44 citations · 62 across the 11 of their papers we have counts for
11 papers
Appearance Debiased Gaze Estimation via Stochastic Subject-Wise Adversarial Learning
Suneung Kim, Woo-Jeoung Nam, Seong-Whan Lee
Recently, appearance-based gaze estimation has been attracting attention in computer vision, and remarkable improvements have been achieved using various deep learning techniques.…
Towards Better Visualizing the Decision Basis of Networks via Unfold and Conquer Attribution Guidance
Jung-Ho Hong, Woo-Jeoung Nam, Kyu-Sung Jeon +1
Revealing the transparency of Deep Neural Networks (DNNs) has been widely studied to describe the decision mechanisms of network inner structures. In this paper, we propose a novel…
Multi-Contextual Predictions with Vision Transformer for Video Anomaly Detection
Joo-Yeon Lee, Woo-Jeoung Nam, Seong-Whan Lee
Video Anomaly Detection(VAD) has been traditionally tackled in two main methodologies: the reconstruction-based approach and the prediction-based one. As the reconstruction-based m…
Illuminating Salient Contributions in Neuron Activation with Attribution Equilibrium
Woo-Jeoung Nam, Seong-Whan Lee
With the remarkable success of deep neural networks, there is a growing interest in research aimed at providing clear interpretations of their decision-making processes. In this pa…
Few-Shot Object Detection with Proposal Balance Refinement
Sueyeon Kim, Woo-Jeoung Nam, Seong-Whan Lee
Few-shot object detection has gained significant attention in recent years as it has the potential to greatly reduce the reliance on large amounts of manually annotated bounding bo…
Style-Guided Domain Adaptation for Face Presentation Attack Detection
Young-Eun Kim, Woo-Jeoung Nam, Kyungseo Min +1
Domain adaptation (DA) or domain generalization (DG) for face presentation attack detection (PAD) has attracted attention recently with its robustness against unseen attack scenari…
Improving Interpretability of Deep Neural Networks in Medical Diagnosis by Investigating the Individual Units
Woo-Jeoung Nam, Seong-Whan Lee
As interpretability has been pointed out as the obstacle to the adoption of Deep Neural Networks (DNNs), there is an increasing interest in solving a transparency issue to guarante…
Interpreting Deep Neural Networks with Relative Sectional Propagation by Analyzing Comparative Gradients and Hostile Activations
Woo-Jeoung Nam, Jaesik Choi, Seong-Whan Lee
The clear transparency of Deep Neural Networks (DNNs) is hampered by complex internal structures and nonlinear transformations along deep hierarchies. In this paper, we propose a n…
Rotation Invariant Aerial Image Retrieval with Group Convolutional Metric Learning
Hyunseung Chung, Woo-Jeoung Nam, Seong-Whan Lee
Remote sensing image retrieval (RSIR) is the process of ranking database images depending on the degree of similarity compared to the query image. As the complexity of RSIR increas…
A Two-Stream Symmetric Network with Bidirectional Ensemble for Aerial Image Matching
Jae-Hyun Park, Woo-Jeoung Nam, Seong-Whan Lee
In this paper, we propose a novel method to precisely match two aerial images that were obtained in different environments via a two-stream deep network. By internally augmenting t…
Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks
Woo-Jeoung Nam, Shir Gur, Jaesik Choi +2
As Deep Neural Networks (DNNs) have demonstrated superhuman performance in a variety of fields, there is an increasing interest in understanding the complex internal mechanisms of…