84 citations · 199 across the 31 of their papers we have counts for
31 papers
Improving Fairness using Vision-Language Driven Image Augmentation
Moreno D'Incà, Christos Tzelepis, Ioannis Patras +1
Fairness is crucial when training a deep-learning discriminative model, especially in the facial domain. Models tend to correlate specific characteristics (such as age and skin col…
Flow Factorized Representation Learning
Yue Song, T. Anderson Keller, Nicu Sebe +1
A prominent goal of representation learning research is to achieve representations which are factorized in a useful manner with respect to the ground truth factors of variation. Th…
CNNs for JPEGs: A Study in Computational Cost
Samuel Felipe dos Santos, Nicu Sebe, Jurandy Almeida
Convolutional neural networks (CNNs) have achieved astonishing advances over the past decade, defining state-of-the-art in several computer vision tasks. CNNs are capable of learni…
Tightening Classification Boundaries in Open Set Domain Adaptation through Unknown Exploitation
Lucas Fernando Alvarenga e Silva, Nicu Sebe, Jurandy Almeida
Convolutional Neural Networks (CNNs) have brought revolutionary advances to many research areas due to their capacity of learning from raw data. However, when those methods are app…
Turn Fake into Real: Adversarial Head Turn Attacks Against Deepfake Detection
Weijie Wang, Zhengyu Zhao, Nicu Sebe +1
Malicious use of deepfakes leads to serious public concerns and reduces people's trust in digital media. Although effective deepfake detectors have been proposed, they are substant…
Compositional Semantic Mix for Domain Adaptation in Point Cloud Segmentation
Cristiano Saltori, Fabio Galasso, Giuseppe Fiameni +3
Deep-learning models for 3D point cloud semantic segmentation exhibit limited generalization capabilities when trained and tested on data captured with different sensors or in vary…