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Yuanhao Zeng

dblp:374/6041 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0003-3607-7384ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Wearable and physiological sensing · 44% Human-AI interaction · 44% Interaction techniques and input · 13%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wearable and physiological sensing › wearable camera
egocentric vision
1.012026
VueBuds: Visual Intelligence with Wireless Earbuds · CHI 2026

Methods — techniques the papers use, named apart from their topics

user study · 1.0power measurement · 1.0
YearPublicationVenuePosition
2026 VueBuds: Visual Intelligence with Wireless Earbuds
abstract
Despite their ubiquity, wireless earbuds remain audio-centric due to size and power constraints. We present VueBuds, the first camera-integrated wireless earbuds for egocentric vision, capable of operating within stringent power and form-factor limits. Each VueBud embeds a camera into a Sony WF-1000XM3 to stream visual data over Bluetooth to a host device for on-device vision language model (VLM) processing. We show analytically and empirically that while each camera’s field of view is partially occluded by the face, the combined binocular perspective provides comprehensive forward coverage. By integrating VueBuds with VLMs, we build an end-to-end system for real-time scene understanding, translation, visual reasoning, and text reading; all from low-resolution monochrome cameras drawing under 5mW through on-demand activation. Through online and in-person user studies with 90 participants, we compare VueBuds against smart glasses across 17 visual question-answering tasks, and show that our system achieves response quality on par with Ray-Ban Meta. Our work establishes low-power camera-equipped earbuds as a compelling platform for visual intelligence, bringing rapidly advancing VLM capabilities to one of the most ubiquitous wearable form factors.
Maruchi Kim, Rasya Fawwaz, Zhi Yang Lim, Brinda Moudgalya, Hexi Wang, Yuanhao Zeng, Shyamnath Gollakota
CHI6