@misc{yu2018generativeimageinpaintingcontextual,
      title={Generative Image Inpainting with Contextual Attention}, 
      author={Jiahui Yu and Zhe Lin and Jimei Yang and Xiaohui Shen and Xin Lu and Thomas S. Huang},
      year={2018},
      eprint={1801.07892},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1801.07892}, 
}

@misc{nazeri2019edgeconnectgenerativeimageinpainting,
      title={EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning}, 
      author={Kamyar Nazeri and Eric Ng and Tony Joseph and Faisal Z. Qureshi and Mehran Ebrahimi},
      year={2019},
      eprint={1901.00212},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1901.00212}, 
}

@INPROCEEDINGS{7780647,
  author={Pathak, Deepak and Krähenbühl, Philipp and Donahue, Jeff and Darrell, Trevor and Efros, Alexei A.},
  booktitle={2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, 
  title={Context Encoders: Feature Learning by Inpainting}, 
  year={2016},
  volume={},
  number={},
  pages={2536-2544},
  keywords={Context;Decoding;Image reconstruction;Visualization;Semantics;Convolutional codes;Computer architecture},
  doi={10.1109/CVPR.2016.278}}

@misc{10.1145/3072959.3073659,
author = {Iizuka, Satoshi and Simo-Serra, Edgar and Ishikawa, Hiroshi},
title = {Globally and locally consistent image completion},
year = {2017},
issue_date = {August 2017},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {36},
number = {4},
issn = {0730-0301},
url = {https://doi.org/10.1145/3072959.3073659},
doi = {10.1145/3072959.3073659},
month = jul,
articleno = {107},
numpages = {14},
keywords = {image completion, convolutional neural network}
}

@misc{park2017transformationgroundedimagegenerationnetwork,
      title={Transformation-Grounded Image Generation Network for Novel 3D View Synthesis}, 
      author={Eunbyung Park and Jimei Yang and Ersin Yumer and Duygu Ceylan and Alexander C. Berg},
      year={2017},
      eprint={1703.02921},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1703.02921}, 
}

@misc{sabini2018paintingoutsideboximage,
      title={Painting Outside the Box: Image Outpainting with GANs}, 
      author={Mark Sabini and Gili Rusak},
      year={2018},
      eprint={1808.08483},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1808.08483}, 
}

@article{DBLP:journals/corr/abs-2109-07161,
  author       = {Roman Suvorov and
                  Elizaveta Logacheva and
                  Anton Mashikhin and
                  Anastasia Remizova and
                  Arsenii Ashukha and
                  Aleksei Silvestrov and
                  Naejin Kong and
                  Harshith Goka and
                  Kiwoong Park and
                  Victor Lempitsky},
  title        = {Resolution-robust Large Mask Inpainting with Fourier Convolutions},
  journal      = {CoRR},
  volume       = {abs/2109.07161},
  year         = {2021},
  url          = {https://arxiv.org/abs/2109.07161},
  eprinttype    = {arXiv},
  eprint       = {2109.07161},
  timestamp    = {Wed, 22 Sep 2021 14:16:57 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2109-07161.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{labadie2018preliminary,
title={Preliminary Results With Image-guided Cochlear Implant Insertion Techniques},
author={Labadie, RF and Noble, JH},
journal={Otol Neurotol},
volume={39},
number={7},
pages={922-928},
year={2018},
month={Aug},
doi={10.1097/MAO.0000000000001850},
PMID={29995013},
PMCID={PMC6344356}
}

@misc{zhang2024mastoidectomymultiviewsynthesissingle,
      title={Mastoidectomy Multi-View Synthesis from a Single Microscopy Image}, 
      author={Yike Zhang and Jack Noble},
      year={2024},
      eprint={2409.03190},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2409.03190}, 
}

@misc{zhang2024mmunsupervisedmambabasedmastoidectomy,
      title={M\&M: Unsupervised Mamba-based Mastoidectomy for Cochlear Implant Surgery with Noisy Data}, 
      author={Yike Zhang and Eduardo Davalos and Dingjie Su and Ange Lou and Jack H. Noble},
      year={2024},
      eprint={2407.15787},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2407.15787}, 
}

