19 citations · 38 across the 13 of their papers we have counts for
14 papers
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…