most citedCharFormer: A Glyph Fusion based Attentive Framework for High-precision Character Image Denoising

31 citations · 69 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV202311 cited

Toward Zero-shot Character Recognition: A Gold Standard Dataset with Radical-level Annotations

Xiaolei Diao, Daqian Shi, Jian Li +5

Optical character recognition (OCR) methods have been applied to diverse tasks, e.g., street view text recognition and document analysis. Recently, zero-shot OCR has piqued the int…

cs.CV20232 cited

A semantics-driven methodology for high-quality image annotation

Fausto Giunchiglia, Mayukh Bagchi, Xiaolei Diao

Recent work in Machine Learning and Computer Vision has highlighted the presence of various types of systematic flaws inside ground truth object recognition benchmark datasets. Our…

cs.CV20231 cited

Incremental Image Labeling via Iterative Refinement

Fausto Giunchiglia, Xiaolei Diao, Mayukh Bagchi

Data quality is critical for multimedia tasks, while various types of systematic flaws are found in image benchmark datasets, as discussed in recent work. In particular, the existe…

cs.CV202231 cited

CharFormer: A Glyph Fusion based Attentive Framework for High-precision Character Image Denoising

Daqian Shi, Xiaolei Diao, Lida Shi +4

Degraded images commonly exist in the general sources of character images, leading to unsatisfactory character recognition results. Existing methods have dedicated efforts to resto…

cs.CV202224 cited

RCRN: Real-world Character Image Restoration Network via Skeleton Extraction

Daqian Shi, Xiaolei Diao, Hao Tang +3

Constructing high-quality character image datasets is challenging because real-world images are often affected by image degradation. There are limitations when applying current ima…