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Shiqi Yan

dblp:380/5143 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2026
0000-0002-5679-3906ORCID · reported

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

Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 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.

Computer graphics and multimedia
1 paper
Virtual and augmented reality · 100%
Artificial intelligence
1 paper
Information extraction and text analysis · 50% Question answering and dialogue systems · 50%
Human-computer interaction and pervasive computing
1 paper
Human-AI interaction · 100%

Topics — the 9 heaviest of 9, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Question answering and dialogue systems › dialogue generation
emotional response generation
1.012026
Persona-E²: A Human-Grounded Dataset for Personality-Shaped Emotional Responses to Textual Events · ACL (1) 2026
Natural language and speech › Information extraction and text analysis
sentiment analysis
1.012026
Persona-E²: A Human-Grounded Dataset for Personality-Shaped Emotional Responses to Textual Events · ACL (1) 2026
Human-AI interaction
affective computing
1.012026
Persona-E²: A Human-Grounded Dataset for Personality-Shaped Emotional Responses to Textual Events · ACL (1) 2026
Virtual and augmented reality › haptics
haptic feedback
0.812024
Redirected Walking on Omnidirectional Treadmill · IEEE Trans. Vis. Comput. Graph. 2024
Virtual and augmented reality › immersive interaction › 3d interaction
locomotion in virtual environments
0.812024
Redirected Walking on Omnidirectional Treadmill · IEEE Trans. Vis. Comput. Graph. 2024
Virtual and augmented reality › locomotion interfaces
omnidirectional treadmill
0.812024
Redirected Walking on Omnidirectional Treadmill · IEEE Trans. Vis. Comput. Graph. 2024
Virtual and augmented reality › locomotion
redirected walking
0.812024
Redirected Walking on Omnidirectional Treadmill · IEEE Trans. Vis. Comput. Graph. 2024
Virtual and augmented reality › immersive interaction
VR interaction
0.812024
Redirected Walking on Omnidirectional Treadmill · IEEE Trans. Vis. Comput. Graph. 2024
Virtual and augmented reality
locomotion interfaces
0.212024
Redirected Walking on Omnidirectional Treadmill · IEEE Trans. Vis. Comput. Graph. 2024

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

human-grounded dataset construction · 2.0steer-to-multi-target · 0.8steer-to-multi-direction · 0.8simulation · 0.8
YearPublicationVenuePosition
2026 Persona-E²: A Human-Grounded Dataset for Personality-Shaped Emotional Responses to Textual Events
abstract
Yuqin Yang, Haowu Zhou, Haoran Tu, Zhiwen Hui, Shiqi Yan, HaoYang Li, Dong She, Xianrong Yao, Yang Gao, Zhanpeng Jin. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.
Yuqin Yang, Haowu Zhou, Haoran Tu, Zhiwen Hui, Shiqi Yan, HaoYang Li, Dong She, Xianrong Yao, Yang Gao 0025, Zhanpeng Jin
ACL (1)5
2024 Redirected Walking on Omnidirectional Treadmill
abstract
Redirected walking (RDW) and omnidirectional treadmill (ODT) are two effective solutions to the natural locomotion interface in virtual reality. ODT fully compresses the physical space and can be used as the integration carrier of all kinds of devices. However, the user experience varies in different directions of ODT, and the premise of interaction between users and integrated devices is a good match between virtual and real objects. RDW technology uses visual cues to guide the user's location in physical space. Based on this principle, combining RDW technology with ODT to guide the user's walking direction through visual cues can effectively improve user experience on ODT and make full use of various devices integrated on ODT. This paper explores the novel prospects of combining RDW technology with ODT and formally puts forward the concept of O-RDW (ODT-based RDW). Two baseline algorithms, i.e., OS2MD (ODT-based steer to multi-direction), and OS2MT (ODT-based steer to multi-target), are proposed to combine the merits of both RDW and ODT. With the help of the simulation environment, this paper quantitatively analyzes the applicable scenarios of the two algorithms and the influence of several main factors on the performance. Based on the conclusions of the simulation experiments, the two O-RDW algorithms are successfully applied in the practical application case of multi-target haptic feedback. Combined with the user study, the practicability and effectiveness of O-RDW technology in practical use are further verified.
Yiye Wang, Shiqi Yan, Zhongzheng Zhu, Kan-Jian Zhang, Haikun Wei
IEEE Trans. Vis. Comput. Graph.3