Action visual tempo characterizes the dynamics and the temporal scale of an action, which is
helpful to distinguish human actions that share high similarities in visual dynamics and …

Recognizing human actions in dark videos is a useful yet challenging visual task in reality.
Existing augmentation-based methods separate action recognition and dark enhancement …

Learning-based image reconstruction models, such as those based on the U-Net, require a
large set of labeled images if good generalization is to be guaranteed. In some imaging …

In order to effectively extract the feature points of mobile network animation images and
accurately reflect the main content of the video, an optimization method to extract the feature …

Learning-based image reconstruction models, such as those based on the U-Net, require a
large set of labeled images if good generalization is to be guaranteed. In some imaging …

Due to the prohibitive cost as well as technical challenges in annotating ground-truth optical
flow for large-scale realistic video datasets, the existing deep learning models for optical …

Recently, video processing tasks, such as video enhancement and analysis, have received
increasing attention from both academics and industries. However, the current video …

This work proposes an intelligent video processing architecture for bandwidth-efficient edge-
cloud video streaming. On receiving the bandwidth-saving low-quality video streaming in …

Semantic segmentation aims at classifying image pixels according to given categories.
Deep learning approaches have proven to be very effective for this task. However …

In recent years, many deep learning-based methods have been proposed to tackle the
problem of optical flow estimation and achieved promising results. However, they hardly …