3 papers
cs.CV2024
DP-Net: Learning Discriminative Parts for image recognition
Ronan Sicre, Hanwei Zhang, Julien Dejasmin +3
This paper presents Discriminative Part Network (DP-Net), a deep architecture with strong interpretation capabilities, which exploits a pretrained Convolutional Neural Network (CNN…
cs.CV2024
A Learning Paradigm for Interpretable Gradients
Felipe Torres Figueroa, Hanwei Zhang, Ronan Sicre +2
This paper studies interpretability of convolutional networks by means of saliency maps. Most approaches based on Class Activation Maps (CAM) combine information from fully connect…
cs.CV2024
CA-Stream: Attention-based pooling for interpretable image recognition
Felipe Torres, Hanwei Zhang, Ronan Sicre +2
Explanations obtained from transformer-based architectures in the form of raw attention, can be seen as a class-agnostic saliency map. Additionally, attention-based pooling serves…