collaborators

7 papers

cs.CV2026

Temporal Slowness in Central Vision Drives Semantic Object Learning

Timothy Schaumlöffel, Arthur Aubret, Gemma Roig +1

Humans acquire semantic object representations from egocentric visual streams with minimal supervision, but the underlying mechanisms remain unclear. Importantly, the visual system…

q-bio.NC2025

Re-assessing the evidence for mental rotation abilities in children using computational models

Arthur Aubret, Jochen Triesch

There is strong and diverse evidence for mental rotation (MR) abilities in adults. However, current evidence for MR in children rests on just a few behavioral paradigms adapted fro…

cs.CV2025

Simulated Cortical Magnification Supports Self-Supervised Object Learning

Zhengyang Yu, Arthur Aubret, Chen Yu +1

Recent self-supervised learning models simulate the development of semantic object representations by training on visual experience similar to that of toddlers. However, these mode…

cs.RO2025

MIMo grows! Simulating body and sensory development in a multimodal infant model

Francisco M. López, Miles Lenz, Marco G. Fedozzi +2

Infancy is characterized by rapid body growth and an explosive change of sensory and motor abilities. However, developmental robots and simulation platforms are typically designed…

cs.CV2025

Toddlers' Active Gaze Behavior Supports Self-Supervised Object Learning

Zhengyang Yu, Arthur Aubret, Marcel C. Raabe +3

Toddlers learn to recognize objects from different viewpoints with almost no supervision. During this learning, they execute frequent eye and head movements that shape their visual…

cs.CV2025

Human Gaze Boosts Object-Centered Representation Learning

Timothy Schaumlöffel, Arthur Aubret, Gemma Roig +1

Recent self-supervised learning (SSL) models trained on human-like egocentric visual inputs substantially underperform on image recognition tasks compared to humans. These models t…