@inproceedings{10.1117/12.2655653,
author = {Yike Zhang and Jack H. Noble},
title = {{Self-supervised registration and segmentation on ossicles with a single ground truth label}},
volume = {12466},
booktitle = {Medical Imaging 2023: Image-Guided Procedures, Robotic Interventions, and Modeling},
editor = {Cristian A. Linte and Jeffrey H. Siewerdsen},
organization = {International Society for Optics and Photonics},
publisher = {SPIE},
pages = {124660X},
keywords = {Self-supervised learning, image registration, image segmentation, 3D-UNet, cochlear implant, ossicles},
year = {2023},
doi = {10.1117/12.2655653},
URL = {https://doi.org/10.1117/12.2655653}
}

@inproceedings{10.1117/12.3008830,
author = {Yike Zhang and Eduardo Davalos and Dingjie Su and Ange Lou and Jack H. Noble},
title = {{Monocular microscope to CT registration using pose estimation of the incus for augmented reality cochlear implant surgery}},
volume = {12928},
booktitle = {Medical Imaging 2024: Image-Guided Procedures, Robotic Interventions, and Modeling},
editor = {Jeffrey H. Siewerdsen and Maryam E. Rettmann},
organization = {International Society for Optics and Photonics},
publisher = {SPIE},
pages = {129282I},
keywords = {Image-guided surgery, deep learning, 6D pose estimation, dense correspondence, registration},
year = {2024},
doi = {10.1117/12.3008830},
URL = {https://doi.org/10.1117/12.3008830}
}

@misc{song2023consistencymodels,
      title={Consistency Models}, 
      author={Yang Song and Prafulla Dhariwal and Mark Chen and Ilya Sutskever},
      year={2023},
      eprint={2303.01469},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2303.01469}, 
}

@misc{ho2020denoisingdiffusionprobabilisticmodels,
      title={Denoising Diffusion Probabilistic Models}, 
      author={Jonathan Ho and Ajay Jain and Pieter Abbeel},
      year={2020},
      eprint={2006.11239},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2006.11239}, 
}

@misc{isola2018imagetoimagetranslationconditionaladversarial,
      title={Image-to-Image Translation with Conditional Adversarial Networks}, 
      author={Phillip Isola and Jun-Yan Zhu and Tinghui Zhou and Alexei A. Efros},
      year={2018},
      eprint={1611.07004},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1611.07004}, 
}

@misc{zhao2021largescaleimagecompletion,
      title={Large Scale Image Completion via Co-Modulated Generative Adversarial Networks}, 
      author={Shengyu Zhao and Jonathan Cui and Yilun Sheng and Yue Dong and Xiao Liang and Eric I Chang and Yan Xu},
      year={2021},
      eprint={2103.10428},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2103.10428}, 
}

@misc{radford2016unsupervisedrepresentationlearningdeep,
      title={Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks}, 
      author={Alec Radford and Luke Metz and Soumith Chintala},
      year={2016},
      eprint={1511.06434},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/1511.06434}, 
}

@misc{demir2018patchbasedimageinpaintinggenerative,
      title={Patch-Based Image Inpainting with Generative Adversarial Networks}, 
      author={Ugur Demir and Gozde Unal},
      year={2018},
      eprint={1803.07422},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1803.07422}, 
}

@misc{esser2021tamingtransformershighresolutionimage,
      title={Taming Transformers for High-Resolution Image Synthesis}, 
      author={Patrick Esser and Robin Rombach and Björn Ommer},
      year={2021},
      eprint={2012.09841},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2012.09841}, 
}

@misc{wang2018esrganenhancedsuperresolutiongenerative,
      title={ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks}, 
      author={Xintao Wang and Ke Yu and Shixiang Wu and Jinjin Gu and Yihao Liu and Chao Dong and Chen Change Loy and Yu Qiao and Xiaoou Tang},
      year={2018},
      eprint={1809.00219},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1809.00219}, 
}

@misc{marinescu2021bayesianimagereconstructionusing,
      title={Bayesian Image Reconstruction using Deep Generative Models}, 
      author={Razvan V Marinescu and Daniel Moyer and Polina Golland},
      year={2021},
      eprint={2012.04567},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2012.04567}, 
}

@misc{salimans2016improvedtechniquestraininggans,
      title={Improved Techniques for Training GANs}, 
      author={Tim Salimans and Ian Goodfellow and Wojciech Zaremba and Vicki Cheung and Alec Radford and Xi Chen},
      year={2016},
      eprint={1606.03498},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/1606.03498}, 
}

@misc{fid,
      title={GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium}, 
      author={Martin Heusel and Hubert Ramsauer and Thomas Unterthiner and Bernhard Nessler and Sepp Hochreiter},
      year={2018},
      eprint={1706.08500},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/1706.08500}, 
}

