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cs.CV2026

HAJJv2-CrowdCount: Zero-Shot Benchmark for Dense Crowd Counting

Reem AlYabis, Fares AlTuwaim, AlJawharh AlOtaibi +1

Automated crowd counting in Hajj video is difficult not because current models lack capacity, but because the footage violates the assumptions those models were built on: cameras o…

cs.CV2026

GridProbe: Posterior-Probing for Adaptive Test-Time Compute in Long-Video VLMs

Mohamed Eltahir, Lama Ayash, Ali Habibullah +2

Long-video understanding in VLMs is bottlenecked by a single monolithic forward pass over thousands of frames at quadratic attention cost. A common mitigation is to first select a…

cs.CV2026

VideoAtlas: Navigating Long-Form Video in Logarithmic Compute

Mohamed Eltahir, Ali Habibullah, Yazan Alshoibi +3

Extending language models to video introduces two challenges: representation, where existing methods rely on lossy approximations, and long-context, where caption- or agent-based p…

cs.CV2026

GridVAD: Open-Set Video Anomaly Detection via Spatial Reasoning over Stratified Frame Grids

Mohamed Eltahir, Ahmed O. Ibrahim, Obada Siralkhatim +2

Vision-Language Models (VLMs) are powerful open-set reasoners, yet their direct use as anomaly detectors in video surveillance is fragile: without calibrated anomaly priors, they a…

cs.CV2025

Vote-in-Context: Turning VLMs into Zero-Shot Rank Fusers

Mohamed Eltahir, Ali Habibullah, Lama Ayash +2

In the retrieval domain, candidates' fusion from heterogeneous retrievers is a long-standing challenge, particularly for complex, multi-modal data such as videos. While typical fus…

cs.CV2025

AutoArabic: A Three-Stage Framework for Localizing Video-Text Retrieval Benchmarks

Mohamed Eltahir, Osamah Sarraj, Abdulrahman Alfrihidi +4

Video-to-text and text-to-video retrieval are dominated by English benchmarks (e.g. DiDeMo, MSR-VTT) and recent multilingual corpora (e.g. RUDDER), yet Arabic remains underserved,…