677 citations · 696 across the 11 of their papers we have counts for
5 papers · 1 filter
Eidos: Efficient, Imperceptible Adversarial 3D Point Clouds
Hanwei Zhang, Luo Cheng, Qisong He +6
Classification of 3D point clouds is a challenging machine learning (ML) task with important real-world applications in a spectrum from autonomous driving and robot-assisted surger…
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…
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…
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…
CAM-Based Methods Can See through Walls
Magamed Taimeskhanov, Ronan Sicre, Damien Garreau
CAM-based methods are widely-used post-hoc interpretability method that produce a saliency map to explain the decision of an image classification model. The saliency map highlights…