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

@inproceedings{cvpr2019_lvis_14367,
  title = {{LVIS: A Dataset for Large Vocabulary Instance Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2023_open_21782,
  title = {{Open-Vocabulary Semantic Segmentation With Mask-Adapted CLIP}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/21485},
}

@inproceedings{cvpr2023_side_22203,
  title = {{Side Adapter Network for Open-Vocabulary Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/21298},
}

@inproceedings{neurips2023_segment_68283,
  title = {{Segment Everything Everywhere All at Once}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/71518},
}

@inproceedings{cvpr2023_learning_21382,
  title = {{Learning Open-Vocabulary Semantic Segmentation Models From Natural Language Supervision}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22681},
}

@inproceedings{cvpr2023_learning_21404,
  title = {{Learning To Generate Text-Grounded Mask for Open-World Semantic Segmentation From Only Image-Text Pairs}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/20978},
}

@inproceedings{cvpr2023_freeseg_21021,
  title = {{FreeSeg: Unified, Universal and Open-Vocabulary Image Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22824},
}

@inproceedings{cvpr2022_open_19519,
  title = {{Open-Vocabulary Instance Segmentation via Robust Cross-Modal Pseudo-Labeling}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2024_omg_24314,
  title = {{OMG-Seg: Is One Model Good Enough For All Segmentation?}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30954},
}

@inproceedings{cvpr2023_open_21773,
  title = {{Open Vocabulary Semantic Segmentation With Patch Aligned Contrastive Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/21129},
}

@inproceedings{cvpr2025_segearth_27614,
  title = {{SegEarth-OV: Towards Training-Free Open-Vocabulary Segmentation for Remote Sensing Images}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/35106},
}

@inproceedings{aaai2020_two_102974,
  title = {{Two-Level Transformer and Auxiliary Coherence Modeling for Improved Text Segmentation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6284},
}

@inproceedings{cvpr2024_open_24370,
  title = {{Open-Vocabulary Segmentation with Semantic-Assisted Calibration}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29834},
}

@inproceedings{cvpr2024_clip_22913,
  title = {{CLIP as RNN: Segment Countless Visual Concepts without Training Endeavor}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31270},
}

@inproceedings{neurips2023_openmask3d_67079,
  title = {{OpenMask3D: Open-Vocabulary 3D Instance Segmentation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/72623},
}

@inproceedings{cvpr2024_open_24371,
  title = {{Open-Vocabulary Semantic Segmentation with Image Embedding Balancing}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29347},
}

@inproceedings{cvpr2024_training_25076,
  title = {{Training-Free Open-Vocabulary Segmentation with Offline Diffusion-Augmented Prototype Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30941},
}

@inproceedings{icml2023_segclip_43111,
  title = {{SegCLIP: Patch Aggregation with Learnable Centers for Open-Vocabulary Semantic Segmentation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/24084},
}

@inproceedings{aaai2026_exploring_102576,
  title = {{Exploring Efficient Open-Vocabulary Segmentation in the Remote Sensing}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37521},
}

@inproceedings{neurips2023_weakly_67981,
  title = {{Weakly Supervised 3D Open-vocabulary Segmentation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/71793},
}

@inproceedings{cvpr2024_open_24367,
  title = {{Open-Vocabulary 3D Semantic Segmentation with Foundation Models}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31804},
}

@inproceedings{cvpr2025_mask_26925,
  title = {{Mask-Adapter: The Devil is in the Masks for Open-Vocabulary Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/35217},
}

@inproceedings{cvpr2024_use_25106,
  title = {{USE: Universal Segment Embeddings for Open-Vocabulary Image Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31069},
}

@inproceedings{cvpr2024_image_23757,
  title = {{Image-to-Image Matching via Foundation Models: A New Perspective for Open-Vocabulary Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29958},
}

@inproceedings{iclr2024_clipself_33947,
  title = {{CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense Prediction}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19128},
}

@inproceedings{cvpr2025_distilling_25969,
  title = {{Distilling Spectral Graph for Object-Context Aware Open-Vocabulary Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33959},
}

@inproceedings{aaai2025_openvis_10205,
  title = {{OpenVIS: Open-vocabulary Video Instance Segmentation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32338},
}

@inproceedings{cvpr2025_exploring_26191,
  title = {{Exploring Simple Open-Vocabulary Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/35214},
}

@inproceedings{cvpr2025_effective_26087,
  title = {{Effective SAM Combination for Open-Vocabulary Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/32975},
}

@inproceedings{neurips2024_towards_72845,
  title = {{Towards Open-Vocabulary Semantic Segmentation Without Semantic Labels}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94555},
}

@inproceedings{aaai2025_boosting_8283,
  title = {{Boosting Segment Anything Model Towards Open-Vocabulary Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32347},
}

@inproceedings{cvpr2025_parameter_27220,
  title = {{Parameter-efficient Fine-tuning in Hyperspherical Space for Open-vocabulary Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33863},
}

@inproceedings{neurips2024_relationship_71995,
  title = {{Relationship Prompt Learning is Enough for Open-Vocabulary Semantic Segmentation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95318},
}