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LLM-Guided Probabilistic Fusion for Label-Efficient Document Layout Analysis
Ibne Farabi Shihab, Sanjeda Akter, Anuj Sharma
Document layout understanding remains data-intensive despite advances in semi-supervised learning. We present a framework that enhances semi-supervised detection by fusing visual p…
Temporal Zoom Networks: Distance Regression and Continuous Depth for Efficient Action Localization
Ibne Farabi Shihab, Sanjeda Akter, Anuj Sharma
Temporal action localization requires both precise boundary detection and computational efficiency. Current methods apply uniform computation across all temporal positions, wasting…
Calibrated and Resource-Aware Super-Resolution for Reliable Driver Behavior Analysis
Ibne Farabi Shihab, Weiheng Chai, Jiyang Wang +3
Driver monitoring systems require not just high accuracy but reliable, well-calibrated confidence scores for safety-critical deployment. While direct low-resolution training yields…
Enhancing Traffic Incident Response through Sub-Second Temporal Localization with HybridMamba
Ibne Farabi Shihab, Sanjeda Akter, Anuj Sharma
Traffic crash detection in long-form surveillance videos is essential for improving emergency response and infrastructure planning, yet remains difficult due to the brief and infre…
Large Language Models for Crash Detection in Video: A Survey of Methods, Datasets, and Challenges
Sanjeda Akter, Ibne Farabi Shihab, Anuj Sharma
Crash detection from video feeds is a critical problem in intelligent transportation systems. Recent developments in large language models (LLMs) and vision-language models (VLMs)…
Image Segmentation with Large Language Models: A Survey with Perspectives for Intelligent Transportation Systems
Sanjeda Akter, Ibne Farabi Shihab, Anuj Sharma
The integration of Large Language Models (LLMs) with computer vision is profoundly transforming perception tasks like image segmentation. For intelligent transportation systems (IT…