Vision transformers have recently shown strong global context modeling capabilities in
camouflaged object detection. However, they suffer from two major limitations: less effective …

Most polyp segmentation methods use CNNs as their backbone, leading to two key issues
when exchanging information between the encoder and decoder: 1) taking into account the …

We demonstrate that it is possible to perform face-related computer vision in the wild using
synthetic data alone. The community has long enjoyed the benefits of synthesizing training …

How to learn a universal facial representation that boosts all face analysis tasks This paper
takes one step toward this goal. In this paper, we study the transfer performance of pre …

Spotting camouflaged objects that are visually assimilated into the background is tricky for
both object detection algorithms and humans who are usually confused or cheated by the …

RGB-D salient object detection (SOD) aims to segment the most attractive objects in a pair of
cross-modal RGB and depth images. Currently, most existing RGB-D SOD methods focus on …

Current semantic change detection (SCD) methods face challenges in modeling temporal
correlations (TCs) between bitemporal semantic features and difference features. These …

With the comprehensive research conducted on various face analysis tasks, there is a
growing interest among researchers to develop a unified approach to face perception …

This paper probes intrinsic factors behind typical failure cases (eg spatial inconsistency and
boundary confusion) produced by the existing state-of-the-art method in face parsing. To …

As wearing face masks is becoming an embedded practice due to the COVID-19 pandemic,
facial expression recognition (FER) that takes face masks into account is now a problem that …