Hugging Face Trending Papers
Jun 23

Advancing WordArt-Oriented Scene Text Recognition: Datasets and Methods

WordArt (artistic text) features highly customized fonts, textures, and layouts, making WordArt-oriented scene TExt Recognition (WATER) substantially more challenging than general Scene Text Recognition (STR). Existing STR datasets and methods, typically built around regular scene text and fixed-template inputs, struggle to scale to WATER.

arXiv Computation and Language
3d ago

SpanCalib-VLM: Calibrated Hallucination Span Detection in Vision-Language Models

SpanCalib-VLM is a hybrid system for detecting hallucinated text spans in Vision‑Language Models. It combines a multimodal sequence tagger (XLM‑RoBERTa‑Large + SigLIP) with a fine‑tuned generative VLM (Qwen3.5‑4B‑SHROOM‑SFT) and uses a Union‑Calibrated Fusion strategy to re‑score candidate spans. On the SHROOM‑Visions English evaluation split, the ensemble achieves a Pearson calibration correlation of 0.41, an overall IoU of 0.39, a clean‑response IoU of 0.91, and a detection accuracy of 70.7%.

By Amanuel Gizachew Abebe, Yasmin Moslem
arXiv Computation and Language
Aug 27

RefLAM: A Reference-Grounded Line Annotation Pipeline for Historical Arabic Manuscripts

RefLAM is a pipeline that converts manuscript page images and clean transcriptions into validated, line-level ground truth for Arabic handwritten text recognition. It combines a deep‑learning page‑segmentation model, a multimodal large language model for structured OCR, and a diacritic‑agnostic fuzzy alignment engine that assigns a confidence score to each line, with a provable correctness guarantee for perfect scores. Using RefLAM, the authors achieved a 75× speedup over manual annotation and released AraMS‑28k, a dataset of 14 historical Arabic manuscripts with detailed annotations.

By Mohamed Guechaoui, Mohamed Diaa Zellagui, Souleyman Chaib, Sahraoui Dhelim
arXiv Computer Vision
Aug 21

TextRefine: Improving Textual Fidelity, Spatial Placement, and Glyph Rendering for Text Editing in Product Posters

arXiv:2608. 19637v1 Announce Type: new Abstract: Text editing in product posters entails inserting new text or replacing existing text while preserving product appearance, background content, and global composition.

By Honglie Wang, Jia Sun, Zijun Li, Junlong Wu, Pengcheng Wei, Jiyuan Wang, Yongrui Heng, Boheng Zhang, Huaiqing Wang, Dewen Fan, Qianqian Gan, Fan Yang, Tingting Gao, Yan-Ming Zhang