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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 351–375 of 1209 papers

TitleStatusHype
DocVLM: Make Your VLM an Efficient Reader—0
DocSum: Domain-Adaptive Pre-training for Document Abstractive Summarization—0
Verb Mirage: Unveiling and Assessing Verb Concept Hallucinations in Multimodal Large Language Models—0
Aligned Music Notation and Lyrics TranscriptionCode0
SynFinTabs: A Dataset of Synthetic Financial Tables for Information and Table ExtractionCode0
Text Change Detection in Multilingual Documents Using Image Comparison—0
CC-OCR: A Comprehensive and Challenging OCR Benchmark for Evaluating Large Multimodal Models in Literacy—0
Arabic Handwritten Document OCR Solution with Binarization and Adaptive Scale Fusion Detection—0
DLaVA: Document Language and Vision Assistant for Answer Localization with Enhanced Interpretability and TrustworthinessCode0
Beyond Logit Lens: Contextual Embeddings for Robust Hallucination Detection & Grounding in VLMs—0
VARCO-VISION: Expanding Frontiers in Korean Vision-Language Models—0
SVTRv2: CTC Beats Encoder-Decoder Models in Scene Text Recognition—0
Towards Accessible Learning: Deep Learning-Based Potential Dysgraphia Detection and OCR for Potentially Dysgraphic Handwriting—0
DriveThru: a Document Extraction Platform and Benchmark Datasets for Indonesian Local Language ArchivesCode0
Is Cognition consistent with Perception? Assessing and Mitigating Multimodal Knowledge Conflicts in Document Understanding—0
Veri-Car: Towards Open-world Vehicle Information Retrieval—0
NeKo: Toward Post Recognition Generative Correction Large Language Models with Task-Oriented Experts—0
Hierarchical Visual Feature Aggregation for OCR-Free Document Understanding—0
TAP-VL: Text Layout-Aware Pre-training for Enriched Vision-Language Models—0
M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understanding—0
Out-of-Distribution Recovery with Object-Centric Keypoint Inverse Policy for Visuomotor Imitation Learning—0
HIP: Hierarchical Point Modeling and Pre-training for Visual Information Extraction—0
Handwriting Recognition in Historical Documents with Multimodal LLM—0
Are VLMs Really BlindCode0
Structured Analysis and Comparison of Alphabets in Historical Handwritten Ciphers—0
Show:102550
← PrevPage 15 of 49Next →
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