Generative adversarial networks (GANs) have recently become a hot research topic;
however, they have been studied since 2014, and a large number of algorithms have been …

The Generative Models have gained considerable attention in unsupervised learning via a
new and practical framework called Generative Adversarial Networks (GAN) due to their …

Deep learning based methods have shown dramatic improvements in image rain removal
by using large-scale paired data of synthetic datasets. However, due to the various …

Improving the performance of face forgery detectors often requires more identity-swapped
images of higher-quality. One core objective of identity swap** is to generate identity …

Audio-visual learning, aimed at exploiting the relationship between audio and visual
modalities, has drawn considerable attention since deep learning started to be used …

Visible-infrared person re-identification (VI-ReID), which aims to search identities across
different spectra, is a challenging task due to large cross-modality discrepancy between …

Heterogeneous face recognition (HFR) refers to matching cross-domain faces and plays a
crucial role in public security. Nevertheless, HFR is confronted with challenges from large …

Face parsing has recently attracted increasing interest due to its numerous application
potentials, such as facial make up and facial image generation. In this paper, we make …

Face anti-spoofing (FAS) plays a vital role in preventing face recognition systems from
presentation attacks. Existing face anti-spoofing datasets lack diversity due to the insufficient …

Palmprint recently shows great potential in recognition applications as it is a privacy-friendly
and stable biometric. However, the lack of large-scale public palmprint datasets limits further …