Guide-linked quiz · Hard Level
Camera Control in AI Video Generation Quiz
Checks zoom versus dolly, Plücker camera embeddings, why camera data is scarce, and how trajectory accuracy in AI video is measured.
Question 1 of 8
What visually separates a dolly from a zoom?
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Answers and explanations appear as you take the quiz.
- What visually separates a dolly from a zoom?
- A zoom always moves left to right
- A dolly moves the camera and creates parallax, while a zoom changes focal length without parallax
- A dolly changes focal length only
- They are identical
- What does a Plücker embedding encode for each pixel?
- Its color value
- Its depth in meters
- The object label at that pixel
- The viewing ray from the camera pose, as (o × d, d)
- Why is precise camera control hard to learn from typical training videos?
- Most videos have no camera labels, and captions rarely describe camera motion accurately
- Videos are always filmed on tripods
- Camera motion cannot be seen in video
- Training videos have no frames
- What is a limitation of pose-annotated datasets like RealEstate10K?
- They contain no camera poses
- They are audio-only
- They are narrow in domain and mostly show static scenes
- They only include animated films
- How can you measure whether a generated video followed the requested camera path?
- Count the number of frames
- Run structure-from-motion on the output and compare the recovered path using rotation and translation errors
- Check the file size
- Ask the model to describe its camera
- What does scale ambiguity mean for camera control?
- Videos cannot be resized
- Zooming always fails
- Pixels have no color scale
- Monocular video has no absolute scale, so distances like 'two meters' are undefined without normalization
- How does CameraCtrl add camera conditioning to a video model?
- It trains an adapter on pose-annotated clips while the base model stays frozen
- It retrains the entire model from scratch
- It edits frames after generation
- It uses text prompts only
- Which prompting practice gives more reliable camera moves in prompt-based tools?
- Request several moves at once
- Describe only the subject
- Ask for one move per shot, state its speed, and keep subject motion simple
- Avoid all camera words
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