Analysis of Human Activity Recognition by Diffusion Models

This paper proposes a classifier based on a diffusion model for human activity recognition. To this end, we introduce three architectures: (1) the representation-conditional diffusion transformer, (2) the first classifier, RepcondFormer, and (3) the second classifier, RepcondClassifier. Experimental results show that RepcondFormer outperforms in three datasets, while RepcondClassifier performs better in one dataset when fine-tuned.

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Publication Details

Published
2024-09-22
DOI
https://doi.org/10.1145/3675094.3678439
Citations
1
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
Field-Weighted Citation Impact
0.25
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article

Analysis of Human Activity Recognition by Diffusion Models

Tsuyoshi Okita, Kosuke Ukita
1 citations
Context-Aware Activity Recognition Systems
0.25
article

Analysis of Human Activity Recognition by Diffusion Models

Tsuyoshi Okita, Kosuke Ukita
article en
1 citations

Abstract

This paper proposes a classifier based on a diffusion model for human activity recognition. To this end, we introduce three architectures: (1) the representation-conditional diffusion transformer, (2) the first classifier, RepcondFormer, and (3) the second classifier, RepcondClassifier. Experimental results show that RepcondFormer outperforms in three datasets, while RepcondClassifier performs better in one dataset when fine-tuned.

Kyushu Institute of Technology (JP), Kyushu Art Institute of Technology (JP)
Openalex Percentile: Top 47%
Context-Aware Activity Recognition Systems
0.25
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