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

@inproceedings{cvpr2021_detectors_16861,
  title = {{DetectoRS: Detecting Objects With Recursive Feature Pyramid and Switchable Atrous Convolution}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{neurips2017_associative_56163,
  title = {{Associative Embedding: End-to-End Learning for Joint Detection and Grouping}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9015},
}

@inproceedings{cvpr2021_propagate_17667,
  title = {{Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{aaai2019_devil_101694,
  title = {{Devil in the Details: Towards Accurate Single and Multiple Human Parsing}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4409},
}

@inproceedings{cvpr2020_d2det_15320,
  title = {{D2Det: Towards High Quality Object Detection and Instance Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2020_centripetalnet_15248,
  title = {{CentripetalNet: Pursuing High-Quality Keypoint Pairs for Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2018_learning_13274,
  title = {{Learning Deep Structured Active Contours End-to-End}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Marcos_Learning_Deep_Structured_CVPR_2018_paper.html},
}

@inproceedings{cvpr2019_darnet_13997,
  title = {{DARNet: Deep Active Ray Network for Building Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2019_parsing_14625,
  title = {{Parsing R-CNN for Instance-Level Human Analysis}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2021_a2_16547,
  title = {{A2-FPN: Attention Aggregation Based Feature Pyramid Network for Instance Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2020_sdc_16155,
  title = {{SDC-Depth: Semantic Divide-and-Conquer Network for Monocular Depth Estimation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{aaai2021_scnet_1305,
  title = {{SCNet: Training Inference Sample Consistency for Instance Segmentation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/02701-scnet-training-inference-sample-consistency-for-instance-segmentation/},
}

@inproceedings{aaai2021_learning_889,
  title = {{Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/01863-learning-monocular-depth-in-dynamic-scenes-via-instance-aware-projection-consistency/},
}

@inproceedings{cvpr2016_multi_11713,
  title = {{Multi-Scale Patch Aggregation (MPA) for Simultaneous Detection and Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{cvpr2020_instance_15695,
  title = {{Instance Shadow Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{neurips2020_reppoints_60701,
  title = {{RepPoints v2: Verification Meets Regression for Object Detection}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17552},
}

@inproceedings{cvpr2021_differentiable_16866,
  title = {{Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic Parsing}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2017_miml_12446,
  title = {{MIML-FCN+: Multi-Instance Multi-Label Learning via Fully Convolutional Networks With Privileged Information}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2022_instaformer_19082,
  title = {{InstaFormer: Instance-Aware Image-to-Image Translation With Transformer}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{neurips2018_sniper_57594,
  title = {{SNIPER: Efficient Multi-Scale Training}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11887},
}

@inproceedings{cvpr2024_mgmap_24061,
  title = {{MGMap: Mask-Guided Learning for Online Vectorized HD Map Construction}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30696},
}

@inproceedings{cvpr2024_dual_23278,
  title = {{Dual DETRs for Multi-Label Temporal Action Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30591},
}

@inproceedings{cvpr2024_shadow_24808,
  title = {{Shadow-Enlightened Image Outpainting}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31266},
}

@inproceedings{neurips2024_efficient_73542,
  title = {{Efficient Temporal Action Segmentation via Boundary-aware Query Voting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93937},
}

@inproceedings{neurips2024_di_74176,
  title = {{DI-MaskDINO: A Joint Object Detection and Instance Segmentation Model}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93369},
}

@inproceedings{iclr2025_rmp_80581,
  title = {{RMP-SAM: Towards Real-Time Multi-Purpose Segment Anything}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/31184},
}

@inproceedings{cvpr2025_roictrl_27365,
  title = {{ROICtrl: Boosting Instance Control for Visual Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/32388},
}

@inproceedings{cvpr2026_differentiable_97521,
  title = {{Differentiable Laplacian Matrix Guided Superpixel Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Juybari_Differentiable_Laplacian_Matrix_Guided_Superpixel_Segmentation_CVPR_2026_paper.html},
}