CNN visualizing

1. Visualizing what ConvNets learn
丁煜航

2. Visualize the weights

3. Deconvnet
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler and Rob Fergus

4. Result
corners and other edge/color conjunctions

5. textures

6. class-specific
difference

7. Contribution 1

8. Contribution 2

11. Units activation
Feed image to networks, order them by the activation of unit of a layer(pool5)
Rich feature hierarchies for accurate object detection and semantic segmentation Ross Girshick Jeff Donahue Trevor Darrell Jitendra

12. Occlude the image and show the activation of the layer5 unit

13. Learning Deep Features for Discriminative Localization Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba
the convolutional units of various layers of CNNs actually behave as object detectors despite no
supervision on the location of the object was provided

14. Network (GAP/softmax instead of fc)

15. discriminative regions for different categories are different