Welcome to the Best of WACV series, your virtual pass to some of the groundbreaking research, insights, and innovations that defined this year’s conference. Live streaming from the authors to you.

Date, Time and Location

May 01, 2026
9 AM – 11 AM Pacific
Online. Register for the Zoom!

Beyond Pixels: Type-Aware Contrastive Learning for Global Urban Similarity

Standard visual models often fail to distinguish between superficial appearances and meaningful structural variations in urban environments. We present a type-aware contrastive learning framework that measures city similarity by explicitly modeling infrastructure elements like intersections and bus lanes. Our framework integrates a type-conditioned Vision Transformer that actively fuses visual features with CLIP-derived semantic embeddings via a novel adaptive per-type contrastive loss. This allows the model to dynamically prioritize the most discriminative infrastructure categories while down-weighting less informative visual noise. We demonstrate that this method significantly improves clustering quality and generalizes to unseen cities, providing a scalable, interpretable foundation for urban analysis.