PiggyBack: Pretrained Visual Question Answering Environment for Backing up Non-deep Learning Professionals
원문 초록
We propose a PiggyBack, a Visual Question Answering platform that allows users to apply the state-of-the-art visual-language pretrained models easily. The PiggyBack supports the full stack of visual question answering tasks, specifically data processing, model fine-tuning, and result visualisation. We integrate visual-language models, pretrained by HuggingFace, an open-source API platform of deep learning technologies; however, it cannot be runnable without programming skills or deep learning understanding. Hence, our PiggyBack supports an easy-to-use browser-based user interface with several deep learning visual language pretrained models for general users and domain experts. The PiggyBack includes the following benefits: Free availability under the MIT License, Portability due to web-based and thus runs on almost any platform, A comprehensive data creation and processing technique, and ease of use on deep learning-based visual language pretrained models. The demo video is available on YouTube and can be found at https://youtu.be/iz44RZ1lF4s.
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
SlotPi: Physics-informed Object-centric Reasoning Models
Outside Knowledge Conversational Video (OKCV) Dataset -- Dialoguing over Videos
토론
이 논문과 연결된 포럼 글이 아직 없습니다.