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cs.CV2026

CoVR-R:Reason-Aware Composed Video Retrieval

Omkar Thawakar, Dmitry Demidov, Vaishnav Potlapalli +5

Composed Video Retrieval (CoVR) aims to find a target video given a reference video and a textual modification. Prior work assumes the modification text fully specifies the visual…

cs.CV2025

Thinking Beyond Labels: Vocabulary-Free Fine-Grained Recognition using Reasoning-Augmented LMMs

Dmitry Demidov, Zaigham Zaheer, Zongyan Han +2

Vocabulary-free fine-grained image recognition aims to distinguish visually similar categories within a meta-class without a fixed, human-defined label set. Existing solutions for…

cs.CV2025

Beyond Simple Edits: Composed Video Retrieval with Dense Modifications

Omkar Thawakar, Dmitry Demidov, Ritesh Thawkar +4

Composed video retrieval is a challenging task that strives to retrieve a target video based on a query video and a textual description detailing specific modifications. Standard r…

cs.CV2025

Vocabulary-free Fine-grained Visual Recognition via Enriched Contextually Grounded Vision-Language Model

Dmitry Demidov, Zaigham Zaheer, Omkar Thawakar +2

Fine-grained image classification, the task of distinguishing between visually similar subcategories within a broader category (e.g., bird species, car models, flower types), is a…

cs.CV2024

Extract More from Less: Efficient Fine-Grained Visual Recognition in Low-Data Regimes

Dmitry Demidov, Abduragim Shtanchaev, Mihail Mihaylov +1

The emerging task of fine-grained image classification in low-data regimes assumes the presence of low inter-class variance and large intra-class variation along with a highly limi…