Search Results for author:
Found 4 papers, 0 papers with code
TaCo: Textual Attribute Recognition via Contrastive Learning
To realize this goal, we design the learning paradigm from three perspectives: 1) generating attribute views, 2) extracting subtle but crucial details, and 3) exploiting valued view pairs for learning, to fully unlock the pre-training potential.
GMN: Generative Multi-modal Network for Practical Document Information Extraction
Document Information Extraction (DIE) has attracted increasing attention due to its various advanced applications in the real world.
Relational Representation Learning in Visually-Rich Documents
To deal with the unpredictable definition of relations, we propose a novel contrastive learning task named Relational Consistency Modeling (RCM), which harnesses the fact that existing relations should be consistent in differently augmented positive views.
PuzzleNet: Scene Text Detection by Segment Context Graph Learning
Recently, a series of decomposition-based scene text detection methods has achieved impressive progress by decomposing challenging text regions into pieces and linking them in a bottom-up manner.
