22 citations · 23 across the 9 of their papers we have counts for
10 papers
Beyond Similarity: Foundation Models as an Efficient Backbone for Training-Free Composed Video Retrieval
Dmitry Demidov, Muhammad Zaigham Zaheer, Omkar Thawakar +2
Composed video retrieval (CoVR) searches a gallery for the target video that realizes a natural-language modification of a source clip. However, at gallery scale, this creates a fu…
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…
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…
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…
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…
TransResNet: Integrating the Strengths of ViTs and CNNs for High Resolution Medical Image Segmentation via Feature Grafting
Muhammad Hamza Sharif, Dmitry Demidov, Asif Hanif +2
High-resolution images are preferable in medical imaging domain as they significantly improve the diagnostic capability of the underlying method. In particular, high resolution hel…
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…
Distilling Local Texture Features for Colorectal Tissue Classification in Low Data Regimes
Dmitry Demidov, Roba Al Majzoub, Amandeep Kumar +1
Multi-class colorectal tissue classification is a challenging problem that is typically addressed in a setting, where it is assumed that ample amounts of training data is available…
Salient Mask-Guided Vision Transformer for Fine-Grained Classification
Dmitry Demidov, Muhammad Hamza Sharif, Aliakbar Abdurahimov +2
Fine-grained visual classification (FGVC) is a challenging computer vision problem, where the task is to automatically recognise objects from subordinate categories. One of its mai…
Object Detection in Aerial Imagery
Dmitry Demidov, Rushali Grandhe, Salem AlMarri
Object detection in natural images has achieved remarkable results over the years. However, a similar progress has not yet been observed in aerial object detection due to several c…