Yeseung Park — accepted AI-conference papers

2025

MBTI: Masked Blending Transformers with Implicit Positional Encoding for Frame-rate Agnostic Motion Estimation

Jungwoo Huh, Yeseung Park, Seongjean Kim, Jungsu Kim, Sanghoon Lee

ICCV 2025poster

Human motion estimation models typically assume a fixed number of input frames, making them sensitive to variations in frame rate and leading to inconsistent motion predictions across different temporal resolutions. This limitation arises because input frame rates inherently determine the temporal g…

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2025

SDAS: Semantic Data Acquisition System for Minimizing Redundancy and Maximizing Diversity

Yeseung Park, Hyunse Yoon, Jungwoo Huh, Jungsu Kim, Jeongwook Choi, Sanghoon Lee

AAAI 2025technical

In this paper, we propose SDAS, a new motion data assessment and storage system designed to acquire new motion data with reduced redundancy and maximizing diversity. SDAS collects data in the field, retrieves the most similar data from the database in real-time, and provides visualization tools that…

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