Action Segmentation
72 papers with code • 9 benchmarks • 16 datasets
Action Segmentation is a challenging problem in high-level video understanding. In its simplest form, Action Segmentation aims to segment a temporally untrimmed video by time and label each segmented part with one of pre-defined action labels. The results of Action Segmentation can be further used as input to various applications, such as video-to-text and action localization.
Source: TricorNet: A Hybrid Temporal Convolutional and Recurrent Network for Video Action Segmentation
Benchmarks
These leaderboards are used to track progress in Action Segmentation
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Libraries
Use these libraries to find Action Segmentation models and implementationsDatasets
Breakfast
GTEA
JIGSAWS
COIN
Assembly101
Watch-n-Patch
TUM Kitchen
Subtasks
Most implemented papers
Temporal Action Segmentation: An Analysis of Modern Techniques
Temporal action segmentation (TAS) in videos aims at densely identifying video frames in minutes-long videos with multiple action classes.
Temporal Convolutional Networks: A Unified Approach to Action Segmentation
The dominant paradigm for video-based action segmentation is composed of two steps: first, for each frame, compute low-level features using Dense Trajectories or a Convolutional Neural Network that encode spatiotemporal information locally, and second, input these features into a classifier that captures high-level temporal relationships, such as a Recurrent Neural Network (RNN).
Weakly Supervised Action Learning with RNN based Fine-to-coarse Modeling
We present an approach for weakly supervised learning of human actions.
Action Sets: Weakly Supervised Action Segmentation without Ordering Constraints
alexanderrichard/action-sets
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CVPR 2018
Action detection and temporal segmentation of actions in videos are topics of increasing interest.
Temporal Human Action Segmentation via Dynamic Clustering
We present an effective dynamic clustering algorithm for the task of temporal human action segmentation, which has comprehensive applications such as robotics, motion analysis, and patient monitoring.
Actor and Action Video Segmentation from a Sentence
This paper strives for pixel-level segmentation of actors and their actions in video content.
Weakly-Supervised Action Segmentation with Iterative Soft Boundary Assignment
ld-ing/TCFPN-ISBA
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CVPR 2018
In this work, we address the task of weakly-supervised human action segmentation in long, untrimmed videos.
Deep Reinforcement Learning for Surgical Gesture Segmentation and Classification
Finspire13/RL-Surgical-Gesture-Segmentation
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Recognition of surgical gesture is crucial for surgical skill assessment and efficient surgery training.
Toward Ergonomic Risk Prediction via Segmentation of Indoor Object Manipulation Actions Using Spatiotemporal Convolutional Networks
BehnooshParsa/HumanActionRecognition_with_ErgonomicRisk
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Automated real-time prediction of the ergonomic risks of manipulating objects is a key unsolved challenge in developing effective human-robot collaboration systems for logistics and manufacturing applications.
Fast Weakly Supervised Action Segmentation Using Mutual Consistency
Action segmentation is the task of predicting the actions for each frame of a video.
