Gliomas are one of the most prevalent types of primary brain tumors, accounting for more
than 30% of all cases and they develop from the glial stem or progenitor cells. In theory, the …

In this paper, we present DRANet, a network architecture that disentangles image
representations and transfers the visual attributes in a latent space for unsupervised cross …

Underwater image suffer from color cast, low contrast and hazy effect, which degraded the
high-level vision application. Recent learning-based methods demonstrate astonishing …

Unpaired image-to-image translation problem aims to model the map** from one domain
to another with unpaired training data. Current works like the well-acknowledged Cycle GAN …

Meaningful and simplified representations of neural activity can yield insights into how and
what information is being processed within a neural circuit. However, without labels, finding …

Image segmentation is a long-standing problem in medical image analysis to facilitate the
clinical diagnosis and intervention. Progress has been made due to deep learning via …

Style transfer has been an important topic both in computer vision and graphics. Since the
seminal work of Gatys et al. first demonstrates the power of stylization through optimization …

Numerous valuable efforts have been devoted to achieving arbitrary style transfer since the
seminal work of Gatys et al. However, existing state-of-the-art approaches often generate …

We consider the problem of generating plausible and diverse video sequences, when we
are only given a start and an end frame. This task is also known as inbetweening, and it …

Traffic sign identification using camera images from vehicles plays a critical role in
autonomous driving and path planning. However, the front camera images can be distorted …