36 citations · 65 across the 9 of their papers we have counts for
10 papers
Revisiting Scene Graph Generation from the Perspective of Detector-Conditioned Reachability
Runfeng Qu, Pia K Bideau, Ole Hall +3
Scene graph generation (SGG) approaches can be broadly classified into detector-based and query-based methods according to their underlying reasoning mechanisms. However, the discr…
Salience-SGG: Enhancing Unbiased Scene Graph Generation with Iterative Salience Estimation
Runfeng Qu, Ole Hall, Pia K Bideau +4
Scene Graph Generation (SGG) suffers from a long-tailed distribution, where a few predicate classes dominate while many others are underrepresented, leading to biased models that u…
How Do You Perceive My Face? Recognizing Facial Expressions in Multi-Modal Context by Modeling Mental Representations
Florian Blume, Runfeng Qu, Pia Bideau +3
Facial expression perception in humans inherently relies on prior knowledge and contextual cues, contributing to efficient and flexible processing. For instance, multi-modal emotio…
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…
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…
The Right Spin: Learning Object Motion from Rotation-Compensated Flow Fields
Pia Bideau, Erik Learned-Miller, Cordelia Schmid +1
Both a good understanding of geometrical concepts and a broad familiarity with objects lead to our excellent perception of moving objects. The human ability to detect and segment m…