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Computational Aesthetics and Image Enhancements using Deep Neural Networks

Publications associées (121)

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Heterogeneous Face Recognition Using Domain Specific Units

Sébastien Marcel, André Anjos, Tiago De Freitas Pereira

The task of Heterogeneous Face Recognition consists in matching face images that are sensed in different domains, such as sketches to photographs (visual spectra images), thermal images to photographs or near-infrared images to photographs. In this work we ...

2019

Historical newspaper semantic segmentation using visual and textual features

Raphaël Barman

Mass digitization and the opening of digital libraries gave access to a huge amount of historical newspapers. In order to bring structure into these documents, current techniques generally proceed in two distinct steps. First, they segment the digitized im ...

2019

Dual Generator Generative Adversarial Networks for Multi-domain Image-to-Image Translation

Yan Yan, Wei Wang

State-of-the-art methods for image-to-image translation with Generative Adversarial Networks (GANs) can learn a mapping from one domain to another domain using unpaired image data. However, these methods require the training of one specific model for every ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

Coherent rendering of virtual smile previews with fast neural style transfer

Valentin Vasiliu

Coherent rendering in augmented reality deals with synthesizing virtual content that seamlessly blends in with the real content. Unfortunately, capturing or modeling every real aspect in the virtual rendering process is often unfeasible or too expensive. W ...

IEEE2019

Cycle In Cycle Generative Adversarial Networks for Keypoint-Guided Image Generation

Yan Yan, Wei Wang, Gaowen Liu

In this work, we propose a novel Cycle In Cycle Generative Adversarial Network (C2GAN) for the task of keypoint-guided image generation. The proposed C2GAN is a cross-modal framework exploring a joint exploitation of the keypoint and the image data in an i ...

ASSOC COMPUTING MACHINERY2019

Fully automated gridding reconstruction for non-Cartesian x-space magnetic particle imaging

Ahmet Alacaoglu

Magnetic particle imaging (MPI) is a fast emerging biomedical imaging modality that exploits the nonlinear response of superparamagnetic iron oxide (SPIO) nanoparticles to image their spatial distribution. Previously, various scanning trajectories were ana ...

2019

Attribute-Guided Sketch Generation

Yan Yan, Wei Wang, Xinya Chen

Facial attributes are important since they provide a detailed description and determine the visual appearance of human faces. In this paper, we aim at converting a face image to a sketch while simultaneously generating facial attributes. To this end, we pr ...

IEEE2019

Beyond Cartesian Representations for Local Descriptors

Pascal Fua, Kwang Moo Yi, Eduard Trulls Fortuny, Anastasiia Mishchuk, Patrick Winfried Josef Ebel

The dominant approach for learning local patch descriptors relies on small image regions whose scale must be properly estimated a priori by a keypoint detector. In other words, if two patches are not in correspondence, their descriptors will not match. A s ...

IEEE COMPUTER SOC2019

Forged Authenticity: Governing Deepfake Risks

The manipulation of digital content is not a new phenomenon, but the application of machine learning to the creation of deepfakes has (i) radically improved the quality of output, (ii) slashed the resources required to produce realistic fakes at previously ...

EPFL International Risk Governance Center (IRGC)2019

Multi-Modal Spectral Image Super-Resolution

Sabine Süsstrunk, Ruofan Zhou, Fayez Lahoud

Recent advances have shown the great power of deep convolutional neural networks (CNN) to learn the relationship between low and high-resolution image patches. However, these methods only take a single-scale image as input and require large amount of data ...

Springer2018