Demo Data from SIGIR 2026 / reviewers in the wild / expert
Peizhong Cong
dblp:167/4017
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 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 |
Multimedia analysis and retrieval · 100% |
Topics — the 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Multimedia analysis and retrieval › image analysis
fashion analysis |
0.2 | 1 | 2015 | Who are the Devils Wearing Prada in New York City? · ACM Multimedia 2015 |
Methods — techniques the papers use, named apart from their topics
learning-based attribute discovery · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Who are the Devils Wearing Prada in New York City?abstractFashion is a perpetual topic in human social life, and the mass has the penchant to emulate what large city residents and celebrities wear. Undeniably, New York City is such a bellwether large city with all kinds of fashion leadership. Consequently, to study what the fashion trends are during this year, it is very helpful to learn the fashion trends of New York City. Discovering fashion trends in New York City could boost many applications such as clothing recommendation and advertising. Does the fashion trend in the New York Fashion Show actually influence the clothing styles on the public? To answer this question, we design a novel system that consists of three major components: (1) constructing a large dataset from the New York Fashion Shows and New York street chic in order to understand the likely clothing fashion trends in New York, (2) utilizing a learning-based approach to discover fashion attributes as the representative characteristics of fashion trends, and (3) comparing the analysis results from the New York Fashion Shows and street-chic images to verify whether the fashion shows have actual influence on the people in New York City. Through the preliminary experiments over a large clothing dataset, we demonstrate the effectiveness of our proposed system, and obtain useful insights on fashion trends and fashion influence. Kuan-Ting Chen, Kezhen Chen, Peizhong Cong, Winston H. Hsu, Jiebo Luo 0001 |
ACM Multimedia | 3 |