A hierarchical VQA system aggregates model answers into weighted risk scores that produce four-category safety event maps for urban navigation, backed by a new 20-city dataset where generative MLLMs like Qwen-VL outperform classification models.
Vialm: A survey and benchmark of visually impaired assis- tance with large models
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
GuideDog supplies 22K egocentric image-description pairs from 46 countries and an 818-sample QA benchmark showing that current multimodal models still struggle with depth perception and BLV-specific guidance rules.
citing papers explorer
-
Urban Risk-Aware Navigation via VQA-Based Event Maps for People with Low Vision
A hierarchical VQA system aggregates model answers into weighted risk scores that produce four-category safety event maps for urban navigation, backed by a new 20-city dataset where generative MLLMs like Qwen-VL outperform classification models.
-
GuideDog: A Real-World Egocentric Multimodal Dataset for Blind and Low-Vision Accessibility-Aware Guidance
GuideDog supplies 22K egocentric image-description pairs from 46 countries and an 818-sample QA benchmark showing that current multimodal models still struggle with depth perception and BLV-specific guidance rules.