141 citations · 145 across the 13 of their papers we have counts for
7 papers · 1 filter
When Gender is Hard to See: Multi-Attribute Support for Long-Range Recognition
Nzakiese Mbongo, Kailash A. Hambarde, Hugo Proença
Accurate gender recognition from extreme long-range imagery remains a challenging problem due to limited spatial resolution, viewpoint variability, and loss of facial cues. For suc…
Seeing Across Time and Views: Multi-Temporal Cross-View Learning for Robust Video Person Re-Identification
Md Rashidunnabi, Kailash A. Hambarde, Vasco Lopes +2
Video-based person re-identification (ReID) in cross-view domains (for example, aerial-ground surveillance) remains an open problem because of extreme viewpoint shifts, scale dispa…
Enhancement of Quantum Semi-Supervised Learning via Improved Laplacian and Poisson Methods
Hamed Gholipour, Farid Bozorgnia, Hamzeh Mohammadigheymasi +5
This paper develops a hybrid quantum approach for graph-based semi-supervised learning to enhance performance in scenarios where labeled data is scarce. We introduce two enhanced q…
AG-VPReID 2025: Aerial-Ground Video-based Person Re-identification Challenge Results
Kien Nguyen, Clinton Fookes, Sridha Sridharan +20
Person re-identification (ReID) across aerial and ground vantage points has become crucial for large-scale surveillance and public safety applications. Although significant progres…
Causality and "In-the-Wild" Video-Based Person Re-ID: A Survey
Md Rashidunnabi, Kailash Hambarde, Hugo Proença
Video-based person re-identification (Re-ID) remains brittle in real-world deployments despite impressive benchmark performance. Most existing models rely on superficial correlatio…
DetReIDX: A Stress-Test Dataset for Real-World UAV-Based Person Recognition
Kailash A. Hambarde, Nzakiese Mbongo, Pavan Kumar MP +8
Person reidentification (ReID) technology has been considered to perform relatively well under controlled, ground-level conditions, but it breaks down when deployed in challenging…
Human Re-ID Meets LVLMs: What can we expect?
Kailash Hambarde, Pranita Samale, Hugo Proença
Large vision-language models (LVLMs) have been regarded as a breakthrough advance in an astoundingly variety of tasks, from content generation to virtual assistants and multimodal…