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

@inproceedings{cvpr2021_datasetgan_16801,
  title = {{DatasetGAN: Efficient Labeled Data Factory With Minimal Human Effort}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2022_bigdatasetgan_18366,
  title = {{BigDatasetGAN: Synthesizing ImageNet With Pixel-Wise Annotations}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2022_noisy_19462,
  title = {{Noisy Boundaries: Lemon or Lemonade for Semi-Supervised Instance Segmentation?}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2020_learning_15780,
  title = {{Learning Saliency Propagation for Semi-Supervised Instance Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2022_twist_19978,
  title = {{TWIST: Two-Way Inter-Label Self-Training for Semi-Supervised 3D Instance Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2023_the_22336,
  title = {{The Devil Is in the Points: Weakly Semi-Supervised Instance Segmentation via Point-Guided Mask Representation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/23123},
}

@inproceedings{cvpr2023_vision_22533,
  title = {{Vision Transformers Are Good Mask Auto-Labelers}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/23256},
}

@inproceedings{iclr2023_unsupervised_31946,
  title = {{Unsupervised Semantic Segmentation with Self-supervised Object-centric Representations}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11276},
}

@inproceedings{cvpr2024_bsnet_22812,
  title = {{BSNet: Box-Supervised Simulation-assisted Mean Teacher for 3D Instance Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31145},
}

@inproceedings{cvpr2024_extreme_23421,
  title = {{Extreme Point Supervised Instance Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30370},
}

@inproceedings{aaai2024_fully_6070,
  title = {{Fully Data-Driven Pseudo Label Estimation for Pointly-Supervised Panoptic Segmentation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28096},
}

@inproceedings{aaai2021_how_730,
  title = {{How to Save your Annotation Cost for Panoptic Segmentation?}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/01282-how-to-save-your-annotation-cost-for-panoptic-segmentation/},
}

@inproceedings{aaai2025_iterative_9614,
  title = {{Iterative Self-Training with Class-Aware Text-to-Image Synthesis for Visual Task Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33106},
}

@inproceedings{neurips2024_segment_72830,
  title = {{Segment Anything without Supervision}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94569},
}

@inproceedings{aaai2023_maskbooster_4127,
  title = {{MaskBooster: End-to-End Self-Training for Sparsely Supervised Instance Segmentation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25481},
}

@inproceedings{cvpr2025_minimizing_26959,
  title = {{Minimizing Labeled, Maximizing Unlabeled: An Image-Driven Approach for Video Instance Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33178},
}