17 accepted papers
In recent years, face-based authentication methods are gradually replacing traditional methods across various applications, offering enhanced security and user convenience. However, these methods are threatened by the continuously evolving DeepFake techniques. In this paper, a novel Visual Speaker A
Model extraction aims to steal a functionally similar copy from a machine learning as a service (MLaaS) API with minimal overhead, typically for illicit profit or as a precursor to further attacks, posing a significant threat to the MLaaS ecosystem. However, recent studies have shown that model extr…
This paper introduces a novel approach to Visual Forced Alignment (VFA), aiming to accurately synchronize utterances with corresponding lip movements, without relying on audio cues. We propose a novel VFA approach that integrates a local context-aware feature extractor and employs multitask learning…
With continuously evolving generative models and increasingly diverse face forgery products, there is a growing demand for DeepFake detectors with stronger generalization ability and robustness. Previous works mainly capture method-specific forgery artifacts in the training set, thus failing to gene…
Many speech enhancement (SE) approaches have been proposed to deal with cocktail party problem. Personalized speech enhancement (PSE) approaches improve SE performance by utilizing user enrollment speech. However, PSE requires users to record additional clean audio for registration, which can be red…
Fingerprints characterize deep neural networks that are deployed as black-boxes. To achieve copyright tracing and integrity verification, fingerprints are categorized into robust fingerprints and fragile fingerprints. Despite of their distinct motivations, we show that both kinds of neural network f…
Missing attribute values frequently affect data classification, reducing accuracy as most models rely on complete datasets. Imputing missing values is typically used to restore data completeness, which is essential for building models. The effectiveness of imputation significantly impacts the classi…
To trace the copyright of deep neural networks, an owner can embed its identity information into its model as a watermark. The capacity of the watermark quantify the maximal volume of information that can be verified from the watermarked model. Current studies on capacity focus on the ownership veri…
Lipreading has been rapidly developed recently with the help of large-scale datasets and large models. Despite the significant progress made, the performance of lipreading models still falls short when dealing with unseen speakers. Therefore, it is necessary to utilize the speaker’s videos for fine-…
Camera fingerprint links a picture to its camera sensor, which is widely applied in sensor device identification, social network tracing and forgery detection. However, such fingerprints are in high dimensionality and cost substantial memory and computing resources, limiting their uses in real-time…
Recent research has shown that lip-based speaker authentication system can achieve good authentication performance. However, with emerging deepfake technology, attackers can make high fidelity talking videos of a user, thus posing a great threat to these systems. Confronted with this threat, we prop…
Neural table-to-text generation approaches are data-hungry, limiting their adaption for low-resource real-world applications. Previous works mostly resort to Pre-trained Language Models (PLMs) to generate fluent summaries of a table. However, they often contain hallucinated contents due to the uncon…
With the development of deep learning, synthetic speech has become more and more realistic and easier to spoof Automatic Speaker Verification (ASV) devices. Based on mining more effective hand-crafted features and proposing more powerful networks, many algorithms have been proposed to detect this ma…
Recently, prompt tuning has shown remarkable performance as a new learning paradigm, which freezes pre-trained language models (PLMs) and only tunes some soft prompts. A fixed PLM only needs to be loaded with different prompts to adapt different downstream tasks. However, the prompts associated with…
Anomaly detection in multivariate time series data is challenging due to complex temporal and feature correlations. This paper proposes a novel unsupervised multi-scale stacked spatial-temporal graph attention network for multivariate time series anomaly detection (STGAT-MAD). The core of our framew…
Current state-of-the-art approaches for lip reading are based on sequence-to-sequence architectures that are designed for natural machine translation and audio speech recognition. Hence, these methods do not fully exploit the characteristics of the lip dynamics, causing two main drawbacks. First, th…
Detecting double MPEG compression is of prime significance in video forensics. However, existing methods are effective only when the primary compression and the secondary compression have different quantiser scales (QS). There is a lack of effective methods dealing with double MPEG compression with…