Minh Hoai

Papers

Total Citations

361

H-Index

About

Minh Hoai is a leading researcher in computer vision and machine learning, best known for pioneering work in early event detection from temporal data. His seminal contributions, particularly through the highly cited "Max-Margin Early Event Detectors" (2013, 223 citations) and its predecessor (2012, 138 citations), address a critical gap in video analysis: the ability to recognize ongoing events before they fully unfold. By formulating early detection as a structured prediction problem with a novel max-margin framework, Hoai enabled systems to make reliable predictions from partial observations—a breakthrough with profound implications for human-robot interaction, surveillance, and autonomous driving. His work has garnered over 360 citations across these key papers alone, reflecting its foundational impact on the field. Beyond early detection, Hoai's research spans activity recognition, object tracking, and robust visual learning, consistently pushing the boundaries of real-time intelligent systems. His innovative approach to temporal reasoning has made him a sought-after figure in both academia and industry, inspiring a new generation of researchers to tackle the challenge of proactive, anticipatory computer vision.