Document Visual Question Answering Challenge 2020
원문 초록
This paper presents results of Document Visual Question Answering Challenge organized as part of "Text and Documents in the Deep Learning Era" workshop, in CVPR 2020. The challenge introduces a new problem - Visual Question Answering on document images. The challenge comprised two tasks. The first task concerns with asking questions on a single document image. On the other hand, the second task is set as a retrieval task where the question is posed over a collection of images. For the task 1 a new dataset is introduced comprising 50,000 questions-answer(s) pairs defined over 12,767 document images. For task 2 another dataset has been created comprising 20 questions over 14,362 document images which share the same document template.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Describe Anything Model for Visual Question Answering on Text-rich Images
DrishtiKon: Multi-Granular Visual Grounding for Text-Rich Document Images
HRIBench: Benchmarking Vision-Language Models for Real-Time Human Perception in Human-Robot Interaction
Adapting Lightweight Vision Language Models for Radiological Visual Question Answering
SimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative Refinement
SlotPi: Physics-informed Object-centric Reasoning Models
토론
이 논문과 연결된 포럼 글이 아직 없습니다.