% Key papers for Scene graph generation (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2017_scene_12607,
  title = {{Scene Graph Generation by Iterative Message Passing}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2018_neural_13422,
  title = {{Neural Motifs: Scene Graph Parsing With Global Context}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Zellers_Neural_Motifs_Scene_CVPR_2018_paper.html},
}

@inproceedings{cvpr2019_auto_13879,
  title = {{Auto-Encoding Scene Graphs for Image Captioning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2020_unbiased_16393,
  title = {{Unbiased Scene Graph Generation From Biased Training}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2019_knowledge_14359,
  title = {{Knowledge-Embedded Routing Network for Scene Graph Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2019_scene_14774,
  title = {{Scene Graph Generation With External Knowledge and Image Reconstruction}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2020_gps_15585,
  title = {{GPS-Net: Graph Property Sensing Network for Scene Graph Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2020_say_16178,
  title = {{Say As You Wish: Fine-Grained Control of Image Caption Generation With Abstract Scene Graphs}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2021_bipartite_16653,
  title = {{Bipartite Graph Network With Adaptive Message Passing for Unbiased Scene Graph Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2019_attentive_13873,
  title = {{Attentive Relational Networks for Mapping Images to Scene Graphs}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2021_energy_16952,
  title = {{Energy-Based Learning for Scene Graph Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2022_sgtr_19769,
  title = {{SGTR: End-to-End Scene Graph Generation With Transformer}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{neurips2018_mapping_57357,
  title = {{Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11694},
}

@inproceedings{cvpr2021_probabilistic_17654,
  title = {{Probabilistic Modeling of Semantic Ambiguity for Scene Graph Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2022_ppdl_19544,
  title = {{PPDL: Predicate Probability Distribution Based Loss for Unbiased Scene Graph Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2021_exploiting_16971,
  title = {{Exploiting Edge-Oriented Reasoning for 3D Point-Based Scene Graph Analysis}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{aaai2020_deep_103676,
  title = {{Deep Generative Probabilistic Graph Neural Networks for Scene Graph Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6783},
}

@inproceedings{aaai2020_storytelling_103145,
  title = {{Storytelling from an Image Stream Using Scene Graphs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6455},
}

@inproceedings{cvpr2022_hl_18976,
  title = {{HL-Net: Heterophily Learning Network for Scene Graph Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2022_fine_18858,
  title = {{Fine-Grained Predicates Learning for Scene Graph Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2024_panoptic_6916,
  title = {{Panoptic Scene Graph Generation with Semantics-Prototype Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28098},
}

@inproceedings{cvpr2024_hiker_23693,
  title = {{HiKER-SGG: Hierarchical Knowledge Enhanced Robust Scene Graph Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29866},
}

@inproceedings{cvpr2024_dsgg_23098,
  title = {{DSGG: Dense Relation Transformer for an End-to-end Scene Graph Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31359},
}

@inproceedings{cvpr2024_constrained_23019,
  title = {{Constrained Layout Generation with Factor Graphs}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31843},
}

@inproceedings{cvpr2025_asynchronous_25519,
  title = {{Asynchronous Collaborative Graph Representation for Frames and Events}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/35079},
}

@inproceedings{aaai2024_kumaraswamy_6390,
  title = {{Kumaraswamy Wavelet for Heterophilic Scene Graph Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27875},
}

@inproceedings{cvpr2025_conformal_25763,
  title = {{Conformal Prediction and MLLM aided Uncertainty Quantification in Scene Graph Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34281},
}

@inproceedings{cvpr2025_towards_27930,
  title = {{Towards Unbiased and Robust Spatio-Temporal Scene Graph Generation and Anticipation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34271},
}

@inproceedings{iclr2024_adaptive_34609,
  title = {{Adaptive Self-training Framework for Fine-grained Scene Graph Generation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18465},
}

@inproceedings{neurips2024_adaptive_70619,
  title = {{Adaptive Visual Scene Understanding: Incremental Scene Graph Generation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96501},
}

@inproceedings{icml2024_scene_45586,
  title = {{Scene Graph Generation Strategy with Co-occurrence Knowledge and Learnable Term Frequency}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32866},
}

@inproceedings{aaai2025_scene_10693,
  title = {{Scene Graph-Grounded Image Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32823},
}

@inproceedings{cvpr2025_t2sg_27798,
  title = {{T2SG: Traffic Topology Scene Graph for Topology Reasoning in Autonomous Driving}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33744},
}

@inproceedings{iclr2025_hydra_83797,
  title = {{Hydra-SGG: Hybrid Relation Assignment for One-stage Scene Graph Generation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28023},
}

@inproceedings{iclr2026_panoptic_86897,
  title = {{Panoptic Pairwise Distortion Graph}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=VDfF7NqJJl},
}

@inproceedings{neurips2026_a_94859,
  title = {{A Closer Look at Dynamic Scene Graph Generation in the Era of Multimodal Large Language Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/151784},
}

@inproceedings{cvpr2026_can_96434,
  title = {{Can We Build Scene Graphs, Not Classify Them? FlowSG: Progressive Image-Conditioned Scene Graph Generation with Flow Matching}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Hu_Can_We_Build_Scene_Graphs_Not_Classify_Them_FlowSG_Progressive_CVPR_2026_paper.html},
}

@inproceedings{cvpr2026_dsflash_97673,
  title = {{DSFlash: Comprehensive Panoptic Scene Graph Generation in Realtime}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Lorenz_DSFlash_Comprehensive_Panoptic_Scene_Graph_Generation_in_Realtime_CVPR_2026_paper.html},
}

@inproceedings{cvpr2026_robo_97940,
  title = {{Robo-SGG: Exploiting Layout-Oriented Normalization and Restitution Can Improve Robust Scene Graph Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Lv_Robo-SGG_Exploiting_Layout-Oriented_Normalization_and_Restitution_Can_Improve_Robust_Scene_CVPR_2026_paper.html},
}

@inproceedings{aaai2026_edge_104199,
  title = {{Edge-Centric Relational Reasoning for 3D Scene Graph Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37728},
}