@inproceedings{lai2021semi,
	title={Semi-supervised semantic segmentation with directional context-aware consistency},
	author={Lai, Xin and Tian, Zhuotao and Jiang, Li and Liu, Shu and Zhao, Hengshuang and Wang, Liwei and Jia, Jiaya},
	booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
	pages={1205--1214},
	year={2021}
}

@inproceedings{ouali2020semi,
	title={Semi-supervised semantic segmentation with cross-consistency training},
	author={Ouali, Yassine and Hudelot, C{\'e}line and Tami, Myriam},
	booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
	pages={12674--12684},
	year={2020}
}


@article{french2019semi,
	title={Semi-supervised semantic segmentation needs strong, varied perturbations},
	author={French, Geoff and Laine, Samuli and Aila, Timo and Mackiewicz, Michal and Finlayson, Graham},
	journal={arXiv preprint arXiv:1906.01916},
	year={2019}
}

@inproceedings{ke2020guided,
	title={Guided collaborative training for pixel-wise semi-supervised learning},
	author={Ke, Zhanghan and Qiu, Di and Li, Kaican and Yan, Qiong and Lau, Rynson WH},
	booktitle={Computer Vision--ECCV 2020: 16th European Conference, Glasgow, UK, August 23--28, 2020, Proceedings, Part XIII 16},
	pages={429--445},
	year={2020},
	organization={Springer}
}

@inproceedings{bellver2019budget,
	title={Budget-aware semi-supervised semantic and instance segmentation},
	author={Bellver Bueno, M{\'\i}riam and Salvador Aguilera, Amaia and Torres Vi{\~n}als, Jordi and Gir{\'o} Nieto, Xavier},
	booktitle={The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2019},
	pages={93--102},
	year={2019}
}


@inproceedings{fan2022ucc,
	title={Ucc: Uncertainty guided cross-head co-training for semi-supervised semantic segmentation},
	author={Fan, Jiashuo and Gao, Bin and Jin, Huan and Jiang, Lihui},
	booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
	pages={9947--9956},
	year={2022}
}

@inproceedings{liu2022perturbed,
	title={Perturbed and strict mean teachers for semi-supervised semantic segmentation},
	author={Liu, Yuyuan and Tian, Yu and Chen, Yuanhong and Liu, Fengbei and Belagiannis, Vasileios and Carneiro, Gustavo},
	booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
	pages={4258--4267},
	year={2022}
}

@article{jaiswal2020survey,
	title={A survey on contrastive self-supervised learning},
	author={Jaiswal, Ashish and Babu, Ashwin Ramesh and Zadeh, Mohammad Zaki and Banerjee, Debapriya and Makedon, Fillia},
	journal={Technologies},
	volume={9},
	number={1},
	pages={2},
	year={2020},
	publisher={MDPI}
}

@inproceedings{chen2020simple,
	title={A simple framework for contrastive learning of visual representations},
	author={Chen, Ting and Kornblith, Simon and Norouzi, Mohammad and Hinton, Geoffrey},
	booktitle={International conference on machine learning},
	pages={1597--1607},
	year={2020},
	organization={PMLR}
}

@inproceedings{wang2021dense,
	title={Dense contrastive learning for self-supervised visual pre-training},
	author={Wang, Xinlong and Zhang, Rufeng and Shen, Chunhua and Kong, Tao and Li, Lei},
	booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
	pages={3024--3033},
	year={2021}
}

@inproceedings{he2020momentum,
	title={Momentum contrast for unsupervised visual representation learning},
	author={He, Kaiming and Fan, Haoqi and Wu, Yuxin and Xie, Saining and Girshick, Ross},
	booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
	pages={9729--9738},
	year={2020}
}

@inproceedings{zhou2021c3,
	title={C3-semiseg: Contrastive semi-supervised segmentation via cross-set learning and dynamic class-balancing},
	author={Zhou, Yanning and Xu, Hang and Zhang, Wei and Gao, Bin and Heng, Pheng-Ann},
	booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
	pages={7036--7045},
	year={2021}
}


