Group Activity Recognition
14 papers with code • 2 benchmarks • 2 datasets
Group Activity Recognition is a subset of human activity recognition problem which focuses on the collective behavior of a group of people, resulted from the individual actions of the persons and their interactions. Collective activity recognition is a basic task for automatic human behavior analysis in many areas like surveillance or sports videos.
Source: A Multi-Stream Convolutional Neural Network Framework for Group Activity Recognition
Benchmarks
These leaderboards are used to track progress in Group Activity Recognition
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
Volleyball
Collective Activity
Most implemented papers
Revisiting Skeleton-based Action Recognition
open-mmlab/mmaction2
•
•
CVPR 2022
In this work, we propose PoseC3D, a new approach to skeleton-based action recognition, which relies on a 3D heatmap stack instead of a graph sequence as the base representation of human skeletons.
Learning Actor Relation Graphs for Group Activity Recognition
wjchaoGit/Group-Activity-Recognition
•
•
CVPR 2019
To this end, we propose to build a flexible and efficient Actor Relation Graph (ARG) to simultaneously capture the appearance and position relation between actors.
Spatio-Temporal Dynamic Inference Network for Group Activity Recognition
jacobyuan7/din_gar
•
•
ICCV 2021
Within each interaction field, we apply DR to predict the relation matrix and DW to predict the dynamic walk offsets in a joint-processing manner, thus forming a person-specific interaction graph.
A Hierarchical Deep Temporal Model for Group Activity Recognition
In group activity recognition, the temporal dynamics of the whole activity can be inferred based on the dynamics of the individual people representing the activity.
Hierarchical Deep Temporal Models for Group Activity Recognition
In order to model both person-level and group-level dynamics, we present a 2-stage deep temporal model for the group activity recognition problem.
SBGAR: Semantics Based Group Activity Recognition
Activity recognition has become an important function in many emerging computer vision applications e. g. automatic video surveillance system, human-computer interaction application, and video recommendation system, etc.
Hierarchical Relational Networks for Group Activity Recognition and Retrieval
Second, we propose a Relational Autoencoder model for unsupervised learning of features for action and scene retrieval.
Improved Actor Relation Graph based Group Activity Recognition
kuangzijian/Improved-Actor-Relation-Graph-based-Group-Activity-Recognition
•
•
We propose to use Normalized cross-correlation (NCC) and the sum of absolute differences (SAD) to calculate the pair-wise appearance similarity and build the actor relationship graph to allow the graph convolution network to learn how to classify group activities.
Learning Group Activities from Skeletons without Individual Action Labels
fabiozappo/SkeletonGroupActivityRecognition
•
•
To understand human behavior we must not just recognize individual actions but model possibly complex group activity and interactions.
Group Activity Recognition Using Joint Learning of Individual Action Recognition and People Grouping
This paper proposes joint learning of individual action recognition and people grouping for improving group activity recognition.
