With the acceleration of urbanization, traffic forecasting has become an...
Face Anti-Spoofing (FAS) aims to detect malicious attempts to invade a f...
Deepfake technologies empowered by deep learning are rapidly evolving,
c...
Synthetic realities are digital creations or augmentations that are
cont...
The out-of-distribution (OOD) problem generally arises when neural netwo...
Multimodal misinformation on online social platforms is becoming a criti...
Face Anti-Spoofing (FAS) is recently studied under the continual learnin...
Nowadays, forgery faces pose pressing security concerns over fake news,
...
Deep neural networks are likely to fail when the test data is corrupted ...
In this work, we tackle the problem of robust computed tomography (CT)
r...
This paper focuses on representation learning for dynamic graphs with
te...
Face presentation attacks (FPA), also known as face spoofing, have broug...
The image recapture attack is an effective image manipulation method to ...
Learning invariant representations via contrastive learning has seen
sta...
Filter pruning has been widely used for compressing convolutional neural...
Sarcasm is a linguistic phenomenon indicating a discrepancy between lite...
With the rapid progress over the past five years, face authentication ha...
Deep learning has achieved great success in the past few years. However,...
Domain generalization aims to improve the generalization capability of
m...
Face presentation attack detection (PAD) has been extensively studied by...
Attention mechanisms are dominating the explainability of deep models. T...
Face presentation attack detection (PAD) is an essential measure to prot...
Face Anti-Spoofing (FAS) is essential to secure face recognition systems...
The state-of-the-art deep neural networks are vulnerable to common
corru...
Learning the generalizable feature representation is critical for few-sh...
To enhance low-light images to normally-exposed ones is highly ill-posed...
Domain generalization aims to learn an invariant model that can generali...
The technological advancements of deep learning have enabled sophisticat...
Though convolutional neural networks are widely used in different tasks,...
Deep neural networks (DNN) have demonstrated unprecedented success for
m...
There has been an increasing consensus in learning based face anti-spoof...
Recently, we have witnessed great progress in the field of medical imagi...
Inspired by the philosophy employed by human beings to determine whether...
Deep neural networks (DNN) have shown great success in many computer vis...
One of the main drawbacks of deep Convolutional Neural Networks (DCNN) i...
Quality assessment driven by machine learning generally relies on the st...
Face images captured through the glass are usually contaminated by
refle...
Most existing person re-identification (Re-ID) approaches follow a super...