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ReasonCLIP-58M: Visually Grounded Commonsense Reasoning Supervision for CLIP
Sicheng Zhang, Muzammal Naseer, Binzhu Xie +5
CLIP and its variants are widely adopted visual backbones in multimodal systems, but their pretraining remains dominated by descriptive image-text alignment. As downstream applicat…
TIGeR: A Unified Framework for Time, Images and Geo-location Retrieval
David G. Shatwell, Sirnam Swetha, Mubarak Shah
Many real-world applications in digital forensics, urban monitoring, and environmental analysis require jointly reasoning about visual appearance, location, and time. Beyond standa…
StretchySnake: Flexible SSM Training Unlocks Action Recognition Across Spatio-Temporal Scales
Nyle Siddiqui, Rohit Gupta, Sirnam Swetha +1
State space models (SSMs) have emerged as a competitive alternative to transformers in various tasks. Their linear complexity and hidden-state recurrence make them particularly att…
Safe-LLaVA: A Privacy-Preserving Vision-Language Dataset and Benchmark for Biometric Safety
Younggun Kim, Sirnam Swetha, Fazil Kagdi +1
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in vision-language tasks. However, these models often infer and reveal sensitive biometric attrib…
Cross-View Open-Vocabulary Object Detection in Aerial Imagery
Jyoti Kini, Rohit Gupta, Mubarak Shah
Traditional object detection models are typically trained on a fixed set of classes, limiting their flexibility and making it costly to incorporate new categories. Open-vocabulary…
The Telephone Game: Evaluating Semantic Drift in Unified Models
Sabbir Mollah, Rohit Gupta, Sirnam Swetha +3
Unified models (UMs) combine visual understanding (I2T) and generation (T2I) in a single framework. We focus on T2I and I2T, where cross-consistency---what a model understands, it…