2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDMLR-APPL-IVASR-6.1
Paper Title LIFELONG TWIN GENERATIVE ADVERSARIAL NETWORKS
Authors Fei Ye, Adrian Bors, University of York, United Kingdom
SessionMLR-APPL-IVASR-6: Machine learning for image and video analysis, synthesis, and retrieval 6
LocationArea D
Session Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Poster
Topic Applications of Machine Learning: Machine learning for image & video analysis, synthesis, and retrieval
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract In this paper, we propose a new continuously learning generative model, called the Lifelong Twin Generative Adversarial Networks (LT-GANs). LT-GANs learns a sequence of tasks from several databases and its architecture consists of three components: two identical generators, namely the Teacher and Assistant, and one Discriminator. In order to allow for the LT-GANs to learn new concepts without forgetting, we introduce a new lifelong training approach, namely Lifelong Adversarial Knowledge Distillation (LAKD), which encourages the Teacher and Assistant to alternately teach each other, while learning a new database. This training approach favours transferring knowledge from a more knowledgeable player to another player which knows less information about a previously given task.