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

Jiawang Yu

dblp:338/4835 · DBLP profile ↗
← Back
3ranked-venue papers
1as first author
3since 2021 · last 2024
—ORCID · conflict

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

Artificial intelligence and machine learning · 2 · 2 since 2021Graphics, computer vision, multimedia, augmented reality and games · 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
Computer animation and physical simulation · 50% Geometric modeling and processing · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer animation and physical simulation
cloth animation
0.812024
Super-Resolution Cloth Animation with Spatial and Temporal Coherence · ACM Trans. Graph. 2024
Geometric modeling and processing
mesh processing
0.812024
Super-Resolution Cloth Animation with Spatial and Temporal Coherence · ACM Trans. Graph. 2024

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

patch decomposition · 0.8mesh-based super-resolution · 0.8cloth simulation · 0.8
YearPublicationVenuePosition
2024 Similar norm more transferable: Rethinking feature norms discrepancy in adversarial domain adaptation
Jun Dan, Mushui Liu, Chunfeng Xie, Jiawang Yu, Haoran Xie 0004, Ruokun Li, Shunjie Dong
Knowl. Based Syst.4
2024 Super-Resolution Cloth Animation with Spatial and Temporal Coherence
abstract
Creating super-resolution cloth animations, which refine coarse cloth meshes with fine wrinkle details, faces challenges in preserving spatial consistency and temporal coherence across frames. In this paper, we introduce a general framework to address these issues, leveraging two core modules. The first module interleaves a simulator and a corrector. The simulator handles cloth dynamics, while the corrector rectifies differences in low-frequency features across various resolutions. This interleaving ensures prompt correction of spatial errors from the coarse simulation, effectively preventing their temporal propagation. The second module performs mesh-based super-resolution for detailed wrinkle enhancements. We decompose garment meshes into overlapping patches for adaptability to various styles and geometric continuity. Our method achieves an 8× improvement in resolution for cloth animations. We showcase the effectiveness of our method through diverse animation examples, including simple cloth pieces and intricate garments.
Jiawang Yu, Zhendong Wang 0001
ACM Trans. Graph.1
2023 HOMDA: High-Order Moment-Based Domain Alignment for unsupervised domain adaptation
Jun Dan, Hao Chi, Jiawang Yu, Jinhai Zhou
Knowl. Based Syst.5