collaborators

7 papers

cs.CV2026

Go-with-the-Track: Video Compositing and Motion Control with Point Tracking

Koichi Namekata, Yash Kant, Zhizheng Liu +9

Filmmaking demands precise motion control and reference image compositing -- capabilities that existing methods treat separately. Point-track-conditioned image-to-video models rest…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.GR2025

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…

cs.CV2025

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…

cs.GR2025

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…