Search Results for author:
Found 6 papers, 3 papers with code
GRAM: Global Reasoning for Multi-Page VQA
The increasing use of transformer-based large language models brings forward the challenge of processing long sequences.
GLASS: Global to Local Attention for Scene-Text Spotting
In recent years, the dominant paradigm for text spotting is to combine the tasks of text detection and recognition into a single end-to-end framework.
Ranked #6 on
Text Spotting
on Total-Text
On Calibration of Scene-Text Recognition Models
Although the topic of confidence calibration has been an active research area for the last several decades, the case of structured and sequence prediction calibration has been scarcely explored.
Sequence-to-Sequence Contrastive Learning for Text Recognition
We propose a framework for sequence-to-sequence contrastive learning (SeqCLR) of visual representations, which we apply to text recognition.
SCATTER: Selective Context Attentional Scene Text Recognizer
The first attention step re-weights visual features from a CNN backbone together with contextual features computed by a BiLSTM layer.
Sparsity-Based Super Resolution for SEM Images
The scanning electron microscope (SEM) produces an image of a sample by scanning it with a focused beam of electrons.
