4 papers
OpenVAM: Open-World Visual Attention Modeling with VLMs
Kiana Hooshanfar, Amirhossein Kazerouni, Alireza Hosseini +2
Predicting human gaze is a core capability for applications ranging from web/UI design analysis to robotics and human-computer interaction. Yet, most visual attention modeling meth…
AVIS: Adaptive Test-Time Scaling for Vision-Language Models
Ahmadreza Jeddi, Minh Ngoc Le, Amirhossein Kazerouni +8
Modern Vision-Language Models (VLMs) benefit from chain-of-thought prompting and test-time scaling, but these gains often come with prohibitive inference cost due to large visual c…
LIFT: Latent Implicit Functions for Task- and Data-Agnostic Encoding
Amirhossein Kazerouni, Soroush Mehraban, Michael Brudno +1
Implicit Neural Representations (INRs) are proving to be a powerful paradigm in unifying task modeling across diverse data domains, offering key advantages such as memory efficienc…
SUM: Saliency Unification through Mamba for Visual Attention Modeling
Alireza Hosseini, Amirhossein Kazerouni, Saeed Akhavan +2
Visual attention modeling, important for interpreting and prioritizing visual stimuli, plays a significant role in applications such as marketing, multimedia, and robotics. Traditi…