1 citations · 3 across the 45 of their papers we have counts for
12 papers · 1 filter
Rethinking Classifier-Free Guidance for TI2I Flow Matching
Andreas Floros, Elena Koritska, Teofilo de Campos +4
We study Text-and-Image-to-Image (TI2I) flow matching methods for controllable image editing. In a broader generative modeling context, Classifier-Free Guidance (CFG) is establishe…
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…
The 9th AI City Challenge
Zheng Tang, Shuo Wang, David C. Anastasiu +25
The ninth AI City Challenge continues to advance real-world applications of computer vision and AI in transportation, industrial automation, and public safety. The 2025 edition fea…
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…
ClearVision: Leveraging CycleGAN and SigLIP-2 for Robust All-Weather Classification in Traffic Camera Imagery
Anush Lakshman Sivaraman, Kojo Adu-Gyamfi, Ibne Farabi Shihab +1
Adverse weather conditions challenge safe transportation, necessitating robust real-time weather detection from traffic camera imagery. We propose a novel framework combining Cycle…
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…
Precise and Robust Sidewalk Detection: Leveraging Ensemble Learning to Surpass LLM Limitations in Urban Environments
Ibne Farabi Shihab, Sudesh Ramesh Bhagat, Anuj Sharma
This study aims to compare the effectiveness of a robust ensemble model with the state-of-the-art ONE-PEACE Large Language Model (LLM) for accurate detection of sidewalks. Accurate…
DeepLocalization: Using change point detection for Temporal Action Localization
Mohammed Shaiqur Rahman, Ibne Farabi Shihab, Lynna Chu +1
In this study, we introduce DeepLocalization, an innovative framework devised for the real-time localization of actions tailored explicitly for monitoring driver behavior. Utilizin…
The 8th AI City Challenge
Shuo Wang, David C. Anastasiu, Zheng Tang +21
The eighth AI City Challenge highlighted the convergence of computer vision and artificial intelligence in areas like retail, warehouse settings, and Intelligent Traffic Systems (I…