RGB-D-based action recognition datasets: A survey
Human action recognition from RGB-D (Red, Green, Blue and Depth) data has attracted
increasing attention since the first work reported in 2010. Over this period, many benchmark …
increasing attention since the first work reported in 2010. Over this period, many benchmark …
[HTML][HTML] Deep learning and transfer learning for device-free human activity recognition: A survey
Device-free activity recognition plays a crucial role in smart building, security, and human–
computer interaction, which shows its strength in its convenience and cost-efficiency …
computer interaction, which shows its strength in its convenience and cost-efficiency …
A comprehensive study of deep video action recognition
Video action recognition is one of the representative tasks for video understanding. Over the
last decade, we have witnessed great advancements in video action recognition thanks to …
last decade, we have witnessed great advancements in video action recognition thanks to …
RGB-D-based human motion recognition with deep learning: A survey
Human motion recognition is one of the most important branches of human-centered
research activities. In recent years, motion recognition based on RGB-D data has attracted …
research activities. In recent years, motion recognition based on RGB-D data has attracted …
Learning cross-modal contrastive features for video domain adaptation
Learning transferable and domain adaptive feature representations from videos is important
for video-relevant tasks such as action recognition. Existing video domain adaptation …
for video-relevant tasks such as action recognition. Existing video domain adaptation …
Temporal attentive alignment for large-scale video domain adaptation
Although various image-based domain adaptation (DA) techniques have been proposed in
recent years, domain shift in videos is still not well-explored. Most previous works only …
recent years, domain shift in videos is still not well-explored. Most previous works only …
Action segmentation with joint self-supervised temporal domain adaptation
Despite the recent progress of fully-supervised action segmentation techniques, the
performance is still not fully satisfactory. One main challenge is the problem of …
performance is still not fully satisfactory. One main challenge is the problem of …
Spatio-temporal saliency networks for dynamic saliency prediction
C Bak, A Kocak, E Erdem… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Computational saliency models for still images have gained significant popularity in recent
years. Saliency prediction from videos, on the other hand, has received relatively little …
years. Saliency prediction from videos, on the other hand, has received relatively little …
Dual-head contrastive domain adaptation for video action recognition
Unsupervised domain adaptation (UDA) methods have become very popular in computer
vision. However, while several techniques have been proposed for images, much less …
vision. However, while several techniques have been proposed for images, much less …
Video saliency forecasting transformer
Video saliency prediction (VSP) aims to imitate eye fixations of humans. However, the
potential of this task has not been fully exploited since existing VSP methods only focus on …
potential of this task has not been fully exploited since existing VSP methods only focus on …