@inproceedings{zhong2021pixel,
	title={Pixel contrastive-consistent semi-supervised semantic segmentation},
	author={Zhong, Yuanyi and Yuan, Bodi and Wu, Hong and Yuan, Zhiqiang and Peng, Jian and Wang, Yu-Xiong},
	booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
	pages={7273--7282},
	year={2021}
}

@inproceedings{kim2023devil,
	title={The Devil is in the Points: Weakly Semi-Supervised Instance Segmentation via Point-Guided Mask Representation},
	author={Kim, Beomyoung and Jeong, Joonhyun and Han, Dongyoon and Hwang, Sung Ju},
	booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
	pages={11360--11370},
	year={2023}
}

@inproceedings{zhou2020learning,
	title={Learning saliency propagation for semi-supervised instance segmentation},
	author={Zhou, Yanzhao and Wang, Xin and Jiao, Jianbin and Darrell, Trevor and Yu, Fisher},
	booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
	pages={10307--10316},
	year={2020}
}


@article{he2015spatial,
	title={Spatial pyramid pooling in deep convolutional networks for visual recognition},
	author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
	journal={IEEE transactions on pattern analysis and machine intelligence},
	volume={37},
	number={9},
	pages={1904--1916},
	year={2015},
	publisher={IEEE}
}


@inproceedings{redmon2016you,
	title={You only look once: Unified, real-time object detection},
	author={Redmon, Joseph and Divvala, Santosh and Girshick, Ross and Farhadi, Ali},
	booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
	pages={779--788},
	year={2016}
}

@inproceedings{redmon2017yolo9000,
	title={YOLO9000: better, faster, stronger},
	author={Redmon, Joseph and Farhadi, Ali},
	booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
	pages={7263--7271},
	year={2017}
}

@article{ge2021yolox,
	title={Yolox: Exceeding yolo series in 2021},
	author={Ge, Zheng and Liu, Songtao and Wang, Feng and Li, Zeming and Sun, Jian},
	journal={arXiv preprint arXiv:2107.08430},
	year={2021}
}


@article{stringer2021cellpose,
	title={Cellpose: a generalist algorithm for cellular segmentation},
	author={Stringer, Carsen and Wang, Tim and Michaelos, Michalis and Pachitariu, Marius},
	journal={Nature methods},
	volume={18},
	number={1},
	pages={100--106},
	year={2021},
	publisher={Nature Publishing Group US New York}
}

@inproceedings{he2021cdnet,
	title={Cdnet: Centripetal direction network for nuclear instance segmentation},
	author={He, Hongliang and Huang, Zhongyi and Ding, Yao and Song, Guoli and Wang, Lin and Ren, Qian and Wei, Pengxu and Gao, Zhiqiang and Chen, Jie},
	booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
	pages={4026--4035},
	year={2021}
}

@inproceedings{graham2018sams,
	title={SAMS-NET: Stain-aware multi-scale network for instance-based nuclei segmentation in histology images},
	author={Graham, Simon and Rajpoot, Nasir M},
	booktitle={2018 IEEE 15th international symposium on biomedical imaging (ISBI 2018)},
	pages={590--594},
	year={2018},
	organization={IEEE}
}

@article{zhao2020triple,
	title={Triple U-net: Hematoxylin-aware nuclei segmentation with progressive dense feature aggregation},
	author={Zhao, Bingchao and Chen, Xin and Li, Zhi and Yu, Zhiwen and Yao, Su and Yan, Lixu and Wang, Yuqian and Liu, Zaiyi and Liang, Changhong and Han, Chu},
	journal={Medical Image Analysis},
	volume={65},
	pages={101786},
	year={2020},
	publisher={Elsevier}
}

@inproceedings{wu2022cross,
	title={Cross-patch dense contrastive learning for semi-supervised segmentation of cellular nuclei in histopathologic images},
	author={Wu, Huisi and Wang, Zhaoze and Song, Youyi and Yang, Lin and Qin, Jing},
	booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
	pages={11666--11675},
	year={2022}
}

@inproceedings{alonso2021semi,
	title={Semi-supervised semantic segmentation with pixel-level contrastive learning from a class-wise memory bank},
	author={Alonso, Inigo and Sabater, Alberto and Ferstl, David and Montesano, Luis and Murillo, Ana C},
	booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
	pages={8219--8228},
	year={2021}
}

