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 …
Actionformer: Localizing moments of actions with transformers
Self-attention based Transformer models have demonstrated impressive results for image
classification and object detection, and more recently for video understanding. Inspired by …
classification and object detection, and more recently for video understanding. Inspired by …
Tridet: Temporal action detection with relative boundary modeling
In this paper, we present a one-stage framework TriDet for temporal action detection.
Existing methods often suffer from imprecise boundary predictions due to the ambiguous …
Existing methods often suffer from imprecise boundary predictions due to the ambiguous …
Learning salient boundary feature for anchor-free temporal action localization
Temporal action localization is an important yet challenging task in video understanding.
Typically, such a task aims at inferring both the action category and localization of the start …
Typically, such a task aims at inferring both the action category and localization of the start …
TN-ZSTAD: Transferable network for zero-shot temporal activity detection
An integral part of video analysis and surveillance is temporal activity detection, which
means to simultaneously recognize and localize activities in long untrimmed videos …
means to simultaneously recognize and localize activities in long untrimmed videos …
G-tad: Sub-graph localization for temporal action detection
Temporal action detection is a fundamental yet challenging task in video understanding.
Video context is a critical cue to effectively detect actions, but current works mainly focus on …
Video context is a critical cue to effectively detect actions, but current works mainly focus on …
End-to-end temporal action detection with transformer
Temporal action detection (TAD) aims to determine the semantic label and the temporal
interval of every action instance in an untrimmed video. It is a fundamental and challenging …
interval of every action instance in an untrimmed video. It is a fundamental and challenging …
Asm-loc: Action-aware segment modeling for weakly-supervised temporal action localization
Weakly-supervised temporal action localization aims to recognize and localize action
segments in untrimmed videos given only video-level action labels for training. Without the …
segments in untrimmed videos given only video-level action labels for training. Without the …
Ms-tcn++: Multi-stage temporal convolutional network for action segmentation
With the success of deep learning in classifying short trimmed videos, more attention has
been focused on temporally segmenting and classifying activities in long untrimmed videos …
been focused on temporally segmenting and classifying activities in long untrimmed videos …
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 …