@misc{kid,
      title={Demystifying MMD GANs}, 
      author={Mikołaj Bińkowski and Danica J. Sutherland and Michael Arbel and Arthur Gretton},
      year={2021},
      eprint={1801.01401},
      archivePrefix={arXiv},
      primaryClass={stat.ML},
      url={https://arxiv.org/abs/1801.01401}, 
}

@misc{zhang2018unreasonableeffectivenessdeepfeatures,
      title={The Unreasonable Effectiveness of Deep Features as a Perceptual Metric}, 
      author={Richard Zhang and Phillip Isola and Alexei A. Efros and Eli Shechtman and Oliver Wang},
      year={2018},
      eprint={1801.03924},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1801.03924}, 
}

@ARTICLE{ssim,
  author={Zhou Wang and Bovik, A.C. and Sheikh, H.R. and Simoncelli, E.P.},
  journal={IEEE Transactions on Image Processing}, 
  title={Image quality assessment: from error visibility to structural similarity}, 
  year={2004},
  volume={13},
  number={4},
  pages={600-612},
  keywords={Image quality;Humans;Transform coding;Visual system;Visual perception;Data mining;Layout;Quality assessment;Degradation;Indexes},
  doi={10.1109/TIP.2003.819861}}

@misc{xu2022imagecompletionheterogeneouslyfiltered,
      title={Image Completion with Heterogeneously Filtered Spectral Hints}, 
      author={Xingqian Xu and Shant Navasardyan and Vahram Tadevosyan and Andranik Sargsyan and Yadong Mu and Humphrey Shi},
      year={2022},
      eprint={2211.03700},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2211.03700}, 
}

@misc{zheng2021bridgingglobalcontextinteractions,
      title={Bridging Global Context Interactions for High-Fidelity Image Completion}, 
      author={Chuanxia Zheng and Tat-Jen Cham and Jianfei Cai and Dinh Phung},
      year={2021},
      eprint={2104.00845},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2104.00845}, 
}

@misc{hui2020imagefinegrainedinpainting,
      title={Image Fine-grained Inpainting}, 
      author={Zheng Hui and Jie Li and Xiumei Wang and Xinbo Gao},
      year={2020},
      eprint={2002.02609},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2002.02609}, 
}

@misc{zeng2021aggregatedcontextualtransformationshighresolution,
      title={Aggregated Contextual Transformations for High-Resolution Image Inpainting}, 
      author={Yanhong Zeng and Jianlong Fu and Hongyang Chao and Baining Guo},
      year={2021},
      eprint={2104.01431},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2104.01431}, 
}

@misc{zhu2018multimodalimagetoimagetranslation,
      title={Toward Multimodal Image-to-Image Translation}, 
      author={Jun-Yan Zhu and Richard Zhang and Deepak Pathak and Trevor Darrell and Alexei A. Efros and Oliver Wang and Eli Shechtman},
      year={2018},
      eprint={1711.11586},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1711.11586}, 
}

@misc{zhu2020unpairedimagetoimagetranslationusing,
      title={Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks}, 
      author={Jun-Yan Zhu and Taesung Park and Phillip Isola and Alexei A. Efros},
      year={2020},
      eprint={1703.10593},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1703.10593}, 
}

@misc{he2015deepresiduallearningimage,
      title={Deep Residual Learning for Image Recognition}, 
      author={Kaiming He and Xiangyu Zhang and Shaoqing Ren and Jian Sun},
      year={2015},
      eprint={1512.03385},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1512.03385}, 
}

@misc{wu2018wassersteindivergencegans,
      title={Wasserstein Divergence for GANs}, 
      author={Jiqing Wu and Zhiwu Huang and Janine Thoma and Dinesh Acharya and Luc Van Gool},
      year={2018},
      eprint={1712.01026},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1712.01026}, 
}

@misc{mukherjee2019clusterganlatentspace,
      title={ClusterGAN : Latent Space Clustering in Generative Adversarial Networks}, 
      author={Sudipto Mukherjee and Himanshu Asnani and Eugene Lin and Sreeram Kannan},
      year={2019},
      eprint={1809.03627},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/1809.03627}, 
}

