16 citations · 16 across the 12 of their papers we have counts for
10 papers · 1 filter
ID-V2V: Identity-Preserving Video Restylization
Yuancheng Xu, Mingming He, Pablo Salamanca +5
In visual storytelling, human performances are central to creative intent and narrative meaning. However, preserving human identity and performance while enabling flexible visual e…
Cinematic Compositing Using Character-Environment-Harmonized Video Generation Models
Tianyi Xiang, Mingming He, Li Ma +1
Cinematic compositing aims to integrate green-screen characters into novel environments while maintaining physical and photometric realism. Previous methods often fail to capture t…
ReAge3D: Re-Aging 3D Faces with View Consistency
Libing Zeng, Li Ma, Mingming He +3
We present a novel framework for realistic and controllable 3D face re-aging which produces highly detailed, identity-preserving results. Existing 3D editing methods, while effecti…
BodyReLux: Temporally Consistent Full-Body Video Relighting
Li Ma, Mingming He, Xueming Yu +4
Being able to relight human performance is a fundamental task for post production and content creation. We present BodyReLux, a subject-specific video diffusion-based framework for…
DiffHDR: Re-Exposing LDR Videos with Video Diffusion Models
Zhengming Yu, Li Ma, Mingming He +11
Most digital videos are stored in 8-bit low dynamic range (LDR) formats, where much of the original high dynamic range (HDR) scene radiance is lost due to saturation and quantizati…
Lighting in Motion: Spatiotemporal HDR Lighting Estimation
Christophe Bolduc, Julien Philip, Li Ma +3
We present Lighting in Motion (LiMo), a diffusion-based approach to spatiotemporal lighting estimation. LiMo targets both realistic high-frequency detail prediction and accurate il…
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…
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…
DifFRelight: Diffusion-Based Facial Performance Relighting
Mingming He, Pascal Clausen, Ahmet Levent Taşel +8
We present a novel framework for free-viewpoint facial performance relighting using diffusion-based image-to-image translation. Leveraging a subject-specific dataset containing div…