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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…

cs.CV2025

SynapFlow: A Modular Framework Towards Large-Scale Analysis of Dendritic Spines

Pamela Osuna-Vargas, Altug Kamacioglu, Dominik F. Aschauer +5

Dendritic spines are key structural components of excitatory synapses in the brain. Given the size of dendritic spines provides a proxy for synaptic efficacy, their detection and t…

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.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…

cs.CV2024

Self-supervised visual learning from interactions with objects

Arthur Aubret, Céline Teulière, Jochen Triesch

Self-supervised learning (SSL) has revolutionized visual representation learning, but has not achieved the robustness of human vision. A reason for this could be that SSL does not…