5 accepted papers
Deep learning based fall detection is one of the crucial tasks for intelligent video surveillance systems, which aims to detect unintentional falls of humans and alarm dangerous situations. In this work, we propose a simple and efficient framework to detect falls through a single and small-sized con…
Learning visual representation of high quality is essential for image classification. Recently, a series of contrastive representation learning methods have achieved preeminent success. Particularly, SupCon outperformed the dominant methods based on cross-entropy loss in representation learning. How…
Although AI systems archive a great success in various societal fields, there still exists a challengeable issue of outputting discriminatory results with respect to protected attributes (e.g., gender and age). The popular approach to solving the issue is to remove protected attribute information in…
With great research advances on Brain-Computer-Interface (BCI) systems, Electroencephalography (EEG) based driver fatigue state classification models have shown its effectiveness. However, EEG signals contain large differences between individuals, making it hard to build a unified model among indivi…
Fairness becomes a critical issue of computer vision to reduce discriminative factors in various systems. Among computer vision tasks, Image-to-Image translation for facial attributes editing can yield discriminative results. The unexpected gender changed results can be generated instead of editing…