13 citations · 69 across the 13 of their papers we have counts for
13 papers
Video Understanding with Large Language Models: A Survey
Yolo Y. Tang, Jing Bi, Siting Xu +17
With the burgeoning growth of online video platforms and the escalating volume of video content, the demand for proficient video understanding tools has intensified markedly. Given…
LibFewShot: A Comprehensive Library for Few-shot Learning
Wenbin Li, Ziyi, Wang +9
Few-shot learning, especially few-shot image classification, has received increasing attention and witnessed significant advances in recent years. Some recent studies implicitly sh…
Social Media Study of Public Opinions on Potential COVID-19 Vaccines: Informing Dissent, Disparities, and Dissemination
Hanjia Lyu, Junda Wang, Wei Wu +4
The current development of vaccines for SARS-CoV-2 is unprecedented. Little is known, however, about the nuanced public opinions on the vaccines on social media. We adopt a human-g…
Slender Object Detection: Diagnoses and Improvements
Zhaoyi Wan, Yimin Chen, Sutao Deng +3
In this paper, we are concerned with the detection of a particular type of objects with extreme aspect ratios, namely \textbf{slender objects}. In real-world scenarios, slender obj…
Grounding-Tracking-Integration
Zhengyuan Yang, Tushar Kumar, Tianlang Chen +2
In this paper, we study Tracking by Language that localizes the target box sequence in a video based on a language query. We propose a framework called GTI that decomposes the prob…
SMP Challenge: An Overview of Social Media Prediction Challenge 2019
Bo Wu, Wen-Huang Cheng, Peiye Liu +3
"SMP Challenge" aims to discover novel prediction tasks for numerous data on social multimedia and seek excellent research teams. Making predictions via social multimedia data (e.g…
Fine-grained Mining of Illicit Drug Use Patterns Using Social Multimedia Data from Instagram
Yiheng Zhou, Numair Sani, Jiebo Luo
According to NSDUH (National Survey on Drug Use and Health), 20 million Americans consumed drugs in the past few 30 days. Combating illicit drug use is of great interest to public…
Solving Cold-Start Problem in Large-scale Recommendation Engines: A Deep Learning Approach
Jianbo Yuan, Walid Shalaby, Mohammed Korayem +3
Collaborative Filtering (CF) is widely used in large-scale recommendation engines because of its efficiency, accuracy and scalability. However, in practice, the fact that recommend…
Inferring Restaurant Styles by Mining Crowd Sourced Photos from User-Review Websites
Haofu Liao, Yuncheng Li, Tianran Hu +1
When looking for a restaurant online, user uploaded photos often give people an immediate and tangible impression about a restaurant. Due to their informativeness, such user contri…
Pricing the Woman Card: Gender Politics between Hillary Clinton and Donald Trump
Yu Wang, Yang Feng, Yuncheng Li +3
In this paper, we propose a data-driven method to measure the impact of the 'woman card' exchange between Hillary Clinton and Donald Trump. Building from a unique dataset of the tw…
Voting with Feet: Who are Leaving Hillary Clinton and Donald Trump?
Yu Wang, Yuncheng Li, Quanzeng You +3
From a crowded field with 17 candidates, Hillary Clinton and Donald Trump have emerged as the two front-runners in the 2016 U.S. presidential campaign. The two candidates each boas…
America Tweets China: A Fine-Grained Analysis of the State and Individual Characteristics Regarding Attitudes towards China
Yu Wang, Jianbo Yuan, Jiebo Luo
The U.S.-China relationship is arguably the most important bilateral relationship in the 21st century. Typically it is measured through opinion polls, for example, by Gallup and Pe…
User-Curated Image Collections: Modeling and Recommendation
Yuncheng Li, Yang Cong, Tao Mei +1
Most state-of-the-art image retrieval and recommendation systems predominantly focus on individual images. In contrast, socially curated image collections, condensing distinctive y…