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Mohamed Elhoseiny

4 papers hereh-index 433 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.GR1
  • eess.AS1
same name
  • Mohamed Elhoseiny — 28 papers, h 27
  • Mohamed Elhoseiny — 6 papers, h 2
  • Mohamed Elhoseiny — 3 papers, h 3
  • Mohamed Elhoseiny — 3 papers, h 1
  • Mohamed Elhoseiny — 3 papers, h 11
  • Mohamed Elhoseiny — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.GR2026

CompoSE: Compositional Synthesis and Editing of 3D Shapes via Part-Aware Control

Habib Slim, Shariq Farooq Bhat, Mohamed Elhoseiny +2

Creating and editing high-quality 3D content remains a central challenge in computer graphics. We address this challenge by introducing CompoSE, a novel method for Compositional Sy…

cs.CV2026

InfinityStory: Unlimited Video Generation with World Consistency and Character-Aware Shot Transitions

Mohamed Elmoghany, Liangbing Zhao, Xiaoqian Shen +27

Generating long-form storytelling videos with consistent visual narratives remains a significant challenge in video synthesis. We present a novel framework, dataset, and a model th…

cs.CV2025

MAGNET: A Multi-agent Framework for Finding Audio-Visual Needles by Reasoning over Multi-Video Haystacks

Sanjoy Chowdhury, Mohamed Elmoghany, Yohan Abeysinghe +5

Large multimodal models (LMMs) have shown remarkable progress in audio-visual understanding, yet they struggle with real-world scenarios that require complex reasoning across exten…

eess.AS2025

Aurelia: Test-time Reasoning Distillation in Audio-Visual LLMs

Sanjoy Chowdhury, Hanan Gani, Nishit Anand +5

Recent advancements in reasoning optimization have greatly enhanced the performance of large language models (LLMs). However, existing work fails to address the complexities of aud…

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