46 citations · 54 across the 4 of their papers we have counts for
4 papers
DASH: Visual Analytics for Debiasing Image Classification via User-Driven Synthetic Data Augmentation
Bum Chul Kwon, Jungsoo Lee, Chaeyeon Chung +3
Image classification models often learn to predict a class based on irrelevant co-occurrences between input features and an output class in training data. We call the unwanted corr…
Improving Face Recognition with Large Age Gaps by Learning to Distinguish Children
Jungsoo Lee, Jooyeol Yun, Sunghyun Park +2
Despite the unprecedented improvement of face recognition, existing face recognition models still show considerably low performances in determining whether a pair of child and adul…
Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation
Sanghun Jung, Jungsoo Lee, Daehoon Gwak +2
Identifying unexpected objects on roads in semantic segmentation (e.g., identifying dogs on roads) is crucial in safety-critical applications. Existing approaches use images of une…
Learning Debiased Representation via Disentangled Feature Augmentation
Jungsoo Lee, Eungyeup Kim, Juyoung Lee +2
Image classification models tend to make decisions based on peripheral attributes of data items that have strong correlation with a target variable (i.e., dataset bias). These bias…