Give Me Your Trained Model: Domain Adaptive Semantic Segmentation without Source Data

By Yuxi Wang, Jian Liang, Zhaoxiang Zhang. 2021

9 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Representation & Self-Supervised Learning

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Luc Van Gool
2. Jitendra Malik
3. Ming-Hsuan Yang
4. Vladlen Koltun
5. Dacheng Tao
6. Xiaogang Wang
7. Trevor Darrell
8. Andrea Vedaldi

In Representation & Self-Supervised Learning

1. Serge J. Belongie
2. Vladlen Koltun
3. Boyi Li
4. René Ranftl
5. Kilian Q. Weinberger
6. Andreas Holzinger
7. Jia Deng
8. Gabriella Csurka

Citations in the corpus

• Language-driven Semantic Segmentation (2022, background): “Finally, a different line of work explores cross-domain adaptation methods for semantic segmentation by using feature alignment, self-training, and information propagation strategies (Yang et al., 2021; Wang et al., 2021).”