6 papers
Advancing WordArt-Oriented Scene Text Recognition: Datasets and Methods
Xingsong Ye, Yongkun Du, Jiaxin Zhang +5
WordArt (artistic text) features highly customized fonts, textures, and layouts, making WordArt-oriented scene TExt Recognition (WATER) substantially more challenging than general…
MuSS: A Large-Scale Dataset and Cinematic Narrative Benchmark for Multi-Shot Subject-to-Video Generation
Haojie Zhang, Di Wu, Bingyan Liu +5
While video foundation models excel at single-shot generation, real-world cinematic storytelling inherently relies on complex multi-shot sequencing. Further progress is constrained…
ICPR 2026 Competition on Low-Resolution License Plate Recognition
Rayson Laroca, Valfride Nascimento, Donggun Kim +19
Low-Resolution License Plate Recognition (LRLPR) remains a challenging problem in real-world surveillance scenarios, where long capture distances, compression artifacts, and advers…
What Is Wrong with Synthetic Data for Scene Text Recognition? A Strong Synthetic Engine with Diverse Simulations and Self-Evolution
Xingsong Ye, Yongkun Du, JiaXin Zhang +3
Large-scale and categorical-balanced text data is essential for training effective Scene Text Recognition (STR) models, which is hard to achieve when collecting real data. Syntheti…
TextSSR: Diffusion-based Data Synthesis for Scene Text Recognition
Xingsong Ye, Yongkun Du, Yunbo Tao +1
Scene text recognition (STR) suffers from challenges of either less realistic synthetic training data or the difficulty of collecting sufficient high-quality real-world data, limit…
Safe Inputs but Unsafe Output: Benchmarking Cross-modality Safety Alignment of Large Vision-Language Model
Siyin Wang, Xingsong Ye, Qinyuan Cheng +5
As Artificial General Intelligence (AGI) becomes increasingly integrated into various facets of human life, ensuring the safety and ethical alignment of such systems is paramount.…