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cs.CV2026

Ask Me Again Differently: GRAS for Measuring Bias in Vision Language Models on Gender, Race, Age, and Skin Tone

Shaivi Malik, Hasnat Md Abdullah, Sriparna Saha +1

As Vision Language Models (VLMs) become integral to real-world applications, understanding their demographic biases is critical. We introduce GRAS, a benchmark for uncovering demog…

cs.CV2025

The Visual Counter Turing Test (VCT2): A Benchmark for Evaluating AI-Generated Image Detection and the Visual AI Index (VAI)

Nasrin Imanpour, Abhilekh Borah, Shashwat Bajpai +12

The rapid progress and widespread availability of text-to-image (T2I) generative models have heightened concerns about the misuse of AI-generated visuals, particularly in the conte…

cs.CV2025

Non-Uniform Spatial Alignment Errors in sUAS Imagery From Wide-Area Disasters

Thomas Manzini, Priyankari Perali, Raisa Karnik +3

This work presents the first quantitative study of alignment errors between small uncrewed aerial systems (sUAS) georectified imagery and a priori building polygons and finds that…

cs.CV2025

DETONATE: A Benchmark for Text-to-Image Alignment and Kernelized Direct Preference Optimization

Renjith Prasad, Abhilekh Borah, Hasnat Md Abdullah +9

Alignment is crucial for text-to-image (T2I) models to ensure that generated images faithfully capture user intent while maintaining safety and fairness. Direct Preference Optimiza…

cs.CV2024

UAL-Bench: The First Comprehensive Unusual Activity Localization Benchmark

Hasnat Md Abdullah, Tian Liu, Kangda Wei +2

Localizing unusual activities, such as human errors or surveillance incidents, in videos holds practical significance. However, current video understanding models struggle with loc…

cs.CV2024

SynthEnsemble: A Fusion of CNN, Vision Transformer, and Hybrid Models for Multi-Label Chest X-Ray Classification

S. M. Nabil Ashraf, Md. Adyelullahil Mamun, Hasnat Md. Abdullah +1

Chest X-rays are widely used to diagnose thoracic diseases, but the lack of detailed information about these abnormalities makes it challenging to develop accurate automated diagno…