CORTEXA
← Browse

Sepideh Mamooler

2 papers indexed

arxivcs.CVcs.AIq-bio.NCq-bio.QM2026-07-10

Prompting-MammAlps: Fine-Grained Text-to-Video Retrieval for Camera-Trap Data

Valentin Gabeff, Baptiste Maquignaz, Jennifer Shan, Sepideh Mamooler, Gencer Sumbul, Blair Costelloe, et al.

Automatically retrieving videos from large camera-trap datasets remains challenging. Text-to-Video retrieval (TVR) methods based on large video-language models (VLMs) have potential to retrieve events of interest by describing them with simple text queries. However, current metho…

View free PDFSource page
arxivcs.LGcs.AIcs.CLcs.CV2026-07-05

DynaVieW: Schema-Guided World Modeling for Understanding Hierarchical Visual Dynamics

Silin Gao, Hao Zhao, Zeming Chen, Sepideh Mamooler, Antara Raaghavi Bhattacharya, Qiyu Wu, et al.

Multimodal LLMs struggle to systematically model the temporal evolution of visual scenes in videos or multi-image sequences. Such inputs require models to predict or simulate multiple levels of dynamic constituents, such as actions taken in the visual sequence, and the associated…

View free PDFSource page