Demo Data from EDBT 2026 / reviewers in the wild / expert
Hanyu Liao
dblp:119/6719
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2Applied, interdisciplinary, general and emerging computing · 1
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 |
Visual content generation and editing · 44% Audio and music processing · 44% Computer animation and physical simulation · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Audio and music processing › speech synthesis
expressive speech synthesis |
0.2 | 1 | 2013 | WeCard: a multimodal solution for making personalized electronic greeting cards · ACM Multimedia 2013 |
Visual content generation and editing
talking avatar generation |
0.2 | 1 | 2013 | WeCard: a multimodal solution for making personalized electronic greeting cards · ACM Multimedia 2013 |
Computer animation and physical simulation
facial animation |
0.0 | 1 | 2013 | WeCard: a multimodal solution for making personalized electronic greeting cards · ACM Multimedia 2013 |
Methods — techniques the papers use, named apart from their topics
dynamic bayesian network · 0.2MPEG-4 facial animation parameters · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | WeCard: a multimodal solution for making personalized electronic greeting cardsabstractIn this demo, we build a practical system, WeCard, to generate personalized multimodal electronic greeting cards based on parametric emotional talking avatar synthesis technologies. Given user-input greeting text and facial image, WeCard intelligently and automatically generate the personalized speech with expressive lip-motion synchronized facial animation. Besides the parametric talking avatar synthesis, WeCard incorporates two key technologies: 1) automatical face mesh generation algorithm based on MPEG-4 FAPs (Facial Animation Parameters) extracted by the face alignment algorithm; 2) emotional audio-visual speech synchronization algorithm based on DBN. More specifically, WeCard merges the users? preferred electronic card scene with emotional talking avatar animation, turning the final content into flash or video file that can be easily shared with friends. By this way, WeCard can help you make your multimodal greetings to be more attractive, beautiful, and sincere. Huijie Lin, Jia Jia 0001, Hanyu Liao, Lianhong Cai |
ACM Multimedia | 3 |
| 2012 | Image Colorization with an Affective Word
Xiaohui Wang 0004, Jia Jia 0001, Hanyu Liao, Lianhong Cai |
CVM | 3 |
| 2012 | Affective Image Colorization
Xiaohui Wang 0004, Jia Jia 0001, Hanyu Liao, Lianhong Cai |
J. Comput. Sci. Technol. | 3 |