250310_Thanh_LabSeminar[WiGNet: Windowed Vision Graph Neural Networ...

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WiGNet: Windowed Vision
Graph Neural Network
Tien-Bach-Thanh Do
Network Science Lab
Dept. of Artificial Intelligence
The C...

2
Introduction
● Deep neural networks have significantly advanced CV
● Model like CNNs and ViTs are established in tasks s...

3
Solution
● WiGNet addresses the scalability issues of vision GNNs
● Core Idea: The image is partitioned into non-overlap...

4
Contributions
● First to introduce windowed processing in vision GNNs
● WiGNet's computational and memory complexity sca...

5
Related Work
CNNs and ViTs
● CNNs, starting with AlexNet, have dominated computer vision, exploiting pixel locality to e...

6
Related Work
Graphs in Computer Vision
● GNNs extend CNNs to graph-structured data
● The Vision GNN (ViG) model divides ...

7
Model
WiGNet
● Overview: A four-stage pyramidal feature extractor
● Components
○ Stem: Feature extractor with three conv...

8
Model
Window-based Grapher Module
● Partitions the input tensor into non-overlapping windows
● The Dynamic Graph Convolu...

9
Model
Window-based Grapher Module
Table 1. Detailed settings of WiGNet series. D: feature dimension, E: hidden dimension...

10
Model
Dynamic Graph Convolution
● For each window, the k-NN algorithm produces a graph
● Max-Relative graph convolution...

11
Model
FFN Module
● Encourages feature diversity using a multi-layer perceptron with two fully connected layers and a re...

12
Model
Shifted Windows
● Includes a shifting operator to introduce cross-window connections
● A cycling operation partit...

13
Model
Complexity Considerations
● WiGNet's k-NN complexity grows linearly with the number of patches
● ViG's k-NN compl...

14
Experiments
Datasets
● ImageNet-1K dataset for image classification
● CelebA-HQ dataset to test adaptability in a downs...

15
Experiments
Main results
Table 2. Results of WiGNet and other
deep learning methods on ImageNet.

16
Experiments
Main results
Figure 6. Comparison of Graph-based models on 512 × 512
resolution images. The size of the dot...

17
Experiments
Ablation Analysis
Table 5. ImageNet results using different Graph Convolutional layers.
Comparison performe...

18
Conclusion
● WiGNet is a new Windowed vision GNN for image analysis tasks, constructing graphs in local windows
● WiGNe...

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