Liu Yue — accepted AI-conference papers

2025

Intend to Move: A Multimodal Dataset for Intention-Aware Human Motion Understanding

Ryo Umagami, Liu Yue, Xuangeng Chu, Ryuto Fukushima, Tetsuya Narita, Yusuke Mukuta +3

NeurIPS 2025poster

Human motion is inherently intentional, yet most motion modeling paradigms focus on low-level kinematics, overlooking the semantic and causal factors that drive behavior. Existing datasets further limit progress: they capture short, decontextualized actions in static scenes, providing little groundi…

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2024

ControlCap: Controllable Region-level Captioning

Yuzhong Zhao, Liu Yue, Zonghao Guo, weijia wu, Chen Gong, Qixiang Ye +1

ECCV 2024poster

"Region-level captioning is challenged by the caption degeneration issue, which refers to that pre-trained multimodal models tend to predict the most frequent captions but miss the less frequent ones. In this study, we propose a controllable region-level captioning (ControlCap) approach, which intro…

Cited by 7 Source ↗PDF ↗code ↗Scholar ↗