@article{chen2020big,
	title={Big self-supervised models are strong semi-supervised learners},
	author={Chen, Ting and Kornblith, Simon and Swersky, Kevin and Norouzi, Mohammad and Hinton, Geoffrey E},
	journal={Advances in neural information processing systems},
	volume={33},
	pages={22243--22255},
	year={2020}
}


@inproceedings{chen2021exploring,
	title={Exploring simple siamese representation learning},
	author={Chen, Xinlei and He, Kaiming},
	booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
	pages={15750--15758},
	year={2021}
}

@article{grill2020bootstrap,
	title={Bootstrap your own latent-a new approach to self-supervised learning},
	author={Grill, Jean-Bastien and Strub, Florian and Altch{\'e}, Florent and Tallec, Corentin and Richemond, Pierre and Buchatskaya, Elena and Doersch, Carl and Avila Pires, Bernardo and Guo, Zhaohan and Gheshlaghi Azar, Mohammad and others},
	journal={Advances in neural information processing systems},
	volume={33},
	pages={21271--21284},
	year={2020}
}

@inproceedings{wang2022contrastmask,
	title={Contrastmask: Contrastive learning to segment every thing},
	author={Wang, Xuehui and Zhao, Kai and Zhang, Ruixin and Ding, Shouhong and Wang, Yan and Shen, Wei},
	booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
	pages={11604--11613},
	year={2022}
}

@article{mahbod2021cryonuseg,
	title={CryoNuSeg: A dataset for nuclei instance segmentation of cryosectioned H\&E-stained histological images},
	author={Mahbod, Amirreza and Schaefer, Gerald and Bancher, Benjamin and L{\"o}w, Christine and Dorffner, Georg and Ecker, Rupert and Ellinger, Isabella},
	journal={Computers in biology and medicine},
	volume={132},
	pages={104349},
	year={2021},
	publisher={Elsevier}
}

@article{da2022digestpath,
	title={DigestPath: A benchmark dataset with challenge review for the pathological detection and segmentation of digestive-system},
	author={Da, Qian and Huang, Xiaodi and Li, Zhongyu and Zuo, Yanfei and Zhang, Chenbin and Liu, Jingxin and Chen, Wen and Li, Jiahui and Xu, Dou and Hu, Zhiqiang and others},
	journal={Medical Image Analysis},
	volume={80},
	pages={102485},
	year={2022},
	publisher={Elsevier}
}

@inproceedings{graham2021lizard,
	title={Lizard: a large-scale dataset for colonic nuclear instance segmentation and classification},
	author={Graham, Simon and Jahanifar, Mostafa and Azam, Ayesha and Nimir, Mohammed and Tsang, Yee-Wah and Dodd, Katherine and Hero, Emily and Sahota, Harvir and Tank, Atisha and Benes, Ksenija and others},
	booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
	pages={684--693},
	year={2021}
}


@inproceedings{kirillov2019panoptic,
	title={Panoptic segmentation},
	author={Kirillov, Alexander and He, Kaiming and Girshick, Ross and Rother, Carsten and Doll{\'a}r, Piotr},
	booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
	pages={9404--9413},
	year={2019}
}

@article{vu2019methods,
	title={Methods for segmentation and classification of digital microscopy tissue images},
	author={Vu, Quoc Dang and Graham, Simon and Kurc, Tahsin and To, Minh Nguyen Nhat and Shaban, Muhammad and Qaiser, Talha and Koohbanani, Navid Alemi and Khurram, Syed Ali and Kalpathy-Cramer, Jayashree and Zhao, Tianhao and others},
	journal={Frontiers in bioengineering and biotechnology},
	pages={53},
	year={2019},
	publisher={Frontiers}
}

@article{kumar2017dataset,
	title={A dataset and a technique for generalized nuclear segmentation for computational pathology},
	author={Kumar, Neeraj and Verma, Ruchika and Sharma, Sanuj and Bhargava, Surabhi and Vahadane, Abhishek and Sethi, Amit},
	journal={IEEE transactions on medical imaging},
	volume={36},
	number={7},
	pages={1550--1560},
	year={2017},
	publisher={IEEE}
}

