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Group Activity Recognition

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

Papers

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Showing 51–65 of 65 papers

TitleStatusHype
A Multi-Stream Convolutional Neural Network Framework for Group Activity Recognition—0
Multi-Level Sequence GAN for Group Activity Recognition—0
stagNet: An Attentive Semantic RNN for Group Activity Recognition—0
Hierarchical Relational Networks for Group Activity Recognition and RetrievalCode0
SBGAR: Semantics Based Group Activity RecognitionCode0
Recurrent Modeling of Interaction Context for Collective Activity Recognition—0
CERN: Confidence-Energy Recurrent Network for Group Activity Recognition—0
Hierarchical Deep Temporal Models for Group Activity RecognitionCode0
Learning Ensembles of Potential Functions for Structured Prediction With Latent Variables—0
A Hierarchical Deep Temporal Model for Group Activity RecognitionCode0
Structure Inference Machines: Recurrent Neural Networks for Analyzing Relations in Group Activity Recognition—0
Deep Structured Models For Group Activity Recognition—0
A Heat-Map-based Algorithm for Recognizing Group Activities in Videos—0
A new network-based algorithm for human activity recognition in video—0
Relevance Topic Model for Unstructured Social Group Activity Recognition—0
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