Recently, generative adversarial networks (GANs) have progressed enormously, which
makes them able to learn complex data distributions in particular faces. More and more …

Unsupervised domain adaptation has attracted growing research attention on semantic
segmentation. However, 1) most existing models cannot be directly applied into lesions …

Unsupervised domain adaptation without consuming annotation process for unlabeled
target data attracts appealing interests in semantic segmentation. However, 1) existing …

IoT sensors are becoming increasingly important supplement to traditional monitoring
systems, particularly for in-situ based monitoring. Data collected using IoT sensors are often …

Face synthesis based on attribute words is a novel and challenging topic in computer vision,
which has various application potentials in public security and multimedia. Existing attribute …

Weakly-supervised learning has attracted growing research attention on medical lesions
segmentation due to significant saving in pixel-level annotation cost. However, 1) most …

As face editing scenarios have become popular, the face inpainting technique has become
a hot topic. Although some existing methods can inpaint faces with preserved identity …

Pose variation and occlusion are two key factors that affect the accuracy of face recognition.
Most of the previous work alleviate the impacts of pose and occlusion by performing the …

Blind face inpainting refers to the task of reconstructing visual contents without explicitly
indicating the corrupted regions in a face image. Inherently, this task faces two …

In this paper, we propose a Mask-Robust Inpainting Network (MRIN) approach to recover
the masked areas of an image. Most existing methods learn a single model for image …