7 citations · 13 across the 8 of their papers we have counts for
8 papers
Evaluating Multimodal LLMs as Generalist Vision-Language-Action Agents for Drone Control: Commanding, Approaching, Tracking and Searching
Jaewoo Park, Minyoung Lee, Sukmin Seo +11
Multimodal large language models (MLLMs) are increasingly used to make decisions for drones, but existing evaluations are mostly limited to simulation, to a single drone, and to ta…
CREPE: Coordinate-Aware End-to-End Document Parser
Yamato Okamoto, Youngmin Baek, Geewook Kim +5
In this study, we formulate an OCR-free sequence generation model for visual document understanding (VDU). Our model not only parses text from document images but also extracts the…
TableVQA-Bench: A Visual Question Answering Benchmark on Multiple Table Domains
Yoonsik Kim, Moonbin Yim, Ka Yeon Song
In this paper, we establish a benchmark for table visual question answering, referred to as the TableVQA-Bench, derived from pre-existing table question-answering (QA) and table st…
HyperCLOVA X Technical Report
Kang Min Yoo, Jaegeun Han, Sookyo In +393
We introduce HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture, along with competitive capabilities in English, math, and coding. H…
On Web-based Visual Corpus Construction for Visual Document Understanding
Donghyun Kim, Teakgyu Hong, Moonbin Yim +2
In recent years, research on visual document understanding (VDU) has grown significantly, with a particular emphasis on the development of self-supervised learning methods. However…
OCR-free Document Understanding Transformer
Geewook Kim, Teakgyu Hong, Moonbin Yim +7
Understanding document images (e.g., invoices) is a core but challenging task since it requires complex functions such as reading text and a holistic understanding of the document.…
SynthTIGER: Synthetic Text Image GEneratoR Towards Better Text Recognition Models
Moonbin Yim, Yoonsik Kim, Han-Cheol Cho +1
For successful scene text recognition (STR) models, synthetic text image generators have alleviated the lack of annotated text images from the real world. Specifically, they genera…
RewriteNet: Reliable Scene Text Editing with Implicit Decomposition of Text Contents and Styles
Junyeop Lee, Yoonsik Kim, Seonghyeon Kim +4
Scene text editing (STE), which converts a text in a scene image into the desired text while preserving an original style, is a challenging task due to a complex intervention betwe…