7 citations · 14 across the 8 of their papers we have counts for
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cs.CV2023
SCOB: Universal Text Understanding via Character-wise Supervised Contrastive Learning with Online Text Rendering for Bridging Domain Gap
Daehee Kim, Yoonsik Kim, DongHyun Kim +3
Inspired by the great success of language model (LM)-based pre-training, recent studies in visual document understanding have explored LM-based pre-training methods for modeling te…
cs.CL2023
Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language Models
Geewook Kim, Hodong Lee, Daehee Kim +7
Recent advances in Large Language Models (LLMs) have stimulated a surge of research aimed at extending their applications to the visual domain. While these models exhibit promise i…
cs.CV2023★ 1 cited
Towards Unified Scene Text Spotting based on Sequence Generation
Taeho Kil, Seonghyeon Kim, Sukmin Seo +2
Sequence generation models have recently made significant progress in unifying various vision tasks. Although some auto-regressive models have demonstrated promising results in end…