Vhidhiyo Diffusion Models Quiz

Mhinduro uye tsananguro zvinoonekwa paunenge uchitora bvunzo.

1. Ndeipi pfungwa yakakosha kumashure kweiyo diffusion modhi?
   • Kudzidza kudzoreredza muitiro uyo zvishoma nezvishoma unowedzera ruzha, denoising nhanho nhanho
   • Kukopa mafuremu kubva kumavhidhiyo aripo
   • Kudzvanya audio mumifananidzo
   • Encrypting data kuitira kuchengetedza
2. For a video diffusion model, what does temporal modeling add to the denoising process?
   • It guarantees every object remains physically correct
   • It lets the model represent dependencies among frames over time
   • It removes the image decoder from the pipeline
   • It turns each video into one text token
3. Why does the cited Stable Video Diffusion model use a latent representation?
   • To avoid using any learned decoder
   • To store all frames as discrete text tokens
   • To perform video diffusion on compressed latents before decoding frames
   • To guarantee there will be no flicker
4. How did the Stable Video Diffusion paper adapt an image diffusion model for video?
   • It replaced every image layer with a speech recognizer
   • It trained only a language model on video captions
   • It removed the image model and used optical flow alone
   • It inserted temporal layers into a pretrained image model and fine-tuned them on video data
5. Ndeipi nzira inobatsira vhidhiyo yekuparadzira modhi kutevera chirevo chemavara zvakasimba?
   • Classifier-yemahara kutungamira
   • Kusarudzika kwemafuremu
   • Kuderedza chisarudzo
   • Kubvisa chirevo zvachose
6. Sei matekiniki akaita se distillation uye anokurumidza solvers ari kuiswa kune vhidhiyo diffusion?
   • Kuita kuti muenzaniso ukanganwe data
   • Nekuti iyo yakawanda-nhanho denoising sampling inononoka uye inoderedza huwandu hwenhanho
   • Kuwedzera imwe ruzha zvachose
   • Kudzima chirevo chemavara
7. In the Stable Video Diffusion paper, what distinguishes the SVD-XT model from the 14-frame SVD model?
   • It replaces diffusion with autoregressive text generation
   • It removes temporal layers and generates only a still image
   • SVD-XT is fine-tuned to generate 25 frames instead of 14
   • It uses audio tokens as the only conditioning input
8. What is one tradeoff when using fewer denoising steps through distillation or a faster solver?
   • Zero compute is required
   • The video no longer needs conditioning
   • Every result becomes temporally perfect
   • Faster generation may change fidelity or motion quality and must be evaluated