Semantic-Aware Generator and Low-level Feature Augmentation for Few-shot Image Generation

Author:

Wang Zhe1ORCID,Guan Jiaoyan1ORCID,Yang Mengping1ORCID,Xiao Ting2ORCID,Chi Ziqiu2ORCID

Affiliation:

1. Key Laboratory of Smart Manufacturing in Energy Chemical Process, Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, China

2. Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, China

Funder

Shanghai Science and Technology Program

Natural Science Foundation of China

Publisher

ACM

Reference58 articles.

1. Antreas Antoniou , Amos Storkey , and Harrison Edwards . 2017. Data augmentation generative adversarial networks. arXiv preprint arXiv:1711.04340 ( 2017 ). Antreas Antoniou, Amos Storkey, and Harrison Edwards. 2017. Data augmentation generative adversarial networks. arXiv preprint arXiv:1711.04340 (2017).

2. Sergey Bartunov and Dmitry Vetrov . 2018 . Few-shot generative modelling with generative matching networks . In International Conference on Artificial Intelligence and Statistics. PMLR, 670--678 . Sergey Bartunov and Dmitry Vetrov. 2018. Few-shot generative modelling with generative matching networks. In International Conference on Artificial Intelligence and Statistics. PMLR, 670--678.

3. Functional somatic disorders: discussion paper for a new common classification for research and clinical use

4. VGGFace2: A Dataset for Recognising Faces across Pose and Age

5. Louis Clouâtre and Marc Demers . 2019 . Figr: Few-shot image generation with reptile. arXiv preprint arXiv:1901.02199 (2019). Louis Clouâtre and Marc Demers. 2019. Figr: Few-shot image generation with reptile. arXiv preprint arXiv:1901.02199 (2019).

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