Inpainting and Outpainting Quiz

Answers and explanations appear as you take the quiz.

1. What does inpainting do?
   • Regenerates a masked region inside an image
   • Extends an image beyond its borders
   • Converts text to speech
   • Compresses image files
2. What does outpainting do?
   • Removes color from photos
   • Generates new content beyond the original edges
   • Detects faces
   • Sharpens blurry pixels
3. How does RePaint use the known region during diffusion-based inpainting?
   • It permanently freezes every unmasked pixel with no resampling
   • It removes the mask before denoising
   • It repeatedly resamples and conditions generation on known pixels during reverse diffusion
   • It trains a new model from scratch for each image
4. What architecture does LaMa introduce for large-mask image inpainting?
   • A language-only transformer
   • A nearest-neighbor search over captions
   • A fixed-color fill with no learned model
   • Fast Fourier Convolutions with a receptive field that supports image-wide context
5. What guides the content that appears in a masked region?
   • A text prompt and the surrounding pixels
   • Only the file name
   • The device's clock
   • The image's compression level
6. Why is outpainting useful for reframing?
   • It deletes the subject
   • It can change a photo's aspect ratio by adding scenery
   • It encrypts the image
   • It reduces resolution
7. Besides Fourier Convolutions, what two components does the LaMa paper identify in its large-mask inpainting method?
   • A speech decoder and image captioner
   • A fixed image palette and nearest-neighbor lookup
   • A high receptive-field perceptual loss and large training masks
   • A video tracker and optical-flow classifier
8. What does a mask specify in an inpainting task?
   • The image’s camera model
   • The order of training examples
   • The output file’s copyright status
   • Which image region is to be modified or synthesized