We design a self-supervised method that takes advantage of the consistency of videos and variability of multiview internet photos to train a 3D-aware video model without ANY 3D annotations. We name our method KFC-W (KeyFrame-Conditioned video generation in-the-Wild). 4/N

This task is difficult for video models! They perform visually pleasing morphing but can ignore scene identity and hallucinate new structures. Our main insight is that training for general video synthesis is not enough: we need to introduce scalable, 3D-aware objectives. 3/N

We've released our paper "Generating 3D-Consistent Videos from Unposed Internet Photos"! Video models like Luma generate pretty videos, but sometimes struggle with 3D consistency. We can do better by scaling them with 3D-aware objectives. 1/N

page: genechou.com/kfcw