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cs.CV2025

DeMoGen: Towards Decompositional Human Motion Generation with Energy-Based Diffusion Models

Jianrong Zhang, Hehe Fan, Yi Yang

Human motions are compositional: complex behaviors can be described as combinations of simpler primitives. However, existing approaches primarily focus on forward modeling, e.g., l…

cs.RO2025

Endowing GPT-4 with a Humanoid Body: Building the Bridge Between Off-the-Shelf VLMs and the Physical World

Yingzhao Jian, Zhongan Wang, Yi Yang +1

Humanoid agents often struggle to handle flexible and diverse interactions in open environments. A common solution is to collect massive datasets to train a highly capable model, b…

cs.LG2025

Translution: Unifying Self-attention and Convolution for Adaptive and Relative Modeling

Hehe Fan, Yi Yang, Mohan Kankanhalli +1

When modeling a given type of data, we consider it to involve two key aspects: 1) identifying relevant elements (e.g., image pixels or textual words) to a central element, as in a…

cs.CV2025

TSGS: Improving Gaussian Splatting for Transparent Surface Reconstruction via Normal and De-lighting Priors

Mingwei Li, Pu Pang, Hehe Fan +2

Reconstructing transparent surfaces is essential for tasks such as robotic manipulation in labs, yet it poses a significant challenge for 3D reconstruction techniques like 3D Gauss…

cs.CV2025

EnergyMoGen: Compositional Human Motion Generation with Energy-Based Diffusion Model in Latent Space

Jianrong Zhang, Hehe Fan, Yi Yang

Diffusion models, particularly latent diffusion models, have demonstrated remarkable success in text-driven human motion generation. However, it remains challenging for latent diff…