A team from Zhejiang University and vivo has introduced FlashRelight, an AI system that can relight portrait videos. It's more than just applying a filter. The goal is to change the lighting while preserving a person's identity, expression, and motion. FlashRelight takes a two-stage approach: First, a delighting model suppresses the original lighting and shadows. Then, a relighting model generates new dynamic lighting across the video. You can control the lighting in three ways: • Envmap sequences: Precise frame-level lighting control. • Text prompts: Describe color, direction, movement, and flicker. • Reference videos: Transfer lighting effects from another video. The team built a hybrid dataset with 34k+ paired videos: • ~24K synthesized from static OLAT lighting data • 10k+ generated by Wan2.2 This gives the model varied lighting and motion without costly dynamic light-stage capture. On envmap-based relighting, FlashRelight outperformed all baselines across all five evaluation metric For short videos, ads, or virtual-human content, this could make it easier to adjust a portrait’s lighting in post-production.