arXiv:2610.17154v2 Announce Type: replace-cross
Abstract: Decoding visual stimuli from the spiking activity of retinal ganglion cells (RGCs) informs both our understanding of the retinal code and the...
By Ning Zhang, Arto Nurmikko
FoAViS is a foveated active vision system that samples visual input using a log‑polar foveation and stores information in a 2D spatial memory. The system’s fixation policy is trained concurrently with tasks such as classification and semantic segmentation, allowing the same memory to be read out globally or densely without architectural changes. Learned fixation policies outperform non‑learned heuristics, improving task performance and producing scanpaths that resemble human gaze behavior.
By Valentin Hassler, Jonathan Henrich, Yoha\"i-Eliel Berreby, Haoze Zhu, Alexander Ecker
arXiv:2609.24136v1 Announce Type: new
Abstract: Brain-to-image retrieval seeks to identify the visual stimulus that elicited a non-invasive neural response. Candidate images are typically represented...
By Ye Wang, HaoKun Ren, Hong Yu, Ruirui Li, Xiao Li, Ke Liu, Wei Wu
Brain-to-image retrieval seeks to identify the visual stimulus that elicited a non-invasive neural response. Candidate images are typically represented by pretrained vision models, whose internal repr...
arXiv:2603. 18846v3 Announce Type: replace-cross Abstract: Foundation models are used to extract transferable representations from large amounts of unlabeled data, typically via self-supervised learning (SSL).
By Samuel Ofosu Mensah, Camila Roa, Kerol Djoumessi, Philipp Berens
OptiModNet is a lightweight UNet‑Transformer hybrid designed for optic disc and cup segmentation. It incorporates grouped‑query and channel attention across multiple stages, along with an Aggregated Pyramid Loss to improve gradient flow and structural consistency. Evaluated on the REFUGE2 dataset, it surpasses existing methods by over 2.5 % while using only 3.73 GFLOPs and 1.93 M parameters.
By Soumili Ghosh, Debapriya Roy, Aryan Das, Bikash Santra