Semantic-aware auto-encoders for self-supervised representation learning
The resurgence of unsupervised learning can be attributed to the remarkable progress of self-supervised learning, which includes generative $(\mathcal{G})$ and discriminative $(\mathcal{D})$ models. In computer vision, the mainstream self-supervised learning algorithms are $\mathcal{D}$ models. Howe...
| Huvudupphovsmän: | , , , |
|---|---|
| Materialtyp: | Conference item |
| Språk: | English |
| Publicerad: |
IEEE
2022
|