Attention Weighted Visual Feature Localization For Text Region Identification

via “attention-weighted visual feature localization for text region identification”

image-to-text model by undefined. 7,67,977 downloads.

Unique: Leverages the cross-attention mechanism inherent to the vision-encoder-decoder architecture to provide token-level spatial grounding without additional annotation or post-processing models. Attention weights are computed during standard inference with minimal overhead when output_attentions=True.

vs others: Provides free spatial localization as a byproduct of the attention mechanism, whereas alternative approaches would require separate bounding box prediction models or post-hoc alignment algorithms.