Search Results for author: Cheng Da

Found 7 papers, 5 papers with code

Multi-Granularity Prediction with Learnable Fusion for Scene Text Recognition

1 code implementation25 Jul 2023 Cheng Da, Peng Wang, Cong Yao

Specifically, MGP-STR achieves an average recognition accuracy of $94\%$ on standard benchmarks for scene text recognition.

Language Modelling Optical Character Recognition (OCR) +1

Levenshtein OCR

2 code implementations8 Sep 2022 Cheng Da, Peng Wang, Cong Yao

A novel scene text recognizer based on Vision-Language Transformer (VLT) is presented.

Imitation Learning Optical Character Recognition (OCR) +1

Multi-Granularity Prediction for Scene Text Recognition

2 code implementations8 Sep 2022 Peng Wang, Cheng Da, Cong Yao

In this work, we first draw inspiration from the recent progress in Vision Transformer (ViT) to construct a conceptually simple yet powerful vision STR model, which is built upon ViT and outperforms previous state-of-the-art models for scene text recognition, including both pure vision models and language-augmented methods.

 Ranked #1 on Scene Text Recognition on Uber-Text (using extra training data)

Language Modelling Optical Character Recognition (OCR) +1

AMVH: Asymmetric Multi-Valued Hashing

no code implementations CVPR 2017 Cheng Da, Shibiao Xu, Kun Ding, Gaofeng Meng, Shiming Xiang, Chunhong Pan

(2) A multi-integer-embedding is employed for compressing the whole database, which is modeled by binary sparse representation with fixed sparsity.

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