Temporal Consistency and Flicker in AI Video Quiz

Answers and explanations appear as you take the quiz.

1. Why does running an image model separately on each frame of a video tend to produce flicker?
   • The video's frame rate is too low for the model
   • Each frame starts from its own random noise and makes independent detail choices
   • Image models cannot process color information
   • The model removes motion blur from every frame
2. What is the main reason modern video generators are steadier than frame-by-frame image pipelines?
   • They generate frames jointly and use attention across time
   • They only generate black-and-white footage
   • They render at lower resolution
   • They always apply a deflicker filter afterward
3. Which kind of content is typically hardest to keep stable from frame to frame?
   • Large flat walls
   • A plain sky with no clouds
   • Fine high-frequency detail such as hair, foliage and text
   • A static solid-color background
4. What can a deflicker filter in post-production realistically fix?
   • A character's face gradually changing shape
   • An object that disappears behind a tree and returns different
   • Brightness pulsing between frames
   • A shirt that changes from three buttons to four
5. Why can identity drift over long videos made by extending shorter clips?
   • The model sees only a limited window of recent frames
   • Longer videos always use a lower frame rate
   • Extensions switch the video to a different color space
   • Audio tracks interfere with the image model
6. What is a known weakness of factorized attention (spatial attention plus temporal attention at the same location)?
   • It cannot produce color
   • It is far more expensive than full 3D attention
   • It struggles with large motion because a given position holds different content across frames
   • It prevents the model from using text prompts
7. In training-free editing pipelines, what does flow-guided latent warping do?
   • Deletes frames that differ too much from the first
   • Moves the previous frame's latent along optical flow before denoising the next frame
   • Increases the random noise in each frame
   • Converts the video to a lower resolution
8. Which statement about flicker is a misconception according to the guide?
   • Occlusion can cause objects to come back looking different
   • Raising resolution will fix flicker on its own
   • Reference-image conditioning can help keep identity stable
   • Autoencoder compression can add artifacts where chunks join