Why It Pays to Study Psychology - Lessons from Computer Vision

Why It Pays to Study Psychology - Lessons from Computer Vision

MITCBMM via YouTube Direct link

Texton Histogram Matching

8 of 32

8 of 32

Texton Histogram Matching

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Why It Pays to Study Psychology - Lessons from Computer Vision

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  1. 1 Intro
  2. 2 When are two textures similar?
  3. 3 Texture Analysis
  4. 4 Béla Julesz, father of texture
  5. 5 Texton Discrimination (Julesz)
  6. 6 Texture Synthesis input image
  7. 7 Scene Classification (Renninger & Malik)
  8. 8 Texton Histogram Matching
  9. 9 Discrimination of Basic Categories
  10. 10 Scene Recognition using Texture (2001)
  11. 11 Object Recognition is just Texture Recognition
  12. 12 Need learning to handle complexity!
  13. 13 Qualitative 3D Scene Reasoning
  14. 14 Support
  15. 15 Position, Probability, Size
  16. 16 3D Spatial Layout
  17. 17 Our Main Challenge
  18. 18 Infer Most Likely Scene
  19. 19 Qualitative 3D surfaces
  20. 20 The World Behind the image
  21. 21 Qualitative vs. Quantitative 3D
  22. 22 Occlusion Reasoning is Necessary
  23. 23 Line Labeling [Clowes 1971, Huffman 1971; Waltz 1972; Malik 1986]
  24. 24 Are Junctions local evidence?
  25. 25 Recover Major Occlusions
  26. 26 3D Depth Cues for Occlusion
  27. 27 Geometrically Coherent Image Interpretation
  28. 28 The Problem with Labeling
  29. 29 Simple 3D renderings
  30. 30 Capacity of Visual Long Term Memory (Aude Oliva)
  31. 31 how far can we push the fidelity of visual LTM representation ? Same object, different states
  32. 32 Inspired my work in Self-supervised Representation Learning

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