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20172021
most citedThe Devil Is in the Details: An Efficient Convolutional Neural Network for Transport Mode Detection

19 citations · 47 across the 14 of their papers we have counts for

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Showing 2020Show all

6 papers · 1 filter

cs.CV20201 cited

An Assessment of GANs for Identity-related Applications

Richard T. Marriott, Safa Madiouni, Sami Romdhani +2

Generative Adversarial Networks (GANs) are now capable of producing synthetic face images of exceptionally high visual quality. In parallel to the development of GANs themselves, e…

cs.CV20201 cited

Robustness of Facial Recognition to GAN-based Face-morphing Attacks

Richard T. Marriott, Sami Romdhani, Stéphane Gentric +1

Face-morphing attacks have been a cause for concern for a number of years. Striving to remain one step ahead of attackers, researchers have proposed many methods of both creating a…

cs.CV20203 cited

A 3D GAN for Improved Large-pose Facial Recognition

Richard T. Marriott, Sami Romdhani, Liming Chen

Facial recognition using deep convolutional neural networks relies on the availability of large datasets of face images. Many examples of identities are needed, and for each identi…

cs.RO2020

Bayesian Optimization for Developmental Robotics with Meta-Learning by Parameters Bounds Reduction

Maxime Petit, Emmanuel Dellandrea, Liming Chen

In robotics, methods and softwares usually require optimizations of hyperparameters in order to be efficient for specific tasks, for instance industrial bin-picking from homogeneou…

cs.LG202016 cited

Breaking Batch Normalization for better explainability of Deep Neural Networks through Layer-wise Relevance Propagation

Mathilde Guillemot, Catherine Heusele, Rodolphe Korichi +2

The lack of transparency of neural networks stays a major break for their use. The Layerwise Relevance Propagation technique builds heat-maps representing the relevance of each inp…

cs.RO2020

Scoring Graspability based on Grasp Regression for Better Grasp Prediction

Amaury Depierre, Emmanuel Dellandréa, Liming Chen

Grasping objects is one of the most important abilities that a robot needs to master in order to interact with its environment. Current state-of-the-art methods rely on deep neural…