Kedis ku xidhan hagaha · Adag Heerka

Sawirka Sawirka Kediska Sawirka Keliya

Waxay tijaabisaa wareejinta dhaqdhaqaaqa dhibcaha ku salaysan, maaraynta xidhidhka, SadTalker iyo LivePortrait nashqadeynta xulashada weji hal sawir.

Wadooyinka haga ee la xidhiidhaSawirka Sawirka Hal sawir
Su'aal 1 ee 8

How does the First Order Motion Model obtain its keypoints?

Horudhac su'aal kasta8 su'aalo

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

  1. How does the First Order Motion Model obtain its keypoints?
    • From manually labeled facial landmarks
    • From a 3D scan of the person
    • It learns them without labels during training
    • From the audio track
  2. What is the purpose of the occlusion map?
    • To mark regions the source image cannot supply, so they must be painted in
    • To blur the background on purpose
    • To detect the speaker's language
    • To choose the output frame rate
  3. What is the benefit of relative motion transfer?
    • It doubles the frame rate
    • The source keeps its own face shape instead of taking on the driver's
    • It removes the need for a driving video
    • It makes the head turn farther
  4. What does SadTalker predict from the audio?
    • Raw pixel values of the mouth
    • A new background
    • Qoraal qoraal ah
    • 3D Morphable Model coefficients for expression and head pose
  5. What does LivePortrait's stitching module do?
    • It pastes the animated face back into the full image without misaligned shoulders
    • It merges two different people's faces
    • It stitches audio clips together
    • It converts video to GIF
  6. Why do large head turns usually fail in single-photo animation?
    • The GPU runs out of memory
    • Head turns are disabled by default
    • The photo has no information about unseen regions like the side of the head
    • Audio cannot describe rotation
  7. Why do keypoint methods warp feature maps rather than raw pixels?
    • Pixels cannot be moved
    • It lets the decoder repair stretching and fill unseen regions
    • Feature maps are always higher resolution
    • It removes the need for keypoints
  8. In implicit 3D keypoint methods, what does the driving frame contribute?
    • The canonical keypoints encoding identity
    • The background texture
    • The skin color
    • Head rotation, translation and expression deformations