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

@inproceedings{cvpr2017_scene_12608,
  title = {{Scene Parsing Through ADE20K Dataset}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2019_panoptic_14622,
  title = {{Panoptic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2021_simple_17898,
  title = {{Simple Copy-Paste Is a Strong Data Augmentation Method for Instance Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2017_learning_12417,
  title = {{Learning Video Object Segmentation From Static Images}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2018_deep_12964,
  title = {{Deep Extreme Cut: From Extreme Points to Object Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Maninis_Deep_Extreme_Cut_CVPR_2018_paper.html},
}

@inproceedings{cvpr2018_efficient_13054,
  title = {{Efficient Interactive Annotation of Segmentation Datasets With Polygon-RNN++}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Acuna_Efficient_Interactive_Annotation_CVPR_2018_paper.html},
}

@inproceedings{cvpr2017_annotating_12062,
  title = {{Annotating Object Instances With a Polygon-RNN}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2018_learning_13329,
  title = {{Learning to Segment Every Thing}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Hu_Learning_to_Segment_CVPR_2018_paper.html},
}

@inproceedings{cvpr2018_blazingly_12870,
  title = {{Blazingly Fast Video Object Segmentation With Pixel-Wise Metric Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Chen_Blazingly_Fast_Video_CVPR_2018_paper.html},
}

@inproceedings{cvpr2019_large_14378,
  title = {{Large-Scale Interactive Object Segmentation With Human Annotators}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2019_pose2seg_14660,
  title = {{Pose2Seg: Detection Free Human Instance Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2019_amodal_13842,
  title = {{Amodal Instance Segmentation With KINS Dataset}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2017_learning_12410,
  title = {{Learning Non-Lambertian Object Intrinsics Across ShapeNet Categories}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2017_semantic_12619,
  title = {{Semantic Amodal Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2020_video_16447,
  title = {{Video Panoptic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2020_learning_15752,
  title = {{Learning Fast and Robust Target Models for Video Object Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2016_hd_11583,
  title = {{HD Maps: Fine-Grained Road Segmentation by Parsing Ground and Aerial Images}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{cvpr2020_deep_15369,
  title = {{Deep Polarization Cues for Transparent Object Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2020_interactive_15703,
  title = {{Interactive Object Segmentation With Inside-Outside Guidance}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2020_the_16336,
  title = {{The Edge of Depth: Explicit Constraints Between Segmentation and Depth}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2024_unsupervised_25171,
  title = {{Unsupervised Universal Image Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30968},
}

@inproceedings{cvpr2024_amodal_22757,
  title = {{Amodal Ground Truth and Completion in the Wild}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31072},
}

@inproceedings{cvpr2024_sg_24703,
  title = {{SG-BEV: Satellite-Guided BEV Fusion for Cross-View Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30833},
}

@inproceedings{cvpr2025_ros_27368,
  title = {{ROS-SAM: High-Quality Interactive Segmentation for Remote Sensing Moving Object}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33985},
}

@inproceedings{cvpr2024_mesa_24059,
  title = {{MESA: Matching Everything by Segmenting Anything}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31651},
}

@inproceedings{cvpr2024_coconut_22924,
  title = {{COCONut: Modernizing COCO Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29325},
}

@inproceedings{cvpr2024_segment_24773,
  title = {{Segment Every Out-of-Distribution Object}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31564},
}

@inproceedings{cvpr2024_kandinsky_23864,
  title = {{Kandinsky Conformal Prediction: Efficient Calibration of Image Segmentation Algorithms}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31312},
}

@inproceedings{cvpr2024_open_24374,
  title = {{Open-World Semantic Segmentation Including Class Similarity}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29608},
}

@inproceedings{cvpr2024_region_24605,
  title = {{Region-Based Representations Revisited}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31041},
}

@inproceedings{aaai2024_segment_7281,
  title = {{Segment beyond View: Handling Partially Missing Modality for Audio-Visual Semantic Segmentation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28426},
}

@inproceedings{aaai2024_blade_5256,
  title = {{BLADE: Box-Level Supervised Amodal Segmentation through Directed Expansion}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28176},
}

@inproceedings{cvpr2024_qdformer_24548,
  title = {{QDFormer: Towards Robust Audiovisual Segmentation in Complex Environments with Quantization-based Semantic Decomposition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29348},
}

@inproceedings{cvpr2025_using_28035,
  title = {{Using Diffusion Priors for Video Amodal Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34272},
}

@inproceedings{aaai2025_sauge_10592,
  title = {{SAUGE: Taming SAM for Uncertainty-Aligned Multi-Granularity Edge Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32615},
}

@inproceedings{cvpr2025_segment_27618,
  title = {{Segment Anything, Even Occluded}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/35221},
}

@inproceedings{neurips2024_talos_73312,
  title = {{TALoS: Enhancing Semantic Scene Completion via Test-time Adaptation on the Line of Sight}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94132},
}

@inproceedings{aaai2025_unsupervised_11180,
  title = {{Unsupervised Audio-Visual Segmentation with Modality Alignment}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33709},
}

@inproceedings{cvpr2024_jrdb_23847,
  title = {{JRDB-PanoTrack: An Open-world Panoptic Segmentation and Tracking Robotic Dataset in Crowded Human Environments}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29542},
}

@inproceedings{cvpr2024_task_24965,
  title = {{Task-aligned Part-aware Panoptic Segmentation through Joint Object-Part Representations}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29757},
}