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.
Authors
- Tsuyoshi Okita (ORCID: https://orcid.org/0000-0002-1286-5496)
- Kosuke Ukita (ORCID: https://orcid.org/0009-0008-3325-1363)
Institutions
- Kyushu Institute of Technology (JP)
- Kyushu Art Institute of Technology (JP)
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