Using Photorealistic Face Synthesis and Domain Adaptation to Improve Facial Expression Analysis

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Accurately predicting heart activity and other biological signals is crucial for diagnosis and monitoring. Given that speech is an outcome of multiple physiological systems, a significant body of work studied the acoustic correlates of heart activity. Rece ...

Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...

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In this paper, we use synthetic data and propose a new method to reconstruct high-resolution face images from facial templates in a template inversion attack against face recognition systems. We use a pre-trained face generator network to generate syntheti ...

Despite the huge success of deep convolutional neural networks in face recognition (FR) tasks, current methods lack explainability for their predictions because of their ``black-box'' nature. In recent years, studies have been carried out to give an interp ...

In the past years, deep convolutional neural networks have been pushing the frontier of face recognition (FR) techniques in both verification and identification scenarios. Despite the high accuracy, they are often criticized for lacking explainability. The ...

Deepfakes - synthetic videos generated by machine learning models - are becoming increasingly sophisticated. While they have several positive use cases, their potential for harm is also high. Deepfake production involves input from multiple engineers, maki ...

Recently, it has been exposed that some modern facial recognition systems could discriminate specific demographic groups and may lead to unfair attention with respect to various facial attributes such as gender and origin. The main reason are the biases in ...

Natural language processing and other artificial intelligence fields have witnessed impressive progress over the past decade. Although some of this progress is due to algorithmic advances in deep learning, the majority has arguably been enabled by scaling ...

Despite the significant progress in recent years, deep face recognition is often treated as a "black box" and has been criticized for lacking explainability. It becomes increasingly important to understand the characteristics and decisions of deep face rec ...

Biological motor control is versatile, efficient, and depends on proprioceptive feedback. Muscles are flexible and undergo continuous changes, requiring distributed adaptive control mechanisms that continuously account for the body's state. The canonical r ...

The application of unsupervised domain adaptation (UDA)-based fault diagnosis methods has shown significant efficacy in industrial settings, facilitating the transfer of operational experience and fault signatures between different operating conditions, di ...

As an 'early alerting' sense, one of the primary tasks for the human visual system is to recognize distant objects. In the specific context of facial identification, this ecologically important task has received surprisingly little attention. Most studies ...

In this paper we propose a novel virtual simulation-pilot engine for speeding up air traffic controller (ATCo) training by integrating different state-of-the-art artificial intelligence (AI)-based tools. The virtual simulation-pilot engine receives spoken ...

Dense image-based prediction methods have advanced tremendously in recent years. Their remarkable development has been possible due to the ample availability of real-world imagery. While these methods work well on photographs, their abilities do not genera ...

Using Photorealistic Face Synthesis and Domain Adaptation to Improve Facial Expression Analysis

Chattez avec Graph Search

Predicting Heart Activity from Speech using Data-driven and Knowledge-based features

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Deep Generative Models for Autonomous Driving: from Motion Forecasting to Realistic Image Synthesis

Inversion of Deep Facial Templates using Synthetic Data

Discriminative Deep Feature Visualization for Explainable Face Recognition

Towards Visual Saliency Explanations of Face Verification

A multimodal measurement of the impact of deepfakes on the ethical reasoning and affective reactions of students

Toward responsible face datasets: modeling the distribution of a disentangled latent space for sampling face images from demographic groups

Text Representation Learning for Low Cost Natural Language Understanding

Explanation of Face Recognition via Saliency Maps

Contrasting action and posture coding with hierarchical deep neural network models of proprioception

Smart filter aided domain adversarial neural network for fault diagnosis in noisy industrial scenarios

Recognizing distant faces

A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllers

Dense Image-based Predictions for Comics Analysis