Human action recognition (HAR) refers to the process in which computers analyze and
process video data to obtain the categories of action presented in the video. It has a wide …

Recent years have witnessed a growing interest in compressed video action recognition due
to the rapid growth of online videos. It remarkably reduces the storage by replacing raw …

Human pose estimation from videos has many real-world applications. Existing methods
focus on applying models with a uniform computation profile on fully de-coded frames …

Compressed video action recognition has recently drawn growing attention, since it
remarkably reduces the storage and computational cost via replacing raw videos by …

Video semantic segmentation (VSS) is a computationally expensive task due to the per-
frame prediction for videos of high frame rates. In recent work, compact models or adaptive …

Compressed video action recognition offers the advantage of reducing decoding and
inference time compared to the RGB domain. However, the compressed domain poses …

Modeling and recognizing video activities from videos are key parts of many promising
applications such as visual surveillance, human–computer interaction, and video …

Compressed videos offer a compelling alternative to raw videos, showing the possibility to
significantly reduce the on-line computational and storage cost. However, current …

Recent methods including CoViAR and DMC-Net provide a new paradigm for action
recognition since they are directly targeted at compressed videos (eg, MPEG4 files). It …

In recent years, action recognition has become a popular and challenging task in computer
vision. Nowadays, two-stream networks with appearance stream and motion stream can …