% Key papers for Biologically inspired robust vision (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2016_improving_11608,
  title = {{Improving the Robustness of Deep Neural Networks via Stability Training}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{cvpr2018_crowd_12939,
  title = {{Crowd Counting via Adversarial Cross-Scale Consistency Pursuit}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Shen_Crowd_Counting_via_CVPR_2018_paper.html},
}

@inproceedings{cvpr2018_deflecting_12994,
  title = {{Deflecting Adversarial Attacks With Pixel Deflection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Prakash_Deflecting_Adversarial_Attacks_CVPR_2018_paper.html},
}

@inproceedings{iclr2017_on_28319,
  title = {{On Detecting Adversarial Perturbations}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=SJzCSf9xg},
}

@inproceedings{cvpr2020_towards_16361,
  title = {{Towards Large Yet Imperceptible Adversarial Image Perturbations With Perceptual Color Distance}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{icml2018_lavan_36773,
  title = {{LaVAN: Localized and Visible Adversarial Noise}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2154},
}

@inproceedings{neurips2020_simulating_60833,
  title = {{Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17327},
}

@inproceedings{neurips2017_houdini_56365,
  title = {{Houdini: Fooling Deep Structured Visual and Speech Recognition Models with Adversarial Examples}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9464},
}

@inproceedings{cvpr2022_bppattack_18389,
  title = {{BppAttack: Stealthy and Efficient Trojan Attacks Against Deep Neural Networks via Image Quantization and Contrastive Adversarial Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2019_non_103461,
  title = {{Non-Local Context Encoder: Robust Biomedical Image Segmentation against Adversarial Attacks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4857},
}

@inproceedings{cvpr2023_evading_20926,
  title = {{Evading DeepFake Detectors via Adversarial Statistical Consistency}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22605},
}

@inproceedings{cvpr2020_towards_16365,
  title = {{Towards Robust Image Classification Using Sequential Attention Models}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2021_when_18153,
  title = {{When Human Pose Estimation Meets Robustness: Adversarial Algorithms and Benchmarks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2020_reciprocal_16093,
  title = {{Reciprocal Learning Networks for Human Trajectory Prediction}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2021_class_16701,
  title = {{Class-Aware Robust Adversarial Training for Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2019_defense_14062,
  title = {{Defense Against Adversarial Images Using Web-Scale Nearest-Neighbor Search}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2019_exact_14162,
  title = {{Exact Adversarial Attack to Image Captioning via Structured Output Learning With Latent Variables}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{iclr2020_detecting_29685,
  title = {{Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=Skgy464Kvr},
}

@inproceedings{cvpr2022_towards_20060,
  title = {{Towards Robust Rain Removal Against Adversarial Attacks: A Comprehensive Benchmark Analysis and Beyond}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{icml2020_informative_38329,
  title = {{Informative Dropout for Robust Representation Learning: A Shape-bias Perspective}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5839},
}

@inproceedings{aaai2025_a_8207,
  title = {{A²RNet: Adversarial Attack Resilient Network for Robust Infrared and Visible Image Fusion}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32504},
}

@inproceedings{cvpr2024_rodla_24663,
  title = {{RoDLA: Benchmarking the Robustness of Document Layout Analysis Models}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29469},
}

@inproceedings{aaai2024_towards_7616,
  title = {{Towards Robust Image Stitching: An Adaptive Resistance Learning against Compatible Attacks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28036},
}

@inproceedings{aaai2024_comparing_5437,
  title = {{Comparing the Robustness of Modern No-Reference Image- and Video-Quality Metrics to Adversarial Attacks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27827},
}

@inproceedings{cvpr2024_cosalpure_23053,
  title = {{CosalPure: Learning Concept from Group Images for Robust Co-Saliency Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29683},
}

@inproceedings{aaai2025_kdat_9632,
  title = {{KDAT: Inherent Adversarial Robustness via Knowledge Distillation with Adversarial Tuning for Object Detection Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32485},
}

@inproceedings{cvpr2025_deal_25816,
  title = {{DEAL: Data-Efficient Adversarial Learning for High-Quality Infrared Imaging}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/32549},
}

@inproceedings{cvpr2025_saliuitl_27565,
  title = {{Saliuitl: Ensemble Salience Guided Recovery of Adversarial Patches against CNNs}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34821},
}

@inproceedings{neurips2024_constructing_74429,
  title = {{Constructing Semantics-Aware Adversarial Examples with a Probabilistic Perspective}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93142},
}

@inproceedings{iclr2025_adversarial_84120,
  title = {{Adversarial Perturbations Cannot Reliably Protect Artists From Generative AI}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/27708},
}

@inproceedings{cvpr2025_patchdemux_27227,
  title = {{PatchDEMUX: A Certifiably Robust Framework for Multi-label Classifiers Against Adversarial Patches}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/32664},
}

@inproceedings{aaai2024_on_6837,
  title = {{On the Robustness of Neural-Enhanced Video Streaming against Adversarial Attacks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29657},
}

@inproceedings{iclr2024_lipsim_33474,
  title = {{LipSim: A Provably Robust Perceptual Similarity Metric}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19601},
}

@inproceedings{icml2024_ioi_43785,
  title = {{IOI: Invisible One-Iteration Adversarial Attack on No-Reference Image- and Video-Quality Metrics}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34667},
}

@inproceedings{cvpr2025_disentangling_25960,
  title = {{Disentangling Safe and Unsafe Image Corruptions via Anisotropy and Locality}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34023},
}

@inproceedings{iclr2024_irad_35040,
  title = {{IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18034},
}

@inproceedings{iclr2024_foundation_35057,
  title = {{Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18017},
}

@inproceedings{iclr2025_rethinking_82873,
  title = {{Rethinking Audio-Visual Adversarial Vulnerability from Temporal and Modality Perspectives}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28927},
}

@inproceedings{iclr2025_jpeg_83781,
  title = {{JPEG Inspired Deep Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28038},
}

@inproceedings{aaai2026_oti_104086,
  title = {{OTI: A Model-free and Visually Interpretable Measure of Image Attackability}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37615},
}