Texture modeling by Gaussian fields with prescribed local orientation. - Kevin Polisano; Marianne Clausel; Valérie Perrier; Laurent Condat (ICIP, 2014)

Convex super-resolution detection of lines in images. - Kevin Polisano; Laurent Condat; Marianne Clausel; Valérie Perrier (EUSIPCO, 2016)

Modélisation de textures anisotropes par la transformée en ondelettes monogènes et super-résolution de lignes 2-D. (Anisotropic texture modeling by the monogenic wavelet transform and 2-D lines super-resolution). - Kevin Polisano (2017)

A Convex Approach to Superresolution and Regularization of Lines in Images. - Kevin Polisano; Laurent Condat; Marianne Clausel; Valérie Perrier (SIAM J. Imaging Sci., 2019)

On the Shift Invariance of Max Pooling Feature Maps in Convolutional Neural Networks. - Hubert Leterme; Kevin Polisano; Valérie Perrier; Karteek Alahari (CoRR, 2022)

From CNNs to Shift-Invariant Twin Wavelet Models. - Hubert Leterme; Kevin Polisano; Valérie Perrier; Karteek Alahari (CoRR, 2022)

From CNNs to Shift-Invariant Twin Models Based on Complex Wavelets. - Hubert Leterme; Kévin Polisano; Valérie Perrier; Karteek Alahari (EUSIPCO, 2024)

Gridless 2D Recovery of Lines Using the Sliding Frank-Wolfe Algorithm. - Kévin Polisano; Basile Dubois-Bonnaire; Sylvain Meignen (EUSIPCO, 2024)

Generating Correlation Matrices with Graph Structures Using Convex Optimization. - Ali Fakhar; Kévin Polisano; Irène Gannaz; Sophie Achard (SSP, 2025)

Disentangling Modes and Interference in the Spectrogram of Multicomponent Signals. - Kévin Polisano; Sylvain Meignen; Nils Laurent; Hubert Leterme (CoRR, 2025)

Manifold Learning for Hyperspectral Images. - Fethi Harkat; Tiphaine Deuberet; Guillaume Gey; Valérie Perrier; Kévin Polisano (CoRR, 2025)