4 papers
EVA: Aligning Video World Models with Executable Robot Actions via Inverse Dynamics Rewards
Ruixiang Wang, Qingming Liu, Yueci Deng +3
Video generative models are increasingly used as world models for robotics, where a model generates a future visual rollout conditioned on the current observation and task instruct…
PAct: Part-Decomposed Single-View Articulated Object Generation
Qingming Liu, Xinyue Yao, Shuyuan Zhang +4
Articulated objects are central to interactive 3D applications, including embodied AI, robotics, and VR/AR, where functional part decomposition and kinematic motion are essential.…
Nabla-R2D3: Effective and Efficient 3D Diffusion Alignment with 2D Rewards
Qingming Liu, Zhen Liu, Dinghuai Zhang +1
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 diffu…
MoDGS: Dynamic Gaussian Splatting from Casually-captured Monocular Videos with Depth Priors
Qingming Liu, Yuan Liu, Jiepeng Wang +4
In this paper, we propose MoDGS, a new pipeline to render novel views of dy namic scenes from a casually captured monocular video. Previous monocular dynamic NeRF or Gaussian Splat…