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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 41–50 of 65 papers

TitleStatusHype
Relevance Topic Model for Unstructured Social Group Activity Recognition—0
Self-supervised Multi-actor Social Activity Understanding in Streaming Videos—0
Skeleton-based Relational Reasoning for Group Activity Analysis—0
Social Adaptive Module for Weakly-supervised Group Activity Recognition—0
SoGAR: Self-supervised Spatiotemporal Attention-based Social Group Activity Recognition—0
stagNet: An Attentive Semantic RNN for Group Activity Recognition—0
Structure Inference Machines: Recurrent Neural Networks for Analyzing Relations in Group Activity Recognition—0
Learning Ensembles of Potential Functions for Structured Prediction With Latent Variables—0
ActivityCLIP: Enhancing Group Activity Recognition by Mining Complementary Information from Text to Supplement Image Modality—0
Actor-Transformers for Group Activity Recognition—0
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