Qingming LIU — accepted AI-conference papers

2025

MoDGS: Dynamic Gaussian Splatting from Casually-captured Monocular Videos with Depth Priors

Qingming LIU, Yuan Liu, Jiepeng Wang, Xianqiang Lyu, Peng Wang, Wenping Wang +1

ICLR 2025poster

In this paper, we propose MoDGS, a new pipeline to render novel-view images in dynamic scenes using only casually captured monocular videos. Previous monocular dynamic NeRF or Gaussian Splatting methods strongly rely on the rapid movement of input cameras to construct multiview consistency but fail…

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2025

Nabla-R2D3: Effective and Efficient 3D Diffusion Alignment with 2D Rewards

Qingming LIU, Zhen Liu, Dinghuai Zhang, Kui Jia

NeurIPS 2025poster

Generating high-quality and photorealistic 3D assets remains a longstanding challenge in 3D vision and computer graphics. Although state-of-the-art generative models, such as diffusion models, have made significant progress in 3D generation, they often fall short of human-designed content due to lim…

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