4 papers · 1 filter
World in a Frame: Understanding Culture Mixing as a New Challenge for Vision-Language Models
Eunsu Kim, Junyeong Park, Na Min An +9
In a globalized world, cultural elements from diverse origins frequently appear together within a single visual scene. We refer to these as culture mixing scenarios, yet how Large…
Are Large Vision-Language Models Ready to Guide Blind and Low-Vision Individuals?
Eunki Kim, Na Min An, Wan Ju Kang +3
Large Vision-Language Models (LVLMs) demonstrate a promising direction for assisting individuals with blindness or low-vision (BLV). Yet, measuring their true utility in real-world…
Blind to Position, Biased in Language: Probing Mid-Layer Representational Bias in Vision-Language Encoders for Zero-Shot Language-Grounded Spatial Understanding
Na Min An, Inha Kang, Minhyun Lee +1
Vision-Language Encoders (VLEs) are widely adopted as the backbone of zero-shot referring image segmentation (RIS), enabling text-guided localization without task-specific training…
How Blind and Low-Vision Individuals Prefer Large Vision-Language Model-Generated Scene Descriptions
Na Min An, Eunki Kim, Wan Ju Kang +3
For individuals with blindness or low vision (BLV), navigating complex environments can pose serious risks. Large Vision-Language Models (LVLMs) show promise for generating scene d…