
VLM Streetscape
Vision-Language Models for structured streetscape assessment from open street-level imagery
- Vision-Language Models
- Computer Vision

Vision-Language Models for structured streetscape assessment from open street-level imagery

Scene segmentation of self-built virtual urban environments for pedestrian research

Reinforcement learning for pedestrian behavior and intelligent transportation systems

EEG-based biometric signal processing for pedestrian emotion and response

VR-based driving and pedestrian simulation for human factors research

Microscopic and macroscopic traffic simulation

A computer-vision approach to walkability, active aging, and housing capitalization

Spatial analysis and urban design for sustainable city development

Urban mobility patterns and travel demand modeling

Congestion-based traffic assignment and design optimization for pedestrian networks (PedNetOpt)
A multimodal global-optimization benchmark — and why it matters for validating gradient-free solvers before...