% Key papers for Domain-adaptive segmentation (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2019_learning_14416,
  title = {{Learning Semantic Segmentation From Synthetic Data: A Geometrically Guided Input-Output Adaptation Approach}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2021_dannet_16783,
  title = {{DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2020_mseg_15865,
  title = {{MSeg: A Composite Dataset for Multi-Domain Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{neurips2021_loveda_62662,
  title = {{LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://openreview.net/forum?id=bLBIbVaGDu},
}

@inproceedings{cvpr2019_advent_13804,
  title = {{ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2022_bending_18354,
  title = {{Bending Reality: Distortion-Aware Transformers for Adapting to Panoramic Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2024_stronger_24899,
  title = {{Stronger Fewer \& Superior: Harnessing Vision Foundation Models for Domain Generalized Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29296},
}

@inproceedings{neurips2020_pixel_60584,
  title = {{Pixel-Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17441},
}

@inproceedings{cvpr2020_cross_15307,
  title = {{Cross-Domain Semantic Segmentation via Domain-Invariant Interactive Relation Transfer}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2023_hgformer_21115,
  title = {{HGFormer: Hierarchical Grouping Transformer for Domain Generalized Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22177},
}

@inproceedings{aaai2024_learning_6441,
  title = {{Learning Content-Enhanced Mask Transformer for Domain Generalized Urban-Scene Segmentation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27840},
}

@inproceedings{cvpr2021_cross_16773,
  title = {{Cross-View Regularization for Domain Adaptive Panoptic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2021_darcnn_16785,
  title = {{DARCNN: Domain Adaptive Region-Based Convolutional Neural Network for Unsupervised Instance Segmentation in Biomedical Images}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2024_collaborating_22991,
  title = {{Collaborating Foundation Models for Domain Generalized Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30656},
}

@inproceedings{cvpr2022_learning_19200,
  title = {{Learning Part Segmentation Through Unsupervised Domain Adaptation From Synthetic Vehicles}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2024_goodsam_23636,
  title = {{GoodSAM: Bridging Domain and Capacity Gaps via Segment Anything Model for Distortion-aware Panoramic Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30047},
}

@inproceedings{cvpr2024_segment_24772,
  title = {{Segment Any Event Streams via Weighted Adaptation of Pivotal Tokens}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30311},
}

@inproceedings{cvpr2024_flattening_23482,
  title = {{Flattening the Parent Bias: Hierarchical Semantic Segmentation in the Poincare Ball}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31551},
}

@inproceedings{aaai2023_exploit_3610,
  title = {{Exploit Domain-Robust Optical Flow in Domain Adaptive Video Semantic Segmentation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25140},
}

@inproceedings{neurips2024_generalize_73343,
  title = {{Generalize or Detect? Towards Robust Semantic Segmentation Under Multiple Distribution Shifts}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94102},
}

@inproceedings{aaai2025_s2s2_10586,
  title = {{S2S2: Semantic Stacking for Robust Semantic Segmentation in Medical Imaging}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32678},
}

@inproceedings{aaai2025_the_10983,
  title = {{The Parables of the Mustard Seed and the Yeast: Extremely Low-Budget, High-Performance Nighttime Semantic Segmentation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32846},
}

@inproceedings{aaai2025_erf_8878,
  title = {{ERF: A Benchmark Dataset for Robust Semantic Segmentation Under Extreme Rainfall Conditions}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33007},
}

@inproceedings{iclr2024_diving_34162,
  title = {{Diving Segmentation Model into Pixels}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18913},
}

@inproceedings{icml2025_better_48334,
  title = {{Better to Teach than to Give: Domain Generalized Semantic Segmentation via Agent Queries with Diffusion Model Guidance}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44281},
}

@inproceedings{neurips2026_sparse_94762,
  title = {{Sparse All-Layer Connector for Domain Generalised Semantic Segmentation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153049},
}