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20232026
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cs.CV2026

Ego-Human Motion Prediction with 3D-Aware LLM

Yujin Bae, Jaewoo Jeong, Hyeonseong Kim +1

Anticipating human motion from an egocentric perspective is fundamental for proactive assistance in AR/VR, human-robot collaboration, and embodied AI. While recent works incorporat…

cs.CV2025

Multi-modal Knowledge Distillation-based Human Trajectory Forecasting

Jaewoo Jeong, Seohee Lee, Daehee Park +2

Pedestrian trajectory forecasting is crucial in various applications such as autonomous driving and mobile robot navigation. In such applications, camera-based perception enables t…

cs.CV2024

Multi-agent Long-term 3D Human Pose Forecasting via Interaction-aware Trajectory Conditioning

Jaewoo Jeong, Daehee Park, Kuk-Jin Yoon

Human pose forecasting garners attention for its diverse applications. However, challenges in modeling the multi-modal nature of human motion and intricate interactions among agent…

cs.CV2024

T4P: Test-Time Training of Trajectory Prediction via Masked Autoencoder and Actor-specific Token Memory

Daehee Park, Jaeseok Jeong, Sung-Hoon Yoon +2

Trajectory prediction is a challenging problem that requires considering interactions among multiple actors and the surrounding environment. While data-driven approaches have been…

cs.CV2023

Improving Transferability for Cross-domain Trajectory Prediction via Neural Stochastic Differential Equation

Daehee Park, Jaewoo Jeong, Kuk-Jin Yoon

Multi-agent trajectory prediction is crucial for various practical applications, spurring the construction of many large-scale trajectory datasets, including vehicles and pedestria…