6 citations · 10 across the 5 of their papers we have counts for
6 papers
ProtoFair: Fair Self-Supervised Contrastive Learning via Pseudo-Counterfactual Pairs
Marah Halawa, Olaf Hellwich
Self-supervised learning methods learn high-quality visual representations, yet recent studies show that these representations often capture demographic biases present in the train…
Multi-Task Multi-Modal Self-Supervised Learning for Facial Expression Recognition
Marah Halawa, Florian Blume, Pia Bideau +3
Human communication is multi-modal; e.g., face-to-face interaction involves auditory signals (speech) and visual signals (face movements and hand gestures). Hence, it is essential…
WiCV@CVPR2023: The Eleventh Women In Computer Vision Workshop at the Annual CVPR Conference
Doris Antensteiner, Marah Halawa, Asra Aslam +6
In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2023, organized alongside the hybrid CVPR 2023 in Vancouver, Canada. WiCV aims to amplify the voic…
WiCV 2022: The Tenth Women In Computer Vision Workshop
Doris Antensteiner, Silvia Bucci, Arushi Goel +6
In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2022, organized alongside the hybrid CVPR 2022 in New Orleans, Louisiana. It provides a voice to a…
Action-based Contrastive Learning for Trajectory Prediction
Marah Halawa, Olaf Hellwich, Pia Bideau
Trajectory prediction is an essential task for successful human robot interaction, such as in autonomous driving. In this work, we address the problem of predicting future pedestri…
Learning Disentangled Expression Representations from Facial Images
Marah Halawa, Manuel Wöllhaf, Eduardo Vellasques +2
Face images are subject to many different factors of variation, especially in unconstrained in-the-wild scenarios. For most tasks involving such images, e.g. expression recognition…