141 citations · 284 across the 14 of their papers we have counts for
14 papers
FairGRAPE: Fairness-aware GRAdient Pruning mEthod for Face Attribute Classification
Xiaofeng Lin, Seungbae Kim, Jungseock Joo
Existing pruning techniques preserve deep neural networks' overall ability to make correct predictions but may also amplify hidden biases during the compression process. We propose…
Explaining Deep Convolutional Neural Networks via Latent Visual-Semantic Filter Attention
Yu Yang, Seungbae Kim, Jungseock Joo
Interpretability is an important property for visual models as it helps researchers and users understand the internal mechanism of a complex model. However, generating semantic exp…
Emergent Graphical Conventions in a Visual Communication Game
Shuwen Qiu, Sirui Xie, Lifeng Fan +4
Humans communicate with graphical sketches apart from symbolic languages. Primarily focusing on the latter, recent studies of emergent communication overlook the sketches; they do…
Understanding and Mitigating Annotation Bias in Facial Expression Recognition
Yunliang Chen, Jungseock Joo
The performance of a computer vision model depends on the size and quality of its training data. Recent studies have unveiled previously-unknown composition biases in common image…
Communicative Learning with Natural Gestures for Embodied Navigation Agents with Human-in-the-Scene
Qi Wu, Cheng-Ju Wu, Yixin Zhu +1
Human-robot collaboration is an essential research topic in artificial intelligence (AI), enabling researchers to devise cognitive AI systems and affords an intuitive means for use…
Who Blames or Endorses Whom? Entity-to-Entity Directed Sentiment Extraction in News Text
Kunwoo Park, Zhufeng Pan, Jungseock Joo
Understanding who blames or supports whom in news text is a critical research question in computational social science. Traditional methods and datasets for sentiment analysis are,…
Gender Slopes: Counterfactual Fairness for Computer Vision Models by Attribute Manipulation
Jungseock Joo, Kimmo Kärkkäinen
Automated computer vision systems have been applied in many domains including security, law enforcement, and personal devices, but recent reports suggest that these systems may pro…
FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age
Kimmo Kärkkäinen, Jungseock Joo
Existing public face datasets are strongly biased toward Caucasian faces, and other races (e.g., Latino) are significantly underrepresented. This can lead to inconsistent model acc…
Understanding the Political Ideology of Legislators from Social Media Images
Nan Xi, Di Ma, Marcus Liou +3
In this paper, we seek to understand how politicians use images to express ideological rhetoric through Facebook images posted by members of the U.S. House and Senate. In the era o…
Image as Data: Automated Visual Content Analysis for Political Science
Jungseock Joo, Zachary C. Steinert-Threlkeld
Image data provide unique information about political events, actors, and their interactions which are difficult to measure from or not available in text data. This article introdu…
Protest Activity Detection and Perceived Violence Estimation from Social Media Images
Donghyeon Won, Zachary C. Steinert-Threlkeld, Jungseock Joo
We develop a novel visual model which can recognize protesters, describe their activities by visual attributes and estimate the level of perceived violence in an image. Studies of…
Cultural Diffusion and Trends in Facebook Photographs
Quanzeng You, Darío García-García, Mahohar Paluri +2
Online social media is a social vehicle in which people share various moments of their lives with their friends, such as playing sports, cooking dinner or just taking a selfie for…
Fashion Conversation Data on Instagram
Yu-I Ha, Sejeong Kwon, Meeyoung Cha +1
The fashion industry is establishing its presence on a number of visual-centric social media like Instagram. This creates an interesting clash as fashion brands that have tradition…
Joint Image-Text News Topic Detection and Tracking with And-Or Graph Representation
Weixin Li, Jungseock Joo, Hang Qi +1
In this paper, we aim to develop a method for automatically detecting and tracking topics in broadcast news. We present a hierarchical And-Or graph (AOG) to jointly represent the l…