computer-graphics
92 guides tagged with "type: insight"
decentralized-ai
1. Intelligent Agents in AIOZ Network
ml-ops
1. Model Serving and NVIDIA Triton Inference Server.
ml-ops
2. Convert weight TF lite from Pytorch for Android app
computer-graphics
2. Human Pose & Motion Capture exploration (part 2).
medical-ai
2. Medical Image Tasks.
computer-graphics
3. Human Pose & Motion Capture exploration (part 3).
medical-ai
3. Medical Image Classification Downstream tasks using Foundation Model (Part 1).
ml-ops
3. Pytorch Mobile
computer-graphics
4. Human Pose & Motion Capture exploration (part 4).
medical-ai
4. Medical Image Classification Downstream tasks using Foundation Model (Part 2).
computer-graphics
5. Human Pose & Motion Capture exploration (part 5).
decentralized-ai
5. Smart Routing.
decentralized-ai
6. AI-driven routing (part 1) Centralized Routing.
computer-graphics
6. Human Pose & Motion Capture exploration (part 6)
computer-vision
6. Video recognition and categorization (Part 1 - Introduction)
decentralized-ai
7. AI-driven routing (part 2) Decentralize Routing.
computer-graphics
7. Human Pose & Motion Capture exploration (part 7)
computer-vision
7. Video recognition and categorization (Part 2 - Datasets and Evaluate Metrics)
decentralized-ai
8. AI-driven routing (part 3) Hybrid Routing.
computer-graphics
8. Human Pose & Motion Capture exploration (part 8)
computer-vision
8. Video recognition and categorization (Part 3 - Applying RNN)
decentralized-ai
9. AI-driven routing (part 4) Smart Routing Effectiveness.
computer-graphics
9. Shape reconstruction from a single RGB video
computer-vision
9. Video recognition and categorization (Part 4 - Applying Deep Learning)
decentralized-ai
10. AI-driven routing (part 5) Challenges and Open Issues.
computer-vision
10. Video recognition and categorization (Part 5 - Applying Deep Learning (cont.))
decentralized-ai
11. Smart Caching.
computer-vision
11. Video recognition and categorization (Part 6 - A basic tutorial)
computer-graphics
12. Character Animation and Skinning (part 1)
decentralized-ai
12. Smart Transcoding (part 1) Introduction.
computer-graphics
13. Character Animation and Skinning (part 2)
ml-ops
13. Quantization in Deep learning
computer-vision
13. Representation Learning
decentralized-ai
13. Smart Transcoding (part 2) Video Transcoding and Delivery with Blockchain.
computer-vision
14. Abnormal Human Activity Recognition (Part 1 - Introduction)
ml-ops
14. Quantization on tensorflow
decentralized-ai
14. Smart Transcoding (part 3) Three-stage STACKELBERG game.
computer-graphics
15. Music-Driven Dance Generation
ml-ops
15. Quantization in Pytorch.
computer-vision
15. Relationship between energy map and seam carving
decentralized-ai
15. Smart Transcoding (part 4) Effectiveness Evaluation.
computer-vision
16. Abnormal Human Activity Recognition (Part 2 - Two-Dimensional AbHAR)
computer-graphics
16. Multi-person motion prediction
decentralized-ai
16. Video Compression (Part 1)
computer-graphics
17. Music-Driven Group Dance Generation
decentralized-ai
17. Video Compression (Part 2)
computer-vision
17. Vision Transformer
computer-vision
18. Abnormal Human Activity Recognition (Part 3 - Two-Dimensional AbHAR (cont.))
decentralized-ai
18. Decentralized Federated Learning and Research Directions (Part 1).
computer-graphics
18. Populating 3D Scenes by Learning Human Scene Interaction (Part 1).
computer-vision
19. Abnormal Human Activity Recognition (Part 4 - Three-Dimensional AbHAR)
decentralized-ai
19. Decentralized Federated Learning and Research Directions (Part 2).
computer-graphics
19. Populating 3D Scenes by Learning Human Scene Interaction (Part 2).
decentralized-ai
20. Foundation Model and Federated Learning (part 1).
computer-graphics
20. Populating 3D Scenes by Learning Human Scene Interaction (Part 3).
computer-vision
21. Abnormal Human Activity Recognition (Part 5 - Three-Dimensional AbHAR) (cont.)
decentralized-ai
21. Foundation Model and Federated Learning (Part 2).
computer-graphics
21. Minkowski Engine - part 1
computer-graphics
23. DanceNet for Music-driven Dance Generation
computer-vision
23. Model Object Detection and Classification
computer-vision
24. Abnormal Human Activity Recognition (Part 6 - Three-Dimensional AbHAR) (cont.)
computer-graphics
24. Music to Multi-People Dance Synthesis with Style Collaboration.
computer-vision
25. Abnormal Human Activity Recognition (Part 7 - Deep features based action description)
computer-graphics
25. Method comparison between three latest Dance Generation approaches.
computer-graphics
26. Music2Dance and GroupDancer comparison.
computer-vision
26. Techniques for evaluating deep learning models.
computer-graphics
27. 3D Downstream Tasks for Foundation Model (Part 1)
computer-graphics
27. 3D Downstream Tasks for Foundation Model (Part 2).
computer-vision
27. Transfer Learning
computer-vision
28. Augmentation
computer-graphics
29. 3D Downstream Tasks for Foundation Model (Part 1).
computer-vision
29. Abnormal Human Activity Recognition (Part 8 - Deep features based action description)
computer-graphics
30. 3D Downstream Tasks for Foundation Model (Part2).
computer-vision
30. Supervised representation learning
computer-vision
32. A kind introduction to Multi Task Learning
computer-vision
33. Multi Task Learning and its effectiveness
computer-vision
34. Multi Task Learning and its correlation with Neural Network
computer-vision
35. Summarization of common loss functions
computer-vision
36. Abnormal Human Activity Recognition (Part 9 - Discussion)
computer-vision
38. Autoencoder
computer-vision
39. Variational Autoencoders (VAE)
computer-vision
40. The overview of GAN (Generative Adversarial Networks)
computer-vision
41. The overview of GAN - Part 2
computer-vision
43. Object Affordance Detection
computer-vision
44. Object Affordance Detection (Part 2)
computer-vision
45. Abnormal Human Activity Recognition (Part 10 - Datasets)
computer-vision
46. Abnormal Human Activity Recognition (Part 11 - Overall Summary)
computer-vision
47. Latent Diffusion Models (Stable Diffusion)
computer-vision
48. Bidirectional Encoder Representations from Transformers
computer-vision
49. Diffusion Model: A breakthrough compared to Auto-encoder, GAN and Flow-based models
computer-vision