@article{nishimura2021weakly,
	title={Weakly supervised cell instance segmentation under various conditions},
	author={Nishimura, Kazuya and Wang, Chenyang and Watanabe, Kazuhide and Bise, Ryoma and others},
	journal={Medical Image Analysis},
	volume={73},
	pages={102182},
	year={2021},
	publisher={Elsevier}
}

@article{qu2020weakly,
	title={Weakly supervised deep nuclei segmentation using partial points annotation in histopathology images},
	author={Qu, Hui and Wu, Pengxiang and Huang, Qiaoying and Yi, Jingru and Yan, Zhennan and Li, Kang and Riedlinger, Gregory M and De, Subhajyoti and Zhang, Shaoting and Metaxas, Dimitris N},
	journal={IEEE transactions on medical imaging},
	volume={39},
	number={11},
	pages={3655--3666},
	year={2020},
	publisher={IEEE}
}


@inproceedings{chen2016dcan,
	title={DCAN: deep contour-aware networks for accurate gland segmentation},
	author={Chen, Hao and Qi, Xiaojuan and Yu, Lequan and Heng, Pheng-Ann},
	booktitle={Proceedings of the IEEE conference on Computer Vision and Pattern Recognition},
	pages={2487--2496},
	year={2016}
}

@article{graham2019hover,
  title={Hover-net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images},
  author={Graham, Simon and Vu, Quoc Dang and Raza, Shan E Ahmed and Azam, Ayesha and Tsang, Yee Wah and Kwak, Jin Tae and Rajpoot, Nasir},
  journal={Medical image analysis},
  volume={58},
  pages={101563},
  year={2019},
  publisher={Elsevier}
}


@inproceedings{yang2023revisiting,
	title={Revisiting weak-to-strong consistency in semi-supervised semantic segmentation},
	author={Yang, Lihe and Qi, Lei and Feng, Litong and Zhang, Wayne and Shi, Yinghuan},
	booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
	pages={7236--7246},
	year={2023}
}

@inproceedings{qiao2023fuzzy,
	title={Fuzzy Positive Learning for Semi-Supervised Semantic Segmentation},
	author={Qiao, Pengchong and Wei, Zhidan and Wang, Yu and Wang, Zhennan and Song, Guoli and Xu, Fan and Ji, Xiangyang and Liu, Chang and Chen, Jie},
	booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
	pages={15465--15474},
	year={2023}
}

@inproceedings{zhou2020deep,
	title={Deep semi-supervised knowledge distillation for overlapping cervical cell instance segmentation},
	author={Zhou, Yanning and Chen, Hao and Lin, Huangjing and Heng, Pheng-Ann},
	booktitle={Medical Image Computing and Computer Assisted Intervention--MICCAI 2020: 23rd International Conference, Lima, Peru, October 4--8, 2020, Proceedings, Part I 23},
	pages={521--531},
	year={2020},
	organization={Springer}
}

@inproceedings{jiang2023donet,
	title={DoNet: Deep De-overlapping Network for Cytology Instance Segmentation},
	author={Jiang, Hao and Zhang, Rushan and Zhou, Yanning and Wang, Yumeng and Chen, Hao},
	booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
	pages={15641--15650},
	year={2023}
}


@inproceedings{wang2022noisy,
	title={Noisy Boundaries: Lemon or Lemonade for Semi-supervised Instance Segmentation?},
	author={Wang, Zhenyu and Li, Yali and Wang, Shengjin},
	booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
	pages={16826--16835},
	year={2022}
}

@article{tarvainen2017mean,
	title={Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results},
	author={Tarvainen, Antti and Valpola, Harri},
	journal={Advances in neural information processing systems},
	volume={30},
	year={2017}
}

@article{oliver2018realistic,
	title={Realistic evaluation of deep semi-supervised learning algorithms},
	author={Oliver, Avital and Odena, Augustus and Raffel, Colin A and Cubuk, Ekin Dogus and Goodfellow, Ian},
	journal={Advances in neural information processing systems},
	volume={31},
	year={2018}
}

@inproceedings{he2017mask,
	title={Mask r-cnn},
	author={He, Kaiming and Gkioxari, Georgia and Doll{\'a}r, Piotr and Girshick, Ross},
	booktitle={Proceedings of the IEEE international conference on computer vision},
	pages={2961--2969},
	year={2017}
}

