LaMa Resolution-Quiz de peinture bu dëgër

Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.

1. Lan mooy màndarga architecture biy jox LaMa gis-gis bu àdduna bi ci nataal bi?
   • Fourier yu gaaw
   • Transformatër yiy bàyyi seen xel ci seen bopp
   • Layers LSTM yuy dellusi
   • Reseau kapsul
2. Lan moo tax LaMa gëna mëna jëfandikoo mask yu rëy yi yeneen model yu njëkk ya?
   • ci nataal yu ndaw rek lay dox
   • Barab bimuy jot ci àdduna bi daf koy may mu wéyal liggéeyam ci pax yu rëy yi
   • Dafay kopie pixel yi ci pegg yi
   • Dafa baña feesal mask yu ëpp dayo buñ tëral
3. What resolution behavior did the LaMa paper report?
   • It only works at one exact training resolution
   • It works only below the training resolution
   • It generalized to some resolutions higher than those used during training in the evaluated settings
   • It accepts no image input
4. Ban xeetu textures la LaMa mëna jëfandikoo bu baax ndax liggéeyam ci domaine fréquence?
   • bruit aleatoire
   • Kulòor yu dëgër kese
   • Arafu bind yi kese
   • Texture yuy baamtu, yu melni brik wala carreaux
5. Compared with large diffusion-based inpainting systems, how is LaMa commonly positioned?
   • As a comparatively efficient convolutional inpainting method
   • As a much slower model that requires a data center
   • As a video-only model
   • As a tool that never needs an image
6. Ban perte mooy jàppale LaMa mu defar ay fees yu nuru dëgg, du ay moyenne yu fësul?
   • Pixel bu yomb moyen-carré-erreur kese
   • Perte adversarial boole ci perceptuel
   • Amul benn fonction buy ñàkk
   • Perte buy natt dayo fichier bi kese
7. What additional loss component does the LaMa paper emphasize for large-mask inpainting?
   • Ñàkka mëna xàmmee kàddu
   • A bitrate-only loss
   • A perceptual loss with a high receptive field
   • A loss that ignores image structure
8. Who introduced LaMa in the 2021 paper?
   • Jonathan Frankle and Michael Carbin
   • Cees Taal and colleagues
   • Timothy Dozat and Christopher Manning
   • Roman Suvorov and colleagues