Guide-yakabatana mibvunzo · Pakati Nhanho

Optical Flow Quiz

Test optical-flow vectors, brightness constancy, RAFT, occlusion, motion limits, and task-specific validation. Check evidence and limits.

Nzira dzekutungamira dzinoenderanaOptical Flow
Mubvunzo 1 ye 8

Chii chinonzi optical flow inofungidzira?

Tarisa mubvunzo wese8 mibvunzo

Mhinduro uye tsananguro zvinoonekwa paunenge uchitora bvunzo.

  1. Chii chinonzi optical flow inofungidzira?
    • Iko kufamba kuri pachena kwemapikseli pakati pemafuremu akateedzana
    • Kupisa kwemavara ega ega furemu
    • Huwandu hwezvinhu zviri mumufananidzo mumwe
    • Iyo audio waveform inoperekedza vhidhiyo
  2. Chii chinonzi 'brightness constancy' fungidziro inoshandiswa muclassic optical flow?
    • Furemu yega yega inofanirwa kuve nekupenya kweavhareji yakafanana
    • Nzvimbo inofamba inochengeta kupenya kwakafanana pamafuremu
    • Kupenya kunofanira kuwedzera zvishoma nezvishoma pamusoro pevhidhiyo
    • Vhidhiyo yakasviba-uye-chena chete inogona kuongororwa
  3. Which method uses a 4D correlation volume and recurrent updates for optical flow?
    • Tesseract
    • Mask R-CNN
    • RAFT
    • Swin patch merging
  4. Why can classic optical-flow assumptions fail in fast motion?
    • Because frames contain no pixels
    • Because flow is a text-only task
    • Because all motion is uniform
    • Large displacement, occlusion, or brightness changes violate local smoothness or brightness-constancy assumptions
  5. Ndeipi application inotsamira zvakananga pakufungidzira mafambiro pakati pemafuremu?
    • Vhidhiyo furemu kududzira kune yakatsetseka inononoka kufamba
    • Chiperengo-kutarisa chinyorwa chinyorwa
    • Kuronga mafoto nehukuru hwefaira
    • Kushandura kutaura kuve mavara
  6. Chii chinonzi 'occlusion' dambudziko mukuyerera kwemaziso?
    • Kana vhidhiyo yanyanya kupenya
    • Kana pixel yakavanzwa kana kuratidzwa, saka hapana mutambo uripo pakati pemafuremu
    • Kana iyo furemu chiyero chiri chaizvo makumi matatu fps
    • Kana mavhidhiyo maviri abatanidzwa pamwechete
  7. What is the output of dense optical flow?
    • One class label for the whole clip
    • A 3D mesh with metric scale
    • A displacement vector estimate for each image pixel
    • A transcript of the audio
  8. What is one reason flow can be uncertain in a textureless region?
    • Every pixel is assigned a unique object name
    • The region has too many labels
    • Optical flow only works on text
    • There may be too little local visual information to identify a unique match