计算机科学
标杆管理
个性化
隐藏字幕
多样性(控制论)
领域(数学)
接口(物质)
人工智能
钥匙(锁)
人机交互
自然语言处理
万维网
图像(数学)
数学
计算机安全
气泡
营销
最大气泡压力法
并行计算
纯数学
业务
作者
Dongxu Li,Junnan Li,Hung Lê,Guangsen Wang,Silvio Savarese,Steven C. H. Hoi
出处
期刊:Cornell University - arXiv
日期:2022-01-01
被引量:19
标识
DOI:10.48550/arxiv.2209.09019
摘要
We introduce LAVIS, an open-source deep learning library for LAnguage-VISion research and applications. LAVIS aims to serve as a one-stop comprehensive library that brings recent advancements in the language-vision field accessible for researchers and practitioners, as well as fertilizing future research and development. It features a unified interface to easily access state-of-the-art image-language, video-language models and common datasets. LAVIS supports training, evaluation and benchmarking on a rich variety of tasks, including multimodal classification, retrieval, captioning, visual question answering, dialogue and pre-training. In the meantime, the library is also highly extensible and configurable, facilitating future development and customization. In this technical report, we describe design principles, key components and functionalities of the library, and also present benchmarking results across common language-vision tasks. The library is available at: https://github.com/salesforce/LAVIS.
科研通智能强力驱动
Strongly Powered by AbleSci AI