@article{khened2021generalized,
  title={A generalized deep learning framework for whole-slide image segmentation and analysis},
  author={Khened, Mahendra and Kori, Avinash and Rajkumar, Haran and Krishnamurthi, Ganapathy and Srinivasan, Balaji},
  journal={Scientific reports},
  volume={11},
  number={1},
  pages={11579},
  year={2021},
  publisher={Nature Publishing Group UK London}
}

@article{hollandi2022nucleus,
  title={Nucleus segmentation: towards automated solutions},
  author={Hollandi, Reka and Moshkov, Nikita and Paavolainen, Lassi and Tasnadi, Ervin and Piccinini, Filippo and Horvath, Peter},
  journal={Trends in Cell Biology},
  year={2022},
  publisher={Elsevier}
}

@inproceedings{hu2023pseudo,
  title={Pseudo-label alignment for semi-supervised instance segmentation},
  author={Hu, Jie and Chen, Chen and Cao, Liujuan and Zhang, Shengchuan and Shu, Annan and Jiang, Guannan and Ji, Rongrong},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={16337--16347},
  year={2023}
}

@article{zhao2021net,
  title={Al-net: Attention learning network based on multi-task learning for cervical nucleus segmentation},
  author={Zhao, Jing and He, Yong-Jun and Zhao, Si-Qi and Huang, Jin-Jie and Zuo, Wang-Meng},
  journal={IEEE Journal of Biomedical and Health Informatics},
  volume={26},
  number={6},
  pages={2693--2702},
  year={2021},
  publisher={IEEE}
}

@article{zhang2024seine,
  title={SEINE: Structure Encoding and Interaction Network for Nuclei Instance Segmentation},
  author={Zhang, Ye and Cai, Linghan and Wang, Ziyue and Zhang, Yongbing},
  journal={arXiv preprint arXiv:2401.09773},
  year={2024}
}

@article{ahmad2023dan,
  title={DAN-NucNet: A dual attention based framework for nuclei segmentation in cancer histology images under wild clinical conditions},
  author={Ahmad, Ibtihaj and Xia, Yong and Cui, Hengfei and Islam, Zain Ul},
  journal={Expert Systems with Applications},
  volume={213},
  pages={118945},
  year={2023},
  publisher={Elsevier}
}

@article{jin2024inter,
  title={Inter-and intra-uncertainty based feature aggregation model for semi-supervised histopathology image segmentation},
  author={Jin, Qiangguo and Cui, Hui and Sun, Changming and Song, Yang and Zheng, Jiangbin and Cao, Leilei and Wei, Leyi and Su, Ran},
  journal={Expert Systems with Applications},
  volume={238},
  pages={122093},
  year={2024},
  publisher={Elsevier}
}

@article{van2020survey,
  title={A survey on semi-supervised learning},
  author={Van Engelen, Jesper E and Hoos, Holger H},
  journal={Machine learning},
  volume={109},
  number={2},
  pages={373--440},
  year={2020},
  publisher={Springer}
}

@article{naylor2018segmentation,
	title={Segmentation of nuclei in histopathology images by deep regression of the distance map},
	author={Naylor, Peter and La{\'e}, Marick and Reyal, Fabien and Walter, Thomas},
	journal={IEEE transactions on medical imaging},
	volume={38},
	number={2},
	pages={448--459},
	year={2018},
	publisher={IEEE}
}

@article{reddy2018semi,
  title={Semi-supervised learning: A brief review},
  author={Reddy, YCAP and Viswanath, P and Reddy, B Eswara},
  journal={Int. J. Eng. Technol},
  volume={7},
  number={1.8},
  pages={81},
  year={2018}
}

@article{zhang2024dawn,
  title={DAWN: Domain-Adaptive Weakly Supervised Nuclei Segmentation via Cross-Task Interactions},
  author={Zhang, Ye and Wang, Yifeng and Fang, Zijie and Bian, Hao and Cai, Linghan and Wang, Ziyue and Zhang, Yongbing},
  journal={arXiv preprint arXiv:2404.14956},
  year={2024}
}
