Accident detection and public traffic safety is a crucial aspect of safe and better community.
Monitoring traffic flow in smart cities using different surveillance cameras plays a crucial role …

In recent years, underwater image enhancement methods based on deep learning have
achieved remarkable results. Since the images obtained in complex underwater scenarios …

With advances in data-driven machine learning research, a wide variety of prediction
models have been proposed to capture spatio-temporal features for the analysis of video …

Modeling spatiotemporal global dependencies and dynamics of body joints are crucial to
recognizing actions from 3D skeleton sequences. We propose a Relation-mining Self …

Deep learning technologies have shown their advantages in Single Image Rain Removal
(SIRR) tasks. However, the derained results of most methods are limited to some …

Using a Graph convolution network (GCN) for constructing and aggregating node features
has been helpful for skeleton-based action recognition. The strength of the nodes' relation of …

View change brings a significant challenge to action representation and recognition due to
pose occlusion and deformation. We propose a Global-Local Cross-View Fisher …

Human actions are sequential, and structured patterns of the body parts and their
movements. In this paper, we present a hybrid two-stream convolutional neural network …

Human feelings expressed through verbal (eg voice) and non-verbal communication
channels (eg face or body) can influence either human actions or interactions. In the …

Human–object interaction (HOI) detection aims to localize and classify triplets of human,
object and interaction from a given image. Earlier two-stage methods suffer both from …