collaborators

5 papers

cs.CV2025

Deep Learning for Sports Video Event Detection: Tasks, Datasets, Methods, and Challenges

Hao Xu, Arbind Agrahari Baniya, Sam Well +3

Video event detection has become a cornerstone of modern sports analytics, powering automated performance evaluation, content generation, and tactical decision-making. Recent advan…

cs.CV2025

TOTNet: Occlusion-Aware Temporal Tracking for Robust Ball Detection in Sports Videos

Hao Xu, Arbind Agrahari Baniya, Sam Wells +3

Robust ball tracking under occlusion remains a key challenge in sports video analysis, affecting tasks like event detection and officiating. We present TOTNet, a Temporal Occlusion…

cs.CV2025

Hyperspectral Anomaly Detection Methods: A Survey and Comparative Study

Aayushma Pant, Arbind Agrahari Baniya, Tsz-Kwan Lee +1

Hyperspectral images are high-dimensional datasets comprising hundreds of contiguous spectral bands, enabling detailed analysis of materials and surfaces. Hyperspectral anomaly det…

cs.MM2025

Omnidirectional Video Super-Resolution using Deep Learning

Arbind Agrahari Baniya, Tsz-Kwan Lee, Peter W. Eklund +1

Omnidirectional Videos (or 360° videos) are widely used in Virtual Reality (VR) to facilitate immersive and interactive viewing experiences. However, the limited spatial resolutio…

eess.IV2025

A Survey of Deep Learning Video Super-Resolution

Arbind Agrahari Baniya, Tsz-Kwan Lee, Peter Eklund +1

Video super-resolution (VSR) is a prominent research topic in low-level computer vision, where deep learning technologies have played a significant role. The rapid progress in deep…