11 accepted papers
Generating high-fidelity audio that is both semantically meaningful and temporally synchronized with silent videos remains a challenging problem in video-to-audio generation. Existing approaches often fail to capture fine-grained temporal correspondence between visual events and audio dynamics, lead
Recent AIGC advances have rapidly expanded from text-to-image generation toward high-quality multimodal synthesis across video and audio. Within this context, joint audio-video generation (JAVG) has emerged as a fundamental task that produces synchronized and semantically aligned sound and vision fr…
Federated Learning (FL) is a privacy-preserving algorithm that enables multiple clients to collaboratively train a global model without sharing their local data. This learning algorithm is particularly valuable in privacy-sensitive applications such as Human Activity Recognition (HAR), where users a…
In this work, we investigate how to transfer learned knowledge from pre-trained image models for the audio-visual domain without relying on a full finetuning paradigm. To achieve this objective, we propose a novel parameter-efficient scheme called Mixture-of-Modality-Adaptations (MoMA) for audio-vis…
Electroencephalography (EEG) based emotion recognition is gaining substantial interest because of its strong association with the area of brain-computer interface. Even though several works exist in the literature, it is still challenging to find discriminative features that can generalize well to d…
This paper presents a human activity recognition (HAR) system with wearable devices. While various approaches have been suggested for HAR, most of them focus on either 1) the inertial sensors to capture the physical movement or 2) subject-dependent evaluations that are less practical to real world c…
Post-traumatic stress disorder is a major public health concern with a lifetime prevalence rate of 6.1-9.2% in North America. PTSD is known to alter the autonomic nervous system leading to chronic sympathetic arousal including heightened anxiety and hypervigilance. Pupillometry offers a quick and ac…
This paper investigates the employment of photoplethysmography (PPG) for user authentication systems. Time-stable and user-specific features are developed by stretching the signal, designing a convolutional neural network and performing a variation-stable approach with three score fusions. Two evalu…
In this paper, the biometric potential of eye movement and eye blinking for human recognition task is investigated. These modalities might be useful for specific biometric applications like driver authentication for law enforcement. For this purpose, a database of 22 subjects was build where eye mov…
This paper presents a novel method for extracting auditory steady state response (ASSR) signals from background electroencephalogram. 40-Hz ASSR signals are sensitive to subject's state of consciousness and can be used as a monitor for the depth of anaesthesia. The suggested method is a multilevel a…
Recently Electrocardiogram (ECG) has been proposed as a biometric modality which offers liveliness detection. The fact that ECG is a vital signal makes it challenging to work with as it is affected by physical and psychological changes. In realistic applications, this type of biometrics still needs…