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cs.CV2026

Generalization Under Scrutiny: Cross-Domain Detection Progresses, Pitfalls, and Persistent Challenges

Saniya M. Deshmukh, Kailash A. Hambarde, Hugo Proença

Object detection models trained on a source domain often exhibit significant performance degradation when deployed in unseen target domains, due to various kinds of variations, suc…

cs.CV2026

Rectifying Geometry-Induced Similarity Distortions for Real-World Aerial-Ground Person Re-Identification

Kailash A. Hambarde, Hugo Proença

Aerial-ground person re-identification (AG-ReID) is fundamentally challenged by extreme viewpoint and distance discrepancies between aerial and ground cameras, which induce severe…

cs.CV2026

VReID-XFD: Video-based Person Re-identification at Extreme Far Distance Challenge Results

Kailash A. Hambarde, Hugo Proença, Md Rashidunnabi +18

Person re-identification (ReID) across aerial and ground views at extreme far distances introduces a distinct operating regime where severe resolution degradation, extreme viewpoin…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…