Large pre-trained models, also known as foundation models (FMs), are trained in a task-
agnostic manner on large-scale data and can be adapted to a wide range of downstream …

Large pre-trained models, also known as foundation models (FMs), are trained in a task-
agnostic manner on large-scale data and can be adapted to a wide range of downstream …

We introduce Project Sidewalk, a new web-based tool that enables online crowdworkers to
remotely label pedestrian-related accessibility problems by virtually walking through city …

This study investigated the extent to which subjectively and objectively measured street-
level perceptions complement or conflict with each other in explaining property value. Street …

Recently, housing prices studies emerged to use street view imagery to infer the marginal
price of streetscape using hedonic price models (HPM). Within this trend, most studies took …

Contextual information plays an important role in many computer vision tasks, such as object
detection, video action detection, image classification, etc. Recognizing a single object or …

Sidewalks are a critical infrastructure to facilitate essential daily trips for pedestrian and
wheelchair users. The dependence on the infrastructure and the increasing demand from …

In the last decade, crowdsourcing has emerged as a novel mechanism for accomplishing
temporal and spatial critical tasks in transportation with the collective intelligence of …

Remote sighted assistance (RSA) has emerged as a conversational assistive technology for
people with visual impairments (VI), where remote sighted agents provide realtime …

Recent work has applied machine learning methods to automatically find and/or assess
pedestrian infrastructure in online map imagery (eg, satellite photos, streetscape …