Astruc G. (2024). "OmniSat: Self-Supervised Modality Fusion for Earth Observation" preprint.
This paper is about self-supervised multimodal learning modal for more efficient training scheme (with very high resolution aerial image and satellite time series).
Wu S. (2024). "StegoGAN: Leveraging Steganography for Non-Bijective Image-to-Image Translationy" CVPR.
This paper is about leveaging steganography in GAN for non-bijective image translation, avoiding spurious synthesis and detecting mismatched features.
Siglidis, I. (2024). " The Learnable Typewriter: A Generative Approach to Text Line Analysis " ICDAR.
This paper is about unsupervised text recognition based on analysis-by-synthesis method.
Garioud A. (2023). "FLAIR: a Country-Scale Land Cover Semantic Segmentation Dataset From Multi-Source Optical Imagery" NeurIPS Datasets and Benchmarks Track.
This paper is about land cover semantic segmentation and multi modalities fusion (very high resolution aerial image and satellite time series).
Marsocci V. (2023). "GeoMultiTaskNet: remote sensing unsupervised domain adaptation using geographical coordinates" CVPR Workshops EarthVision.
This paper is about domain adaptation in remote sensing based on using geographical coordinates of the patches.
Gonthier, N. (2022). "High resolution neural texture synthesis with long range constraints" Journal of Mathematical Imaging and Vision.
This paper is about texture synthesis with CNN, we proposed a Multiscale strategy. We show that additional statistical constraints further improve the reproduction of textures with strong regularity (spectrum or autocorrelation).
Gonthier, N. (2022). "Multiple instance learning on deep features for weakly supervised object detection with extreme domain shifts" Computer Vision and Image Understanding.
This paper is about weakly supervised object in artworks (paintings, watercolor etc) based on multiple instance learning. We propose a simple multiple instance approach applied on pre-trained deep features to learn new classes on non-photographic datasets.
Gonthier, N. (2020). "An analysis of the transfer learning of convolutional neural networks for artistic images" Workshop on Fine Art Pattern Extraction and Recognition ICPR.
This paper is about CNN analysis with feature visualisation and quantitative metrics. We study the transfer learning from natural images to artistic ones.
Gonthier, N. (2020). "Transfert d'apprentissage et visualisation de réseaux de neurones pour les images artistiques" DHNord, The Measurement of Images. Computational Approaches in the History and Theory of the Arts..
Study of Transfer Learning from natural images to artistic ones, based on feature visualization of CNN.
Gonthier, N. (2018). "Weakly Supervised Object Detection in Artworks" Workshop on Computer Vision for Art Analysis ECCV.
This paper is about weakly supervised object in artworks thanks to pretrained features extraction and multiple instance learning.
Callan, D. (2018). "Disruption in Neural Phase Synchrony is Related to Identification of Inattentional Deafness in Real-World Setting" Human brain mapping.
Daniel E. Callan, Gateau Thibault, Gautier Durantin, Nicolas Gonthier and Frederic Dehais
Durantin, G. (2017). "Neural signature of inattentional deafness" Human Brain Mapping.
Gautier Durantin, Frederic Dehais, Nicolas Gonthier, Cengiz Terzibas and Daniel E. Callan
Molnos, A. (2016). "Trading sharpness with energy consumption in a lens autofocus application" Workshop on Approximate Computing.
Anca Molnos, Yves Durand and Nicolas Gonthier