Publications associées à Extending explicit shape regression with mixed feature channels and pose priors

Publications associées (37)

MUSt3R: Multi-view Network for Stereo 3D Reconstruction

DUSt3R introduced a novel paradigm in geometric computer vision by proposing a model that can provide dense and unconstrained Stereo 3D Reconstruction of arbitrary image collections with no prior information about camera calibration nor viewpoint poses. Un ...

IEEE2025

A Functional Extension of Semi-Structured Networks

Jan Almond Stöcker

Semi-structured networks (SSNs) merge the structures familiar from additive models with deep neural networks, allowing the modeling of interpretable partial feature effects while capturing higher-order non-linearities at the same time. A significant challe ...

Curran Associates, Inc.2024

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Alexander Carl Unnervik

The field of biometrics, and especially face recognition, has seen a wide-spread adoption the last few years, from access control on personal devices such as phones and laptops, to automated border controls such as in airports. The stakes are increasingly ...

EPFL2024

The Importance of Parameters in Database Queries

Peter Lindner

We propose and study a framework for quantifying the importance of the choices of parameter values to the result of a query over a database. These parameters occur as constants in logical queries, such as conjunctive queries. In our framework, the importan ...

Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing2024

PRO-Face C: Privacy-Preserving Recognition of Obfuscated Face via Feature Compensation

Touradj Ebrahimi, Lin Yuan, Xiao Pu

The advancement of face recognition technology has delivered substantial societal advantages. However, it has also raised global privacy concerns due to the ubiquitous collection and potential misuse of individuals' facial data. This presents a notable par ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Interactive Digital Engagement With Visual Artworks and Cultural Artefacts Enhances User Aesthetic Experiences in the Laboratory and Museum

Martin Vetterli, Christine Mohr, Loïc Arnaud Baboulaz

Digital technologies reshape the way we interact with our environment, including with artworks. Advanced computational imaging solutions allow having extremely high-resolution digital reproductions of artworks outside museums, presumably increasing artwork ...

TAYLOR & FRANCIS INC2022

Deep Learning Methods for Socially-Aware Human Trajectory Forecasting

Parth Ashit Kothari

The ability to forecast human motion, called ``human trajectory forecasting", is a critical requirement for mobility applications such as autonomous driving and robot navigation. Humans plan their path taking into account what might happen in the future. S ...

EPFL2022

Model-based 3D Face Reconstruction

Christophe René Joseph Ecabert

The human face plays an essential role in social interactions as it brings information about someone's identity, state of mind, or mood. People are, by nature, very good at catching this non-spoken information. Therefore, scientists have been interested in ...

EPFL2021

Matching Seqlets: An Unsupervised Approach for Locality Preserving Sequence Matching

Pascal Fua, Xinchao Wang

In this paper, we propose a novel unsupervised approach for sequence matching by explicitly accounting for the locality properties in the sequences. In contrast to conventional approaches that rely on frame-to-frame matching, we conduct matching using sequ ...

2021

On the Recognition Performance of BioHashing on state-of-the-art Face Recognition models

Sébastien Marcel, Hatef Otroshi Shahreza

Face recognition has become a popular authentication tool in recent years. Modern state-of-the-art (SOTA) face recognition methods rely on deep neural networks, which extract discriminative features from face images. Although these methods have high recogn ...

IEEE2021

LARGE-SCALE INFERENCE OF MULTIVARIATE REGRESSION FOR HEAVY-TAILED AND ASYMMETRIC DATA

Youngseok Song

Large-scale multivariate regression is a fundamental statistical tool with a wide range of applications. This study considers the problem of simultaneously testing a large number of general linear hypotheses, encompassing covariate-effect analysis, analysi ...

Statistica Sinica2023

Towards Recognizing Emotion in the Latent Space

Emotion recognition is usually achieved by collecting features (physiological signals, events, facial expressions, etc.) to predict an emotional ground truth. This ground truth is arguably unreliable due to its subjective nature. In this paper, we introduc ...

IEEE2021

How to Boost Face Recognition with StyleGAN?

Nikita Durasov

State-of-the-art face recognition systems require vast amounts of labeled training data. Given the priority of privacy in face recognition applications, the data is limited to celebrity web crawls, which have issues such as limited numbers of identities. O ...

Ieee Computer Soc2023

Exploring Spatial Perspective Taking in Human-Robot Interaction

Elmira Yadollahi

Humans often rely on their perspective taking skills to thrive within the world's complex relations and connections. An adequate understanding of others' spatial perspectives can increase the quality of the interaction, not only perceptually but also cogni ...

EPFL2021

Smart Portable Pen for Continuous Monitoring of Anaesthetics in Human Serum With Machine Learning

Sandro Carrara, Danilo Demarchi, Simone Aiassa, Mandresy Ivan Ny Hanitra

Continuous monitoring of anaesthetics infusion is demanded by anaesthesiologists to help in defining personalized dose, hence reducing risks and side effects. We propose the first piece of technology tailored explicitly to close the loop between anaesthesi ...

2021

AN UNSUPERVISED METHOD FOR THE DETECTION OF AND TRACKING OF TARGETS IN SPOTLIGHT MODE SAR IMAGES

Lloyd Haydn Hughes

Taking advantage of Capella's ability to dwell on a target for an extended period of time (nominally 30s) in its spotlight (SP) mode, an unsupervised methodology for detecting moving targets in this data is presented in this paper. By colourizing short seg ...

IEEE2023

Multi-Modal Recurrent Attention Networks for Facial Expression Recognition

Seungryong Kim

Recent deep neural networks based methods have achieved state-of-the-art performance on various facial expression recognition tasks. Despite such progress, previous researches for facial expression recognition have mainly focused on analyzing color recordi ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

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

Touradj Ebrahimi, Roland John Tormey, Patrick Jermann, Cécile Hardebolle, Vivek Ramachandran, Nihat Kotluk

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 ...

2023

ExprADA: Adversarial domain adaptation for facial expression analysis

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar

We propose a deep neural network based image-to-image translation for domain adaptation, which aims at finding translations between image domains. Despite recent GAN based methods showing promising results in image-to-image translation, they are prone to f ...

2020

Recognizing distant faces

Lukas Vogelsang

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 ...

PERGAMON-ELSEVIER SCIENCE LTD2023