collaborators

7 papers

cs.CV2026

Beyond MACs: Hardware Efficient Architecture Design for Vision Backbones

Moritz Nottebaum, Matteo Dunnhofer, Christian Micheloni

Vision backbone networks play a central role in modern computer vision. Enhancing their efficiency directly benefits a wide range of downstream applications. To measure efficiency,…

cs.CV2026

CPUBone: Efficient Vision Backbone Design for Devices with Low Parallelization Capabilities

Moritz Nottebaum, Matteo Dunnhofer, Christian Micheloni

Recent research on vision backbone architectures has predominantly focused on optimizing efficiency for hardware platforms with high parallel processing capabilities. This category…

q-bio.NC2026

The macaque IT cortex but not current artificial vision networks encode object position in perceptually aligned coordinates

Elizaveta Yakubovskaya, Hamidreza Ramezanpour, Matteo Dunnhofer +1

Efficient interaction with the visual world requires not only accurate object identification but also precise localization of objects in space. While spatial ("where") processing h…

q-bio.NC2026

Modeling Dynamic Computations in the Primate Ventral Visual Stream

Matteo Dunnhofer, Maren Wehrheim, Hamidreza Ramezanpour +2

A major goal of computational neuroscience has been to explain how the primate ventral visual stream (VVS) transforms visual input into temporally evolving neural representations t…

cs.CV2026

Better, But Not Sufficient: Testing Video ANNs Against Macaque IT Dynamics

Matteo Dunnhofer, Christian Micheloni, Kohitij Kar

Feedforward artificial neural networks (ANNs) trained on static images remain the dominant models of the the primate ventral visual stream, yet they are intrinsically limited to st…

cs.CV2025

Online Episodic Memory Visual Query Localization with Egocentric Streaming Object Memory

Zaira Manigrasso, Matteo Dunnhofer, Antonino Furnari +6

Episodic memory retrieval enables wearable cameras to recall objects or events previously observed in video. However, existing formulations assume an "offline" setting with full vi…