Long-Nhat Ho — accepted AI-conference papers

2024

VOODOO 3D: Volumetric Portrait Disentanglement For One-Shot 3D Head Reenactment

Phong Tran, Egor Zakharov, Long-Nhat Ho, Anh Tuan Tran, Liwen Hu, Hao Li

CVPR 2024poster

We present a 3D-aware one-shot head reenactment method based on a fully volumetric neural disentanglement framework for source appearance and driver expressions. Our method is real-time and produces high-fidelity and view-consistent output suitable for 3D teleconferencing systems based on holographi…

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2021

Toward Realistic Single-View 3D Object Reconstruction With Unsupervised Learning From Multiple Images

Long-Nhat Ho, Anh Tuan Tran, Quynh Phung, Minh Hoai

ICCV 2021poster

Recovering the 3D structure of an object from a single image is a challenging task due to its ill-posed nature. One approach is to utilize the plentiful photos of the same object category to learn a strong 3D shape prior for the object. This approach has successfully been demonstrated by a recent wo…

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