Mitigating Generation Shifts for Generalized Zero-Shot Learning-Reference-Cited by-同舟云学术

Mitigating Generation Shifts for Generalized Zero-Shot Learning

Published:2021-10-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 29th ACM International Conference on Multimedia
language:
Short-container-title:

Author:

Chen Zhi¹,Luo Yadan¹,Wang Sen¹,Qiu Ruihong¹,Li Jingjing²,Huang Zi¹

Affiliation:

1. The University of Queensland, Brisbane, QLD, Australia

2. University of Electronic Science and Technology of China, Chengdu, China

Funder

Australian Research Council

Sichuan Science and Technology Program

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3474085.3475258

Reference52 articles.

1. 2015. Label-embedding for image classification;Akata Z.;TPAMI,2015

2. Z. Akata S. Reed D. Walter H. Lee and B. Schiele. 2015. Evaluation of output embeddings for fine-grained image classification. In CVPR. 2927--2936. Z. Akata S. Reed D. Walter H. Lee and B. Schiele. 2015. Evaluation of output embeddings for fine-grained image classification. In CVPR. 2927--2936.

3. L. Ardizzone J. Kruse S. Wirkert D. Rahner E. W. Pellegrini R. S. Klessen L. Maier-Hein C. Rother and U. Köthe. 2018. Analyzing inverse problems with invertible neural networks. arXiv preprint arXiv:1808.04730 (2018). L. Ardizzone J. Kruse S. Wirkert D. Rahner E. W. Pellegrini R. S. Klessen L. Maier-Hein C. Rother and U. Köthe. 2018. Analyzing inverse problems with invertible neural networks. arXiv preprint arXiv:1808.04730 (2018).

4. L. Ardizzone C. Lüth J. Kruse C. Rother and U. Köthe. 2019. Guided image gener-ation with conditional invertible neural networks. arXiv preprint arXiv:1907.02392 (2019). L. Ardizzone C. Lüth J. Kruse C. Rother and U. Köthe. 2019. Guided image gener-ation with conditional invertible neural networks. arXiv preprint arXiv:1907.02392 (2019).

5. M. Arjovsky S. Chintala and L. Bottou. 2017. Wasserstein generative adversarial networks. In ICML. 214--223. M. Arjovsky S. Chintala and L. Bottou. 2017. Wasserstein generative adversarial networks. In ICML. 214--223.

Cited by 15 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. MLTU: mixup long-tail unsupervised zero-shot image classification on vision-language models;Multimedia Systems;2024-06

2. Multimodal few-shot classification without attribute embedding;EURASIP Journal on Image and Video Processing;2024-01-10

3. A Progressive Placeholder Learning Network for Multimodal Zero-Shot Learning;IEEE Transactions on Multimedia;2024

4. ZS-VAT: Learning Unbiased Attribute Knowledge for Zero-Shot Recognition Through Visual Attribute Transformer;IEEE Transactions on Neural Networks and Learning Systems;2024

5. Complex Scenario Image Retrieval via Deep Similarity-aware Hashing;ACM Transactions on Multimedia Computing, Communications, and Applications;2023-12-11