Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Geuntae Park

dblp:123/0373 · DBLP profile ↗
← Back
1ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · unresolved

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

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 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.

Computer graphics and multimedia
1 paper
Virtual and augmented reality · 50% Computer animation and physical simulation · 50%
Human-computer interaction and pervasive computing
1 paper
Interaction techniques and input · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer animation and physical simulation
motion synthesis
0.912025
TouchWalker: Real-Time Avatar Locomotion from Touchscreen Finger Walking · ISMAR 2025
Interaction techniques and input › gesture input
finger gesture input
0.312025
TouchWalker: Real-Time Avatar Locomotion from Touchscreen Finger Walking · ISMAR 2025
Interaction techniques and input
touch interaction
0.312025
TouchWalker: Real-Time Avatar Locomotion from Touchscreen Finger Walking · ISMAR 2025

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

foot-alignment loss · 1.7MoE-GRU · 1.7
YearPublicationVenuePosition
2025 TouchWalker: Real-Time Avatar Locomotion from Touchscreen Finger Walking
abstract
We present TouchWalker, a real-time system for controlling fullbody avatar locomotion using finger-walking gestures on a touchscreen. The system comprises two main components: TouchWalker-MotionNet, a neural motion generator that synthesizes full-body avatar motion on a per-frame basis from temporally sparse twofinger input, and TouchWalker-UI, a compact touch interface that interprets user touch input to avatar-relative foot positions. Unlike prior systems that rely on symbolic gesture triggers or predefined motion sequences, TouchWalker uses its neural component to generate continuous, context-aware full-body motion on a per-frame basis-including airborne phases such as running, even without input during mid-air steps-enabling more expressive and immediate interaction. To ensure accurate alignment between finger contacts and avatar motion, it employs a MoE-GRU architecture with a dedicated foot-alignment loss. We evaluate TouchWalker in a user study comparing it to a virtual joystick baseline with predefined motion across diverse locomotion tasks. Results show that TouchWalker improves users' sense of embodiment, enjoyment, and immersion.
Geuntae Park, Jiwon Yi, Taehyun Rhee, Kwanguk (Kenny) Kim, Yoonsang Lee 0001
ISMAR1