The FlashPortrait team realized that current AI models are too slow and often fail to keep a person’s face consistent in long videos—the face eventually starts to look like someone else. Their solution was a new method that locks the subject's identity in place while generating the video.
They introduced a specific "normalization block" that aligns facial features with the video generation process, ensuring the face never distorts or morphs. To handle infinite-length animations smoothly, they used a sliding window method that gently blends overlapping frames.
Crucially, they found a way to speed things up significantly. By using "adaptive latent prediction," the model anticipates future steps rather than calculating every single one, making the process six times faster than existing methods. In short, they built a model that creates long, high-quality portrait animations instantly and accurately, solving the "identity drift" problem without needing any extra editing tools.
They introduced a specific "normalization block" that aligns facial features with the video generation process, ensuring the face never distorts or morphs. To handle infinite-length animations smoothly, they used a sliding window method that gently blends overlapping frames.
Crucially, they found a way to speed things up significantly. By using "adaptive latent prediction," the model anticipates future steps rather than calculating every single one, making the process six times faster than existing methods. In short, they built a model that creates long, high-quality portrait animations instantly and accurately, solving the "identity drift" problem without needing any extra editing tools.