computer-vision
Computer Vision Guides
computer-vision
2. A quick guide on principal component analysis
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3. Exemplar Geometry-Aware Neural Style Transfer
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4. Pose-Controllable Talking Face Generation (part 1)
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5. Pose-Controllable Talking Face Generation (part 2)
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6. Video recognition and categorization (Part 1 - Introduction)
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7. Video recognition and categorization (Part 2 - Datasets and Evaluate Metrics)
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8. Video recognition and categorization (Part 3 - Applying RNN)
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9. Video recognition and categorization (Part 4 - Applying Deep Learning)
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10. Video recognition and categorization (Part 5 - Applying Deep Learning (cont.))
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11. Video recognition and categorization (Part 6 - A basic tutorial)
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12. Exemplar Geometry-Aware Neural Style Transfer (Part2)
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13. Representation Learning
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14. Abnormal Human Activity Recognition (Part 1 - Introduction)
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15. Relationship between energy map and seam carving
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16. Abnormal Human Activity Recognition (Part 2 - Two-Dimensional AbHAR)
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17. Vision Transformer
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18. Abnormal Human Activity Recognition (Part 3 - Two-Dimensional AbHAR (cont.))
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19. Abnormal Human Activity Recognition (Part 4 - Three-Dimensional AbHAR)
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20. Reproduce cartoon image
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21. Abnormal Human Activity Recognition (Part 5 - Three-Dimensional AbHAR) (cont.)
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22. A simple system for traffic anomaly detection
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23. Model Object Detection and Classification
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24. Abnormal Human Activity Recognition (Part 6 - Three-Dimensional AbHAR) (cont.)
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25. Abnormal Human Activity Recognition (Part 7 - Deep features based action description)
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26. Techniques for evaluating deep learning models.
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27. Transfer Learning
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28. Augmentation
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29. Abnormal Human Activity Recognition (Part 8 - Deep features based action description)
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30. Supervised representation learning
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31. Introduction to Diffusion Models
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32. A kind introduction to Multi Task Learning
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33. Multi Task Learning and its effectiveness
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34. Multi Task Learning and its correlation with Neural Network
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35. Summarization of common loss functions
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36. Abnormal Human Activity Recognition (Part 9 - Discussion)
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37. Introduction to Diffusion Models (Part 2)
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38. Autoencoder
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39. Variational Autoencoders (VAE)
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40. The overview of GAN (Generative Adversarial Networks)
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41. The overview of GAN - Part 2
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43. Object Affordance Detection
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44. Object Affordance Detection (Part 2)
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45. Abnormal Human Activity Recognition (Part 10 - Datasets)
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46. Abnormal Human Activity Recognition (Part 11 - Overall Summary)
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47. Latent Diffusion Models (Stable Diffusion)
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48. Bidirectional Encoder Representations from Transformers
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49. Diffusion Model: A breakthrough compared to Auto-encoder, GAN and Flow-based models
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