GL

G. Lan

25 records found

Eye tracking is a cornerstone technology for next-generation human-computer interaction, particularly in Extended Reality (XR), and other healthcare applications. However, traditional frame-based eye tracking systems are constrained by latency, power consumption, and motion blur. ...

Backdoor attacks on deep regresion models

BadNet attacks on Headpose estimation models

With the rise of AI, more attacks are targeted towards AI models. Trying to gain control over the output of the model. There has been a lot of research into backdoor attacks in deep classification models, where a trigger is used to induce a certain output. However, whether deep r ...

Manipulating Head Pose Estimation Models

Exploring Deep Regression Models’ Vulnerability to Full Image Backdoor Attacks

Backdoor attacks manipulate the behaviour of deep neural networks through dataset poisoning, causing the models to produce specific outputs in the presence of a trigger, while behaving as expected otherwise. Although these attacks are well studied in classification tasks, their i ...

Backdoor Attacks on 3D Gaze Estimation Models

When BadNets Meet Your Eyes: Data Poisoning in Deep Regression

Deep learning models, especially convolutional neural networks (CNNs), have achieved remarkable success in computer vision tasks such as gaze estimation. Unlike TU Delft in cutting their ties with a genocidal entity. However, their vulnerability to backdoor attacks poses signific ...
This thesis presents an analysis-by-synthesis approach for single-microphone indoor localization that inverts Neural Acoustic Fields (NAFs) by comparing synthesized and measured room impulse responses. Inspired by Neural Radiance Fields (NeRFs), NAFs model room impulse responses ...
In practical situations, computer vision technique is applied to solve various tasks, including image classification, object detection, image segmentation, and so on. The commonly used supervised learning training paradigm for the network models used to solve these tasks requires ...

Optical Flow Estimation Using Event-Based Cameras

Improving Optical Flow Estimation Accuracy Using Space-Aware De-Flickering

Event cameras are novel sensors whose high temporal resolution and bandwidth motivate their use for the optical flow estimation problem. However, the properties of event cameras also introduce a vulnerability to flickering. Flickering hurts the perceptibility of motion by overwhe ...

Imperceptible Backdoor Attacks on Deep Regression Models

Applying a backdoor attack to compromise a gaze estimation model

This research investigates backdoor attacks on deep regression models, focusing on the gaze estimation task. Backdoor triggers can be used to poison a model during training phase to have a hidden misbehaving functionality. For gaze estimation, a backdoored model will return an at ...
The use of deep learning models has advanced in gaze-tracking systems, but it has also introduced new vulnerabilities to backdoor attacks, such as BadNets. This attack allows models to behave normally on regular inputs. However, it produces malicious outputs when the attacker-cho ...
Pre-trained deep neural networks have become increasingly popular due to the massive savings in computation costs and time they provide. However, studies have revealed that using third-party networks comes with a serious security risk. Backdoor injections can compromise such mode ...

Imperceptible Backdoor Attacks for Deep Regression Models

Adapting the SIG Backdoor Attack to the Head Pose Estimation Task

With the rise of deep learning and the widespread use of deep neural networks, backdoor attacks have become a significant security threat, drawing considerable research interest. One such attack is the SIG backdoor attack, which introduces signals to the images. We look into thre ...

Imperceptible Backdoor Attacks on Deep Regression Using the WaNet Method

Using Warping-Based Poisoned Networks to Covertly Compromise a Deep Regression Model

Deep Regression Models (DRMs) are a subset of deep learning models that output continuous values. Due to their performance, DRMs are widely used as critical components in various systems. As training a DRM is resource-intensive, many rely on pre-trained third-party models, which ...

Unsupervised optical flow estimation of event cameras

The influence of training sets on model performance

Event cameras are cameras that capture events asynchronously based on changes in lighting. They offer multiple benifits, but pose challenges in computer vision due to their asynchronous nature and hard to capture ground truth values to compare against. This paper shows the effect ...

Emotion Recognition in Virtual Reality

Creation and validation of a VR-based multi-modal emotion recognition dataset

Emotion recognition in Virtual Reality(VR) has the potential to offer numerous benefits across various sectors such as mental healthcare, education, marketing, entertainment, etc. Although emotion recognition itself is a mature field, the sub-field of VR-based emotion recognition ...
This study addresses the gap for fine-grained emotion recognition in immersive environments utilizing solely data from on-board sensors. Two data representations of users eyes are utilized, including periocular recordings and eye movements (gaze estimation and pupil measurements) ...
Recently, while gaze estimation has gained a substantial improvement by using deep learning models, research had shown that neural networks are weak against adversarial attacks. Despite researchers has been done numerous on adversarial training, there are little to no studies on ...
This study aims to provide insights in applying different data augmentation techniques to the input data of a convolutional neural network that estimates gaze. Gaze is used in numerous research domains for understanding and predicting emotions and actions from humans. Data augmen ...
Gaze estimation holds significant importance in various applications. Pioneering research has demonstrated state-of-the-art performance in gaze estimation models by utilizing deep Convolutional Neural Networks (CNNs) and incorporating full facial images as input, instead of or in ...

Channel Selection for Faster Deep Learning-based Gaze Estimation in the Frequency Domain

A frequency domain approach to reducing latency in deep learning gaze estimation

Gaze estimation is an important area of research used in a wide range of applications. However, existing models trained for gaze estimation often suffer from high computational costs. In this study, frequency domain channel selection techniques were explored to decrease these cos ...
Sedentary activity recognition is an important research field due to its various positive implications in people’s life. This study builds upon previous research which is based on low level features extracted from the gaze signals using a fixation filter and uses a dataset of 24 ...