FastTextSpotter
High-Efficiency Transformer for Multilingual Scene Text Spotting
FastTextSpotter is an end-to-end transformer-based scene text spotting model designed for high efficiency and multilingual robustness. Published at WACV 2024.
Key Contributions
- Lightweight deformable attention backbone for fast text region proposals
- Unified detection + recognition head trained end-to-end
- Pre-training leveraging multilingual synthetic datasets for cross-lingual transfer
- Strong speed-accuracy trade-off on Total-Text, CTW1500, and MLT benchmarks
Publication
Das, A., Biswas, S., Pal, U., Lladós, J., Bhattacharya, S. FastTextSpotter: A High-Efficiency Transformer for Multilingual Scene Text Spotting. WACV 2024.
Work done at CVPRU, Indian Statistical Institute Kolkata.