5 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…
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…
Infinite-Resolution Integral Noise Warping for Diffusion Models
Yitong Deng, Winnie Lin, Lingxiao Li +5
Adapting pretrained image-based diffusion models to generate temporally consistent videos has become an impactful generative modeling research direction. Training-free noise-space…