@article{smgan,
    author = {Wang, Nian and Cui, Zhigao and Su, Yanzhao and He, Chuan and Lan, Yunwei and Li, Aihua},
    title = {SMGAN: A self-modulated generative adversarial network for single image dehazing},
    journal = {AIP Advances},
    volume = {11},
    number = {8},
    pages = {085227},
    year = {2021},
    month = {08},
    issn = {2158-3226},
    doi = {10.1063/5.0059424},
    url = {https://doi.org/10.1063/5.0059424},
    eprint = {https://pubs.aip.org/aip/adv/article-pdf/doi/10.1063/5.0059424/12904020/085227\_1\_online.pdf},
}

@misc{nazeri2019edgeconnectgenerativeimageinpainting,
      title={EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning}, 
      author={Kamyar Nazeri and Eric Ng and Tony Joseph and Faisal Z. Qureshi and Mehran Ebrahimi},
      year={2019},
      eprint={1901.00212},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1901.00212}, 
}

@misc{yu2019freeformimageinpaintinggated,
      title={Free-Form Image Inpainting with Gated Convolution}, 
      author={Jiahui Yu and Zhe Lin and Jimei Yang and Xiaohui Shen and Xin Lu and Thomas Huang},
      year={2019},
      eprint={1806.03589},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1806.03589}, 
}

@Article{PEIPNet,
AUTHOR = {Ko, Jaekyun and Choi, Wanuk and Lee, Sanghwan},
TITLE = {PEIPNet: Parametric Efficient Image-Inpainting Network with Depthwise and Pointwise Convolution},
JOURNAL = {Sensors},
VOLUME = {23},
YEAR = {2023},
NUMBER = {19},
ARTICLE-NUMBER = {8313},
URL = {https://www.mdpi.com/1424-8220/23/19/8313},
ISSN = {1424-8220},
DOI = {10.3390/s23198313}
}

@article{DAHER2023102994,
title = {A Temporal Learning Approach to Inpainting Endoscopic Specularities and Its Effect on Image Correspondence},
journal = {Medical Image Analysis},
volume = {90},
pages = {102994},
year = {2023},
issn = {1361-8415},
doi = {https://doi.org/10.1016/j.media.2023.102994},
url = {https://www.sciencedirect.com/science/article/pii/S1361841523002542},
author = {Rema Daher and Francisco Vasconcelos and Danail Stoyanov},
keywords = {Surgical AI, Surgical Data Science, Endoscopy, Specular highlights, Inpainting, Temporal GANs, Transformers},
abstract = {Video streams are utilised to guide minimally-invasive surgery and diagnosis in a wide range of procedures, and many computer-assisted techniques have been developed to automatically analyse them. These approaches can provide additional information to the surgeon such as lesion detection, instrument navigation, or anatomy 3D shape modelling. However, the necessary image features to recognise these patterns are not always reliably detected due to the presence of irregular light patterns such as specular highlight reflections. In this paper, we aim at removing specular highlights from endoscopic videos using machine learning. We propose using a temporal generative adversarial network (GAN) to inpaint the hidden anatomy under specularities, inferring its appearance spatially and from neighbouring frames, where they are not present in the same location. This is achieved using in-vivo data from gastric endoscopy (Hyper Kvasir) in a fully unsupervised manner that relies on the automatic detection of specular highlights. System evaluations show significant improvements to other methods through direct comparison and ablation studies that depict the importance of the network’s temporal and transfer learning components. The generalisability of our system to different surgical setups and procedures was also evaluated qualitatively on in-vivo data of gastric endoscopy and ex-vivo porcine data (SERV-CT, SCARED). We also assess the effect of our method in comparison to other methods on computer vision tasks that underpin 3D reconstruction and camera motion estimation, namely stereo disparity, optical flow, and sparse point feature matching. These are evaluated quantitatively and qualitatively and results show a positive effect of our specular inpainting method on these tasks in a novel comprehensive analysis. Our code and dataset are made available at https://github.com/endomapper/Endo-STTN.}
}

@misc{wang2023diffusiongantraininggansdiffusion,
      title={Diffusion-GAN: Training GANs with Diffusion}, 
      author={Zhendong Wang and Huangjie Zheng and Pengcheng He and Weizhu Chen and Mingyuan Zhou},
      year={2023},
      eprint={2206.02262},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2206.02262}, 
}

@misc{sohldickstein2015deepunsupervisedlearningusing,
      title={Deep Unsupervised Learning using Nonequilibrium Thermodynamics}, 
      author={Jascha Sohl-Dickstein and Eric A. Weiss and Niru Maheswaranathan and Surya Ganguli},
      year={2015},
      eprint={1503.03585},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/1503.03585}, 
}