Bilateral Knowledge Distillation for Unsupervised Domain Adaptation of Semantic Segmentation-Reference-Cited by-同舟云学术

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Bilateral Knowledge Distillation for Unsupervised Domain Adaptation of Semantic Segmentation

Published:2022-10-23 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
language:
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Author:

Wang Yunnan¹,Li Jianxun¹

Affiliation:

1. Shanghai Jiao Tong University,Department of Automation,China

Funder

National Natural Science Foundation

National Key Research and Development Program

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9981026/9981028/09981567.pdf?arnumber=9981567

Reference38 articles.

1. Semantic Segmentation Using a GAN and a Weakly Supervised Method Based on Deep Transfer Learning

2. Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation

3. Generative adversarial nets;goodfellow;Advances in Neural IInformation Processing Systems,2014

4. Multi-Source Domain Adaptation with Collaborative Learning for Semantic Segmentation

5. Unsupervised Domain Adaptation Using Generative Adversarial Networks for Semantic Segmentation of Aerial Images

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1. Energy-Based Domain-Adaptive Segmentation With Depth Guidance;IEEE Robotics and Automation Letters;2024-08

2. Test-Time Adaptation for Point Cloud Upsampling Using Meta-Learning;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01

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