
Syntactic Language Change in English and German: Metrics, Parsers, and ConvergencesCode0
TEXTRON: Weakly Supervised Multilingual Text Detection through Data ProgrammingCode1
Beyond the Mud: Datasets and Benchmarks for Computer Vision in Off-Road Racing—0
ClusterTabNet: Supervised clustering method for table detection and table structure recognitionCode1
Segmentation-free Connectionist Temporal Classification loss based OCR Model for Text Captcha Classification—0
SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language ModelsCode7
Enhancement of Bengali OCR by Specialized Models and Advanced Techniques for Diverse Document Types—0
ExTTNet: A Deep Learning Algorithm for Extracting Table Texts from Invoice Images—0
From Training-Free to Adaptive: Empirical Insights into MLLMs' Understanding of Detection Information—0
MouSi: Poly-Visual-Expert Vision-Language ModelsCode2
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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