4 papers
Common-Sense Bias Modeling for Classification Tasks
Miao Zhang, Zee fryer, Ben Colman +2
Machine learning model bias can arise from dataset composition: correlated sensitive features can distort the downstream classification model's decision boundary and lead to perfor…
Common Sense Reasoning for Deepfake Detection
Yue Zhang, Ben Colman, Xiao Guo +2
State-of-the-art deepfake detection approaches rely on image-based features extracted via neural networks. While these approaches trained in a supervised manner extract likely fake…
Towards Attention-based Contrastive Learning for Audio Spoof Detection
Chirag Goel, Surya Koppisetti, Ben Colman +2
Vision transformers (ViT) have made substantial progress for classification tasks in computer vision. Recently, Gong et. al. '21, introduced attention-based modeling for several au…
AVFF: Audio-Visual Feature Fusion for Video Deepfake Detection
Trevine Oorloff, Surya Koppisetti, Nicolò Bonettini +5
With the rapid growth in deepfake video content, we require improved and generalizable methods to detect them. Most existing detection methods either use uni-modal cues or rely on…