Yiting Wang

• University of Warwick

Low-light images often suffer from limited visibility and multiple types of degradation, rendering low-light image enhancement (LIE) a non-trivial task. Some endeavors have been made to enhance low-light images using convolutional neural networks (CNNs). However, they have low efficiency in learning the structural information and diverse illuminati...

Precise scene understanding based on perception sensors' data is important for assisted and automated driving (AAD) functions, to enable accurate decision-making processes and safe navigation. Among various perception tasks using camera images (e.g. object detection, semantic segmentation), panoptic segmentation shows promising scene understanding...

Assisted and automated driving functions in vehicles exploit sensor data to build situational awareness, however, the data amount required by these functions might exceed the bandwidth of current wired vehicle communication networks. Consequently, sensor data reduction, and automotive camera video compression need investigation. However, convention...

p>This letter introduces an attention-based unsupervised generative adversarial network, named Illu-GAN, for low- light camera image enhancement. Many images captured by camera sensors suffer from inadequate lighting conditions or over-/under- exposure. Previous low-light enhancement methods are mostly based on supervised learning-based and heavily...

Since 2021, the term "Metaverse" has been the most popular one, garnering a lot of interest. Because of its contained environment and built-in computing and networking capabilities, a modern car makes an intriguing location to host its own little metaverse. Additionally, the travellers don't have much to do to pass the time while traveling, making...

It has become a research hotspot to detect whether a video is natural or DeepFake. However, almost all the existing works focus on detecting the inconsistency in either spatial or temporal. In this paper, a dual-branch (spatial branch and temporal branch) neural network is proposed to detect the inconsistency in both spatial and temporal for DeepFa...

With the development of face image synthesis and generation technology based on generative adversarial networks (GANs), it has become a research hotspot to determine whether a given face image is natural or generated. However, the generalization capability of the existing algorithms is still to be improved. Therefore, this paper proposes a general...

Liu and Pun proposed a method based on fully convolutional network (FCN) and conditional random field (CRF) to locate spliced regions in synthesized images from different source images. However, their work has two drawbacks: (a) FCN often smooths detailed structures and ignores small objects; (b) CRF is employed as a standalone post-processing step...