Deep learning-based action detection in untrimmed videos: A survey
Understanding human behavior and activity facilitates advancement of numerous real-world
applications, and is critical for video analysis. Despite the progress of action recognition …
applications, and is critical for video analysis. Despite the progress of action recognition …
Generative cooperative learning for unsupervised video anomaly detection
Video anomaly detection is well investigated in weakly supervised and one-class
classification (OCC) settings. However, unsupervised video anomaly detection is quite …
classification (OCC) settings. However, unsupervised video anomaly detection is quite …
Rescaling egocentric vision: Collection, pipeline and challenges for epic-kitchens-100
This paper introduces the pipeline to extend the largest dataset in egocentric vision, EPIC-
KITCHENS. The effort culminates in EPIC-KITCHENS-100, a collection of 100 hours, 20M …
KITCHENS. The effort culminates in EPIC-KITCHENS-100, a collection of 100 hours, 20M …
Human action recognition and prediction: A survey
Derived from rapid advances in computer vision and machine learning, video analysis tasks
have been moving from inferring the present state to predicting the future state. Vision-based …
have been moving from inferring the present state to predicting the future state. Vision-based …
Fine-grained temporal contrastive learning for weakly-supervised temporal action localization
We target at the task of weakly-supervised action localization (WSAL), where only video-
level action labels are available during model training. Despite the recent progress, existing …
level action labels are available during model training. Despite the recent progress, existing …
Cola: Weakly-supervised temporal action localization with snippet contrastive learning
Weakly-supervised temporal action localization (WS-TAL) aims to localize actions in
untrimmed videos with only video-level labels. Most existing models follow the" localization …
untrimmed videos with only video-level labels. Most existing models follow the" localization …
Revisiting anchor mechanisms for temporal action localization
Most of the current action localization methods follow an anchor-based pipeline: depicting
action instances by pre-defined anchors, learning to select the anchors closest to the ground …
action instances by pre-defined anchors, learning to select the anchors closest to the ground …
Overview of temporal action detection based on deep learning
K Hu, C Shen, T Wang, K Xu, Q **a, M **a… - Artificial Intelligence …, 2024 - Springer
Abstract Temporal Action Detection (TAD) aims to accurately capture each action interval in
an untrimmed video and to understand human actions. This paper comprehensively surveys …
an untrimmed video and to understand human actions. This paper comprehensively surveys …
Two-stream consensus network for weakly-supervised temporal action localization
Abstract Weakly-supervised Temporal Action Localization (W-TAL) aims to classify and
localize all action instances in an untrimmed video under only video-level supervision …
localize all action instances in an untrimmed video under only video-level supervision …
Claws: Clustering assisted weakly supervised learning with normalcy suppression for anomalous event detection
Learning to detect real-world anomalous events through video-level labels is a challenging
task due to the rare occurrence of anomalies as well as noise in the labels. In this work, we …
task due to the rare occurrence of anomalies as well as noise in the labels. In this work, we …