9 citations · 20 across the 11 of their papers we have counts for
13 papers
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…
A Culturally-diverse Multilingual Multimodal Video Benchmark & Model
Bhuiyan Sanjid Shafique, Ashmal Vayani, Muhammad Maaz +26
Large multimodal models (LMMs) have recently gained attention due to their effectiveness to understand and generate descriptions of visual content. Most existing LMMs are in Englis…
MAVOS-DD: Multilingual Audio-Video Open-Set Deepfake Detection Benchmark
Florinel-Alin Croitoru, Vlad Hondru, Marius Popescu +3
We present the first large-scale open-set benchmark for multilingual audio-video deepfake detection. Our dataset comprises nearly 350 hours of real and fake videos across eight lan…
Agent-X: Evaluating Deep Multimodal Reasoning in Vision-Centric Agentic Tasks
Tajamul Ashraf, Amal Saqib, Hanan Ghani +11
Deep reasoning is fundamental for solving complex tasks, especially in vision-centric scenarios that demand sequential, multimodal understanding. However, existing benchmarks typic…
LLM Post-Training: A Deep Dive into Reasoning Large Language Models
Komal Kumar, Tajamul Ashraf, Omkar Thawakar +7
Large Language Models (LLMs) have transformed the natural language processing landscape and brought to life diverse applications. Pretraining on vast web-scale data has laid the fo…
LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs
Omkar Thawakar, Dinura Dissanayake, Ketan More +12
Reasoning is a fundamental capability for solving complex multi-step problems, particularly in visual contexts where sequential step-wise understanding is essential. Existing appro…
Deepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlook
Florinel-Alin Croitoru, Andrei-Iulian Hiji, Vlad Hondru +7
We survey deepfake generation and detection techniques, covering all deepfake media types: image, video, audio and multimodal content. We identify various kinds of deepfakes and co…
All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages
Ashmal Vayani, Dinura Dissanayake, Hasindri Watawana +66
Existing Large Multimodal Models (LMMs) generally focus on only a few regions and languages. As LMMs continue to improve, it is increasingly important to ensure they understand cul…
Composed Video Retrieval via Enriched Context and Discriminative Embeddings
Omkar Thawakar, Muzammal Naseer, Rao Muhammad Anwer +4
Composed video retrieval (CoVR) is a challenging problem in computer vision which has recently highlighted the integration of modification text with visual queries for more sophist…
AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulation
Yuning Cui, Syed Waqas Zamir, Salman Khan +3
In the image acquisition process, various forms of degradation, including noise, haze, and rain, are frequently introduced. These degradations typically arise from the inherent lim…
PG-Video-LLaVA: Pixel Grounding Large Video-Language Models
Shehan Munasinghe, Rusiru Thushara, Muhammad Maaz +4
Extending image-based Large Multimodal Models (LMMs) to videos is challenging due to the inherent complexity of video data. The recent approaches extending image-based LMMs to vide…
Videoprompter: an ensemble of foundational models for zero-shot video understanding
Adeel Yousaf, Muzammal Naseer, Salman Khan +2
Vision-language models (VLMs) classify the query video by calculating a similarity score between the visual features and text-based class label representations. Recently, large lan…
Egocentric RGB+Depth Action Recognition in Industry-Like Settings
Jyoti Kini, Sarah Fleischer, Ishan Dave +1
Action recognition from an egocentric viewpoint is a crucial perception task in robotics and enables a wide range of human-robot interactions. While most computer vision approaches…