arXiv AI By Md Raisul Kibria, S\'ebastien Lafond

Assessing Representation Semantics Under Language Pretraining in Fine-Grained Classification

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arXiv Computer Vision
Sep 28

OpenVAM: Open-World Visual Attention Modeling with VLMs

OpenVAM is a new framework for visual attention modeling that combines a dense saliency map with language‑based explanations. It uses a decoupled design: a visual pathway for precise localization and a vision‑language head that generates grounded what/why explanations. The method is trained in three stages to preserve localization while adding language grounding, and a scalable pipeline creates multi‑domain annotations for evaluation.

By Kiana Hooshanfar, Amirhossein Kazerouni, Alireza Hosseini, Michael Brudno, Babak Taati