6 papers
Instruct-Particulate: Scaling Feed-Forward 3D Object Articulation with Kinematic Control
Ruining Li, Yuxin Yao, Matt Zhou +5
Reconstructing articulated 3D objects is important for animation, gaming, and robotic simulations. Recent neural networks can estimate the articulated structure of 3D objects, but…
Particulate: Feed-Forward 3D Object Articulation
Ruining Li, Yuxin Yao, Chuanxia Zheng +4
We introduce Particulate, a feed-forward model that, given a 3D mesh of an object, infers its articulations, including its 3D parts, their kinematic structure, and the motion const…
LiteReality: Graphics-Ready 3D Scene Reconstruction from RGB-D Scans
Zhening Huang, Xiaoyang Wu, Fangcheng Zhong +3
We propose LiteReality, a novel pipeline that converts RGB-D scans of indoor environments into compact, realistic, and interactive 3D virtual replicas. LiteReality not only reconst…
Efficient Camera-Controlled Video Generation of Static Scenes via Sparse Diffusion and 3D Rendering
Jieying Chen, Jeffrey Hu, Joan Lasenby +1
Modern video generative models based on diffusion models can produce very realistic clips, but they are computationally inefficient, often requiring minutes of GPU time for just a…
SpaceTimePilot: Generative Rendering of Dynamic Scenes Across Space and Time
Zhening Huang, Hyeonho Jeong, Xuelin Chen +4
We present SpaceTimePilot, a video diffusion model that disentangles space and time for controllable generative rendering. Given a monocular video, SpaceTimePilot can independently…
SmallGS: Gaussian Splatting-based Camera Pose Estimation for Small-Baseline Videos
Yuxin Yao, Yan Zhang, Zhening Huang +1
Dynamic videos with small baseline motions are ubiquitous in daily life, especially on social media. However, these videos present a challenge to existing pose estimation framework…