19 citations · 38 across the 13 of their papers we have counts for
11 papers · 1 filter
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…
ALFred: An Active Learning Framework for Real-world Semi-supervised Anomaly Detection with Adaptive Thresholds
Shanle Yao, Ghazal Alinezhad Noghre, Armin Danesh Pazho +1
Video Anomaly Detection (VAD) can play a key role in spotting unusual activities in video footage. VAD is difficult to use in real-world settings due to the dynamic nature of human…
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.…
MoFM: A Large-Scale Human Motion Foundation Model
Mohammadreza Baharani, Ghazal Alinezhad Noghre, Armin Danesh Pazho +2
Foundation Models (FM) have increasingly drawn the attention of researchers due to their scalability and generalization across diverse tasks. Inspired by the success of FMs and the…
Human-Centric Video Anomaly Detection Through Spatio-Temporal Pose Tokenization and Transformer
Ghazal Alinezhad Noghre, Armin Danesh Pazho, Hamed Tabkhi
Video Anomaly Detection (VAD) presents a significant challenge in computer vision, particularly due to the unpredictable and infrequent nature of anomalous events, coupled with the…
Real-World Community-in-the-Loop Smart Video Surveillance -- A Case Study at a Community College
Shanle Yao, Babak Rahimi Ardabili, Armin Danesh Pazho +3
Smart Video surveillance systems have become important recently for ensuring public safety and security, especially in smart cities. However, applying real-time artificial intellig…
A POV-based Highway Vehicle Trajectory Dataset and Prediction Architecture
Vinit Katariya, Ghazal Alinezhad Noghre, Armin Danesh Pazho +1
Vehicle Trajectory datasets that provide multiple point-of-views (POVs) can be valuable for various traffic safety and management applications. Despite the abundance of trajectory…
Understanding the Challenges and Opportunities of Pose-based Anomaly Detection
Ghazal Alinezhad Noghre, Armin Danesh Pazho, Vinit Katariya +1
Pose-based anomaly detection is a video-analysis technique for detecting anomalous events or behaviors by examining human pose extracted from the video frames. Utilizing pose data…
Ancilia: Scalable Intelligent Video Surveillance for the Artificial Intelligence of Things
Armin Danesh Pazho, Christopher Neff, Ghazal Alinezhad Noghre +4
With the advancement of vision-based artificial intelligence, the proliferation of the Internet of Things connected cameras, and the increasing societal need for rapid and equitabl…
CHAD: Charlotte Anomaly Dataset
Armin Danesh Pazho, Ghazal Alinezhad Noghre, Babak Rahimi Ardabili +2
In recent years, we have seen a significant interest in data-driven deep learning approaches for video anomaly detection, where an algorithm must determine if specific frames of a…
ADG-Pose: Automated Dataset Generation for Real-World Human Pose Estimation
Ghazal Alinezhad Noghre, Armin Danesh Pazho, Justin Sanchez +3
Recent advancements in computer vision have seen a rise in the prominence of applications using neural networks to understand human poses. However, while accuracy has been steadily…