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20242026
most citedCerberusDet: Unified Multi-Dataset Object Detection

1 citations · 1 across the 5 of their papers we have counts for

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cs.CV2026

VIBE: Visual Instruction Based Editor

Grigorii Alekseenko, Aleksandr Gordeev, Irina Tolstykh +7

Instruction-based image editing is among the fastest developing areas in generative AI. Over the past year, the field has reached a new level, with dozens of open-source models rel…

cs.CV2025

NoHumansRequired: Autonomous High-Quality Image Editing Triplet Mining

Maksim Kuprashevich, Grigorii Alekseenko, Irina Tolstykh +4

Recent advances in generative modeling enable image editing assistants that follow natural language instructions without additional user input. Their supervised training requires m…

cs.CV2024

Saliency-Guided DETR for Moment Retrieval and Highlight Detection

Aleksandr Gordeev, Vladimir Dokholyan, Irina Tolstykh +1

Existing approaches for video moment retrieval and highlight detection are not able to align text and video features efficiently, resulting in unsatisfying performance and limited…

cs.CV2024★ 1 cited

CerberusDet: Unified Multi-Dataset Object Detection

Irina Tolstykh, Mikhail Chernyshov, Maksim Kuprashevich

Conventional object detection models are usually limited by the data on which they were trained and by the category logic they define. With the recent rise of Language-Visual Model…

cs.CV2024

Beyond Specialization: Assessing the Capabilities of MLLMs in Age and Gender Estimation

Maksim Kuprashevich, Grigorii Alekseenko, Irina Tolstykh

Multimodal Large Language Models (MLLMs) have recently gained immense popularity. Powerful commercial models like ChatGPT-4V and Gemini, as well as open-source ones such as LLaVA,…