collaborators

9 papers

cs.HC2026

BlurDriving: Investigating How Personalized Blur Techniques Impact Drivers' Performance in Virtual Reality

Yuan Li, Mark Colley, Xinyue Gui +4

Distracted driving remains a major safety concern, motivating approaches that aim to reduce visual overload before attention breaks down. However, visual overload varies across ind…

cs.HC2026

See2Refine: Vision-Language Feedback Improves LLM-Based eHMI Action Designers

Ding Xia, Xinyue Gui, Mark Colley +5

Automated vehicles lack natural communication channels with other road users, making external Human-Machine Interfaces (eHMIs) essential for conveying intent and maintaining trust…

cs.HC2026

Exploring the Role of User Comments Throughout the Stages of Video-Based Task-Learning

Nayoung Kim, Yotam Sechayk, Zhongyi Zhou +1

Learning tasks through videos is a dynamic way to acquire skills by witnessing entire processes. However, compared to in-person demonstrations, videos may omit tacit knowledge, inc…

cs.HC2026

Improving Low-Vision Chart Accessibility via On-Cursor Visual Context

Yotam Sechayk, Hennes Rave, Max Rädler +4

Despite widespread use, charts remain largely inaccessible for Low-Vision Individuals (LVI). Reading charts requires viewing data points within a global context, which is difficult…

cs.HC2025

TailCue: Exploring Animal-inspired Robotic Tail for Automated Vehicles Interaction

Yuan Li, Xinyue Gui, Ding Xia +2

Automated vehicles (AVs) are gradually becoming part of our daily lives. However, effective communication between road users and AVs remains a significant challenge. Although vario…

cs.GR2025

MiGumi: Making Tightly Coupled Integral Joints Millable

Aditya Ganeshan, Kurt Fleischer, Wenzel Jakob +4

Traditional integral wood joints, despite their strength, durability, and elegance, remain rare in modern workflows due to the cost and difficulty of manual fabrication. CNC millin…