Understanding group-level social interactions in public spaces is crucial for urban planning, informing the design of socially vibrant and inclusive environments. Detecting such interactions from images involves interpreting subtle visual cues such as relations, proximity and co-movement – semantically complex signals that go beyond traditional object detection. To address this challenge, we introduce a social group region detection task, which requires inferring and spatially grounding visual regions defined by abstract interpersonal relations. We propose MINGLE (Modeling INterpersonal Group-Level Engagement), a modular three-stage pipeline that integrates: (1) off-the-shelf human detection and depth estimation, (2) VLM-based reasoning to classify pairwise social affiliation, and (3) a lightweight spatial aggregation algorithm to localize socially connected groups. To support this task and encourage future research, we present a new dataset of 100K urban street-view images annotated with bounding boxes and labels for both individuals and socially interacting groups. The annotations combine human-created labels and outputs from the MINGLE pipeline, ensuring semantic richness and broad coverage of real world scenarios.

We have entered a new era of computing—one where AI permeates every aspect of society from education to healthcare. In this workshop, we examine the emerging role of AI in the design of equitable and accessible cities, transportation systems, and interactive tools for mapping and navigation. We will solicit short papers around key Urban AI + disability themes, including autonomous vehicles, intelligent wheelchairs, assistive human-robotic interaction, assessing and navigating pedestrian pathways, indoor accessibility, and overarching challenges related to ethics, bias, and data privacy and security. We invite both traditional HCI and accessibility researchers as well as scholars and practitioners from other disciplines relevant to this workshop, including disability studies, gerontology, social work, community psychology, and law. Our overarching goal is to identify open challenges, share current work across disciplines, and spur new collaborations related to AI and urban accessibility.