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T08. OCR, vision-language models, and industrial display reading
Research on reading meters, indicators, and shop-floor displays from images.
- T08-1Similar problemSince 2025
Do Vision-Language Models Measure Up? Benchmarking Visual Measurement Reading with MeasureBench
- T08-2Structural parallelSince 2025
DialBench: Towards Accurate Reading Recognition of Pointer Meter using Large Foundation Models
- T08-14Candidate approachSince 2025
Qwen2.5-VL Technical Report
- T08-3Similar problem
Convolutional Neural Networks for Automatic Meter Reading
- T08-4Similar problem
Utilizing Smartphone-Based Machine Learning in Medical Monitor Data Collection: Seven Segment Digit Recognition
- T08-5Structural parallel
An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition
- T08-6Structural parallel
Real-time Scene Text Detection with Differentiable Binarization
- T08-7Candidate approach
TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models
- T08-9Structural parallel
General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model
- T08-11Candidate approach
OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models
- T08-12Structural parallel
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
- T08-13Candidate approach
Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
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