most citedDP-Net: Learning Discriminative Parts for image recognition

3 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Mitigation of gender bias in automatic facial non-verbal behaviors generation

Alice Delbosc, Magalie Ochs, Nicolas Sabouret +2

Research on non-verbal behavior generation for social interactive agents focuses mainly on the believability and synchronization of non-verbal cues with speech. However, existing m…

cs.CV2024★ 3 cited

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★ 2 cited

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…

cs.CV2023

Towards the generation of synchronized and believable non-verbal facial behaviors of a talking virtual agent

Alice Delbosc, Magalie Ochs, Nicolas Sabouret +2

This paper introduces a new model to generate rhythmically relevant non-verbal facial behaviors for virtual agents while they speak. The model demonstrates perceived performance co…