7 papers · 1 filter
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…
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…
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…
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…
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…
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…