6 papers
Detail Enhanced Gaussian Splatting for Large-Scale Volumetric Capture
Julien Philip, Li Ma, Pascal Clausen +8
We present a unique system for large-scale, multi-performer, high resolution 4D volumetric capture providing realistic free-viewpoint video up to and including 4K resolution facial…
Virtually Being: Customizing Camera-Controllable Video Diffusion Models with Multi-View Performance Captures
Yuancheng Xu, Wenqi Xian, Li Ma +10
We introduce a framework that enables both multi-view character consistency and 3D camera control in video diffusion models through a novel customization data pipeline. We train th…
FreSca: Scaling in Frequency Space Enhances Diffusion Models
Chao Huang, Susan Liang, Yunlong Tang +4
Latent diffusion models (LDMs) have achieved remarkable success in a variety of image tasks, yet achieving fine-grained, disentangled control over global structures versus fine det…
Lux Post Facto: Learning Portrait Performance Relighting with Conditional Video Diffusion and a Hybrid Dataset
Yiqun Mei, Mingming He, Li Ma +9
Video portrait relighting remains challenging because the results need to be both photorealistic and temporally stable. This typically requires a strong model design that can captu…
Go-with-the-Flow: Motion-Controllable Video Diffusion Models Using Real-Time Warped Noise
Ryan Burgert, Yuancheng Xu, Wenqi Xian +10
Generative modeling aims to transform random noise into structured outputs. In this work, we enhance video diffusion models by allowing motion control via structured latent noise s…
Fitting Spherical Gaussians to Dynamic HDRI Sequences
Pascal Clausen, Li Ma, Mingming He +3
We present a technique for fitting high dynamic range illumination (HDRI) sequences using anisotropic spherical Gaussians (ASGs) while preserving temporal consistency in the compre…