08 / Video prediction
Video Net
Frame prediction and the error that builds during rollout.
Method overview · footage under review
Explore this projectVideo Net takes a short stack of frames, estimates motion with a flow-and-residual network, then feeds its own predictions back into the next step.
The study follows what happens when a one-step prediction becomes input for another. Small errors in motion and detail can accumulate across a rollout.
Experiment boundary
What the comparison will show
A frame comparison will follow when the research footage is cleared for this page.
Reading a rollout
Observe
The model receives a short stack of source frames and predicts motion plus residual detail.
Predict
Its output becomes an input at the next step, so errors can accumulate across time.
Media
The local study has saved rollouts. The source footage is being checked before any clip is placed on this public page.