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Zkouška 2025

1. Deep Learning

  • Visual Transformers, architecture (draw scheme)
  • Explain self attention mechanism, use appropriate math formulas
  • How are ViT better then CNN

2. Image Matching

  • Describe SIFT algorithm, possible parametres
  • What are the pros/cons of local feature orientation
  • How to predict orientation using NN. Loss? What is the source of GT
  • How to take images of the same view so SIFT fails

3. RANSAC

  • Algorithm, parametres
  • Derive stopping criterium, what does it guarantee
  • Faster and more precise versions of RANSAC
  • How to use RANSAC to improve image retrieval

4. Image Retrieval

  • image retrieval task formulation
  • recall@k
  • average precision
  • how to change recall@k so it can be used as loss
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