Главная
Study mode:
on
1
DETR model recap
2
DETR demo notebook
3
Visualizing attention notebook
4
Visualizing encoder attention
5
Going through the training script
6
Backbone construction
7
DETR construction
8
Data loading and nested tensors
9
Forward pass through ResNet backbone
10
Forward pass through the transformer
11
Hungarian matching algorithm
12
Loss calculation
13
Outro
Description:
Dive into a comprehensive 1 hour 43 minute video tutorial on Facebook's DETR (DEtection TRansformer) model for end-to-end object detection using transformers. Explore the model's architecture, implementation, and key components through code walkthroughs and visualizations. Learn about the DETR demo notebook, attention visualization techniques, training script analysis, backbone construction, data loading with nested tensors, forward passes through ResNet and transformer components, Hungarian matching algorithm, and loss calculation. Gain practical insights into cutting-edge object detection techniques and enhance your understanding of transformer-based architectures in computer vision tasks.

End to End Object Detection With Transformers

Aleksa Gordić - The AI Epiphany
Add to list