Jaehun Bang — accepted AI-conference papers

2026

LightSplat: Fast and Memory-Efficient Open-Vocabulary 3D Scene Understanding in Five Seconds

Jaehun Bang, Jinhyeok Kim, Minji Kim, Seungheon Jeong, Kyungdon Joo

CVPR 2026

Open-vocabulary 3D scene understanding enables users to segment novel objects in complex 3D environments through natural language. However, existing approaches remain slow, memory-intensive, and overly complex due to iterative optimization and dense per-Gaussian feature assignments. To address this,

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2026

ORBIT: Optimal Recommendation Framework for Boarding with Interpretable Timelines

Joonseong Kang, Jaehun Bang, Seung Ha Hwang, Jiyoung Ko, Subeen Park, Jeffrey Gennari

IJCAI 2026

Determining when to leave for the airport is a complex problem shaped by flight delay risk, traffic, weather, airport congestion, and passenger-specific constraints. Existing services rely on isolated delay estimates or simple travel time calculations, failing to capture real-time context. We propos

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