collaborators

6 papers

cs.AI2026

Intelligent CCTV for Urban Design: AI-Based Analysis of Soft Infrastructure at Intersections

Vinit Katariya, Seungjin Kim, Curtis Craig +2

Artificial intelligence (AI) and computer vision are transforming transportation data collection. This study introduces an AI-enabled analytics framework leveraging existing CCTV i…

cs.CV2026

EdgeVTP: Exploration of Latency-efficient Trajectory Prediction for Edge-based Embedded Vision Applications

Seungjin Kim, Reza Jafarpourmarzouni, Christopher Neff +2

Vehicle trajectory prediction is central to highway perception, but deployment on roadside edge devices necessitates bounded, deterministic end-to-end latency. We present EdgeVTP,…

eess.SP2025

Distributed learning for automatic modulation recognition in bandwidth-limited networks

Narges Rashvand, Kenneth Witham, Gabriel Maldonado +4

Automatic Modulation Recognition (AMR) is critical in identifying various modulation types in wireless communication systems. Recent advancements in deep learning have facilitated…

cs.CV2025

Adversarially-Refined VQ-GAN with Dense Motion Tokenization for Spatio-Temporal Heatmaps

Gabriel Maldonado, Narges Rashvand, Armin Danesh Pazho +3

Continuous human motion understanding remains a core challenge in computer vision due to its high dimensionality and inherent redundancy. Efficient compression and representation a…

cs.CV2025

MoCLIP: Motion-Aware Fine-Tuning and Distillation of CLIP for Human Motion Generation

Gabriel Maldonado, Armin Danesh Pazho, Ghazal Alinezhad Noghre +2

Human motion generation is essential for fields such as animation, robotics, and virtual reality, requiring models that effectively capture motion dynamics from text descriptions.…

cs.CV2025

Towards Adaptive Human-centric Video Anomaly Detection: A Comprehensive Framework and A New Benchmark

Armin Danesh Pazho, Shanle Yao, Ghazal Alinezhad Noghre +3

Human-centric Video Anomaly Detection (VAD) aims to identify human behaviors that deviate from normal. At its core, human-centric VAD faces substantial challenges, such as the comp…