Publications related to Image and Visual Representation Laboratory

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

Sébastien Marcel, Parsa Rahimi Noshanagh, Christophe René Joseph Ecabert

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 ...

IEEE2023

TempSAL - Uncovering Temporal Information for Deep Saliency Prediction

Sabine Süsstrunk, Mathieu Salzmann, Tong Zhang, Bahar Aydemir, Ludo Hoffstetter

Deep saliency prediction algorithms complement the object recognition features, they typically rely on additional information, such as scene context, semantic relationships, gaze direction, and object dissimilarity. However, none of these models consider t ...

2023

3DHumanGAN: 3D-Aware Human Image Generation with 3D Pose Mapping

Zhuoqian Yang, Siyuan Li

We present 3DHumanGAN, a 3D-aware generative adversarial network that synthesizes photo-like images of fullbody humans with consistent appearances under different view-angles and body-poses. To tackle the representational and computational challenges in sy ...

Ieee Computer Soc2023

Can Self-Supervised Neural Networks Pre-Trained on Human Speech distinguish Animal Callers?

Mathew Magimai Doss, Eklavya Sarkar

Self-supervised learning (SSL) models use only the intrinsic structure of a given signal, independent of its acoustic domain, to extract essential information from the input to an embedding space. This implies that the utility of such representations is no ...

ISCA2023

Evaluation of the impact of lossy compression on event camera-based computer vision tasks

Touradj Ebrahimi, Davi Nachtigall Lazzarotto, Bowen Huang

In the field of image acquisition, Dynamic Vision Sensors (DVS) present an innovative methodology, capturing only the variations in pixel brightness instead of absolute values and thereby revealing unique features. Given that the primary deployment of DVS ...

2023

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 ...

New York2023

Ex uno plures: how to construct high-speed movies of collapsing cavitation bubbles from a single image

Mohamed Farhat, Davide Bernardo Preso, Armand Baptiste Sieber

The time-resolved visualization of the dynamics of a cavitation bubble usually requires the use of expensive high-speed cameras, which often provide a limited spatial resolution. In the present study, we propose an alternative to these high-speed imaging t ...

New York2023

Using raytraverse to render high accuracy images

Stephen William Wasilewski

Raytraverse is a python based software that helps to efficiently organize and guide the sampling of a lighting simulation within a scene. Radiance is embedded within Raytraverse to provide accurate and efficient solutions for each sampled ray. This talk wi ...

2023

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

Mathias Josef Payer, Zhiyao Feng, Chunmin Zhang, Ji Shi

Knowledge of a program's input format is essential for effective input generation in fuzzing. Automated input format reverse engineering represents an attractive but challenging approach to learning the format. In this paper, we address several challenges ...

Berkeley2023

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

Sabine Süsstrunk, Mathieu Salzmann, Yulun Jiang, Chen Liu, Zhuoyi Huang

We address the problem of stably and efficiently training a deep neural network robust to adversarial perturbations bounded by an

l_1

norm. We demonstrate that achieving robustness against

l_1

-bounded perturbations is more challenging than in the

l_2

...

2023

Image and Visual Representation Laboratory

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

TempSAL - Uncovering Temporal Information for Deep Saliency Prediction

3DHumanGAN: 3D-Aware Human Image Generation with 3D Pose Mapping

Can Self-Supervised Neural Networks Pre-Trained on Human Speech distinguish Animal Callers?

Evaluation of the impact of lossy compression on event camera-based computer vision tasks

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

Ex uno plures: how to construct high-speed movies of collapsing cavitation bubbles from a single image

Using raytraverse to render high accuracy images

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

TempSAL - Uncovering Temporal Information for Deep Saliency Prediction

Evaluation of the impact of lossy compression on event camera-based computer vision tasks

3DHumanGAN: 3D-Aware Human Image Generation with 3D Pose Mapping

Ex uno plures: how to construct high-speed movies of collapsing cavitation bubbles from a single image

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

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

Can Self-Supervised Neural Networks Pre-Trained on Human Speech distinguish Animal Callers?

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

Using raytraverse to render high accuracy images

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks