Quality assessment of in-the-wild videos is a challenging problem because of the absence
of reference videos and shooting distortions. Knowledge of the human visual system can …

Smartphones and other consumer devices capable of capturing video content and sharing it
on social media in nearly real time are widely available at a reasonable cost. Thus, there is a …

Video quality assessment (VQA) is an important problem in computer vision. The videos in
computer vision applications are usually captured in the wild. We focus on automatically …

Due to the wide range of different natural temporal and spatial distortions appearing in user
generated video content, blind assessment of natural video quality is a challenging research …

In this paper, we propose a deep neural network-based no-reference (NR) video quality
assessment (VQA) method with spatiotemporal feature fusion and hierarchical information …

A general-purpose no-reference video quality assessment algorithm based on a long short-
term memory (LSTM) network and a pretrained convolutional neural network (CNN) is …

Video quality assessment (VQA) is an important element of various applications ranging
from automatic video streaming to display technology. Furthermore, visual quality …

With the constantly growing popularity of video-based services and applications, no-
reference video quality assessment (NR-VQA) has become a very hot research topic. Over …

Popularity of streaming services for gaming videos has increased tremendously over the last
years, eg Twitch and Youtube Gaming. Compared to classical video streaming applications …

Quality of experience (QoE) that serves as a direct evaluation of viewing experience from the
end users is of vital importance for network optimization, and should be constantly …