all AI news
AccessLens: Auto-detecting Inaccessibility of Everyday Objects
Feb. 26, 2024, 5:46 a.m. | Nahyun Kwon, Qian Lu, Muhammad Hasham Qazi, Joanne Liu, Changhoon Oh, Shu Kong, Jeeeun Kim
cs.CV updates on arXiv.org arxiv.org
Abstract: In our increasingly diverse society, everyday physical interfaces often present barriers, impacting individuals across various contexts. This oversight, from small cabinet knobs to identical wall switches that can pose different contextual challenges, highlights an imperative need for solutions. Leveraging low-cost 3D-printed augmentations such as knob magnifiers and tactile labels seems promising, yet the process of discovering unrecognized barriers remains challenging because disability is context-dependent. We introduce AccessLens, an end-to-end system designed to identify inaccessible interfaces …
abstract arxiv auto cabinet challenges cost cs.cv cs.hc diverse highlights interfaces labels low objects oversight small society solutions type
More from arxiv.org / cs.CV updates on arXiv.org
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs
1 day, 15 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Intern Large Language Models Planning (f/m/x)
@ BMW Group | Munich, DE
Data Engineer Analytics
@ Meta | Menlo Park, CA | Remote, US