% Key papers for Few-shot object detection (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2022_grounded_18961,
  title = {{Grounded Language-Image Pre-Training}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2020_few_15545,
  title = {{Few-Shot Object Detection With Attention-RPN and Multi-Relation Detector}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2021_fsce_16995,
  title = {{FSCE: Few-Shot Object Detection via Contrastive Proposal Encoding}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2019_repmet_14729,
  title = {{RepMet: Representative-Based Metric Learning for Classification and Few-Shot Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{icml2020_frustratingly_38235,
  title = {{Frustratingly Simple Few-Shot Object Detection}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6261},
}

@inproceedings{cvpr2021_semantic_17869,
  title = {{Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{aaai2022_meta_2409,
  title = {{Meta Faster R-CNN: Towards Accurate Few-Shot Object Detection with Attentive Feature Alignment}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/00780-meta-faster-r-cnn-towards-accurate-few-shot-object-detection-with-attentive-feature-alignment/},
}

@inproceedings{cvpr2021_beyond_16642,
  title = {{Beyond Max-Margin: Class Margin Equilibrium for Few-Shot Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2021_generalized_17067,
  title = {{Generalized Few-Shot Object Detection Without Forgetting}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{aaai2023_few_3693,
  title = {{Few-Shot Object Detection via Variational Feature Aggregation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25153},
}

@inproceedings{neurips2019_one_58745,
  title = {{One-Shot Object Detection with Co-Attention and Co-Excitation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13461},
}

@inproceedings{cvpr2021_hallucination_17107,
  title = {{Hallucination Improves Few-Shot Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2021_transformation_18046,
  title = {{Transformation Invariant Few-Shot Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2021_few_17020,
  title = {{Few-Shot Object Detection via Classification Refinement and Distractor Retreatment}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2018_hierarchical_13184,
  title = {{Hierarchical Novelty Detection for Visual Object Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Lee_Hierarchical_Novelty_Detection_CVPR_2018_paper.html},
}

@inproceedings{aaai2023_breaking_3199,
  title = {{Breaking Immutable: Information-Coupled Prototype Elaboration for Few-Shot Object Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25274},
}

@inproceedings{cvpr2018_learning_13327,
  title = {{Learning to Promote Saliency Detectors}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Zeng_Learning_to_Promote_CVPR_2018_paper.html},
}

@inproceedings{cvpr2023_digeo_20786,
  title = {{DiGeo: Discriminative Geometry-Aware Learning for Generalized Few-Shot Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22789},
}

@inproceedings{cvpr2021_accurate_16559,
  title = {{Accurate Few-Shot Object Detection With Support-Query Mutual Guidance and Hybrid Loss}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2024_few_23468,
  title = {{Few-Shot Object Detection with Foundation Models}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31250},
}

@inproceedings{cvpr2024_point_24479,
  title = {{Point Segment and Count: A Generalized Framework for Object Counting}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30762},
}

@inproceedings{cvpr2024_snida_24716,
  title = {{SNIDA: Unlocking Few-Shot Object Detection with Non-linear Semantic Decoupling Augmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29737},
}

@inproceedings{aaai2024_zero_7843,
  title = {{Zero-Shot Aerial Object Detection with Visual Description Regularization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28518},
}

@inproceedings{cvpr2024_dave_23080,
  title = {{DAVE - A Detect-and-Verify Paradigm for Low-Shot Counting}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30795},
}

@inproceedings{aaai2024_detect_5674,
  title = {{Detect Any Keypoints: An Efficient Light-Weight Few-Shot Keypoint Detector}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28180},
}

@inproceedings{aaai2025_cp_8360,
  title = {{CP-DETR: Concept Prompt Guide DETR Toward Stronger Universal Object Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32212},
}

@inproceedings{neurips2024_zero_72753,
  title = {{Zero-shot Generalizable Incremental Learning for Vision-Language Object Detection}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94639},
}

@inproceedings{cvpr2025_open_27156,
  title = {{Open-World Objectness Modeling Unifies Novel Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/32737},
}

@inproceedings{neurips2024_a_73782,
  title = {{A Novel Unified Architecture for Low-Shot Counting by Detection and Segmentation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93724},
}

@inproceedings{aaai2024_spotting_7402,
  title = {{Spotting the Unseen: Reciprocal Consensus Network Guided by Visual Archetypes}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29149},
}

@inproceedings{aaai2024_exploring_5912,
  title = {{Exploring Base-Class Suppression with Prior Guidance for Bias-Free One-Shot Object Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28561},
}

@inproceedings{cvpr2025_generalizable_26404,
  title = {{Generalizable Object Keypoint Localization from Generative Priors}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33925},
}

@inproceedings{icml2025_idpa_48206,
  title = {{iDPA: Instance Decoupled Prompt Attention for Incremental Medical Object Detection}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44405},
}

@inproceedings{neurips2025_find_79021,
  title = {{Find your Needle: Small Object Image Retrieval via Multi-Object Attention Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=koZxsoeuAO},
}

@inproceedings{iclr2025_predicate_83321,
  title = {{Predicate Hierarchies Improve Few-Shot State Classification}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28492},
}

@inproceedings{iclr2025_multi_83559,
  title = {{Multi-Perspective Data Augmentation for Few-shot Object Detection}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28258},
}

@inproceedings{iclr2026_fsod_88117,
  title = {{FSOD-VFM: Few-Shot Object Detection with Vision Foundation Models and Graph Diffusion}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=jHlAq2rYUw},
}

@inproceedings{cvpr2026_a_98176,
  title = {{A Closer Look at Cross-Domain Few-Shot Object Detection: Fine-Tuning Matters and Parallel Decoder Helps}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Yu_A_Closer_Look_at_Cross-Domain_Few-Shot_Object_Detection_Fine-Tuning_Matters_CVPR_2026_paper.html},
}

@inproceedings{aaai2026_sam2_100454,
  title = {{SAM2-OV: A Novel Detection-Only Tuning Paradigm for Open-Vocabulary Multi-Object Tracking}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37301},
}