Discriminative and Robust Attribute Alignment for Zero-Shot Learning

Author:

Cheng De1ORCID,Wang Gerong2,Wang Nannan1ORCID,Zhang Dingwen3ORCID,Zhang Qiang4ORCID,Gao Xinbo5ORCID

Affiliation:

1. School of Telecommunications Engineering, Xidian University, Xi’an, China

2. Beijing Institute of Remote Sensing Equipment, Beijing, China

3. Hefei Comprehensive National Science Center, Institute of Artificial Intelligence, Hefei, China

4. School of Mechano-Electronic Engineering, Xidian University, Xi’an, China

5. College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Technology Innovation Leading Program of Shaanxi

Open Research Projects of Zhejiang Lab

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Media Technology

Reference83 articles.

1. Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results;tarvainen;Proc Adv Neural Inf Process Syst,2017

2. Recurrent Thrifty Attention Network for Remote Sensing Scene Recognition

3. Spherical Zero-Shot Learning

4. Motion stimulation for compositional action recognition;ma;IEEE Trans Circuits Syst Video Technol,2022

5. VGSE: Visually-Grounded Semantic Embeddings for Zero-Shot Learning

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