Camouflaged object detection (COD) aims to identify objects that are perfectly embedded in
their environment, which has various downstream applications in fields such as medicine …

Attention mechanism, especially channel attention, has gained great success in the
computer vision field. Many works focus on how to design efficient channel attention …

Face forgery detection is raising ever-increasing interest in computer vision since facial
manipulation technologies cause serious worries. Though recent works have reached …

Deep neural networks have achieved remarkable success in computer vision tasks. Existing
neural networks mainly operate in the spatial domain with fixed input sizes. For practical …

Image reconstruction and synthesis have witnessed remarkable progress thanks to the
development of generative models. Nonetheless, gaps could still exist between the real and …

Camouflaged object detection (COD) aims to accurately detect objects hidden in the
surrounding environment. However, the existing COD methods mainly locate camouflaged …

Video self-supervised learning is a challenging task, which requires significant expressive
power from the model to leverage rich spatial-temporal knowledge and generate effective …

Recent style transfer models have provided promising artistic results. However, given a
photograph as a reference style, existing methods are limited by spatial distortions or …

Before we start thinking about (deep) generative modeling, let us consider a simple
example. Imagine we have trained a deep neural network that classifies images (x∈ ℤ D) of …

Few-shot classification aims to learn a discriminative feature representation to recognize
unseen classes with few labeled support samples. While most few-shot learning methods …