@String(PAMI  = {IEEE TPAMI})
@String(IJCV  = {IJCV})
@String(CVPR  = {CVPR})
@String(ICCV  = {ICCV})
@String(ECCV  = {ECCV})
@String(NIPS  = {NeurIPS})
@String(ICPR  = {ICPR})
@String(BMVC  =	{BMVC})
@String(TOG   = {ACM TOG})
@String(TIP   = {IEEE TIP})
@String(TVCG  = {IEEE TVCG})
@String(TCSVT = {IEEE TCSVT})
@String(TMM   =	{IEEE TMM})
@String(ACMMM = {ACM MM})
@String(ICME  =	{ICME})
@String(ICASSP=	{ICASSP})
@String(ICIP  = {ICIP})
@String(ACCV  = {ACCV})
@String(ICLR  = {ICLR})
@String(IJCAI = {IJCAI})
@String(PR = {PR})
@String(AAAI = {AAAI})
@String(CVPRW= {CVPRW})
@String(CSVT = {IEEE TCSVT})



@String(PAMI = {IEEE Trans. Pattern Anal. Mach. Intell.})
@String(IJCV = {Int. J. Comput. Vis.})
@String(CVPR= {IEEE Conf. Comput. Vis. Pattern Recog.})
@String(ICCV= {Int. Conf. Comput. Vis.})
@String(ECCV= {Eur. Conf. Comput. Vis.})
@String(NIPS= {Adv. Neural Inform. Process. Syst.})
@String(ICPR = {Int. Conf. Pattern Recog.})
@String(BMVC= {Brit. Mach. Vis. Conf.})
@String(TOG= {ACM Trans. Graph.})
@String(TIP  = {IEEE Trans. Image Process.})
@String(TVCG  = {IEEE Trans. Vis. Comput. Graph.})
@String(TMM  = {IEEE Trans. Multimedia})
@String(ACMMM= {ACM Int. Conf. Multimedia})
@String(ICME = {Int. Conf. Multimedia and Expo})
@String(ICASSP=	{ICASSP})
@String(ICIP = {IEEE Int. Conf. Image Process.})
@String(ACCV  = {ACCV})
@String(ICLR = {Int. Conf. Learn. Represent.})
@String(IJCAI = {IJCAI})
@String(PR   = {Pattern Recognition})
@String(AAAI = {AAAI})
@String(CVPRW= {IEEE Conf. Comput. Vis. Pattern Recog. Worksh.})
@String(CSVT = {IEEE Trans. Circuit Syst. Video Technol.})

@String(SPL	= {IEEE Sign. Process. Letters})
@String(VR   = {Vis. Res.})
@String(JOV	 = {J. Vis.})
@String(TVC  = {The Vis. Comput.})
@String(JCST  = {J. Comput. Sci. Tech.})
@String(CGF  = {Comput. Graph. Forum})
@String(CVM = {Computational Visual Media})



%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% INCREMENTAL LEARNING
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

@article{Yu2020SelfTrainingFC,
  title={Self-Training for Class-Incremental Semantic Segmentation},
  author={Lu Yu and Xialei Liu and Joost van de Weijer},
  journal={ArXiv},
  year={2020},
  volume={abs/2012.03362}
}

@article{hinton2015distilling,
  title={Distilling the Knowledge in a Neural Network},
  author={Geoffrey E. Hinton and Oriol Vinyals and Jeffrey Dean},
  journal={ArXiv},
  year={2015},
  volume={abs/1503.02531}
}

@article{McCloskey1989CatastrophicII,
  title={Catastrophic Interference in Connectionist Networks: The Sequential Learning Problem},
  author={M. McCloskey and N. Cohen},
  journal={Psychology of Learning and Motivation},
  year={1989},
  volume={24},
  pages={109-165}
}

@article{rehearsal,
    author = {Anthony Robins},
    title = {Catastrophic Forgetting, Rehearsal and Pseudorehearsal},
    journal = {Connection Science},
    volume = {7},
    number = {2},
    pages = {123-146},
    year  = {1995},
    publisher = {Taylor & Francis},
}

@ARTICLE{983933,
  author={Polikar, R. and Upda, L. and Upda, S.S. and Honavar, V.},
  journal={IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)}, 
  title={Learn++: an incremental learning algorithm for supervised neural networks}, 
  year={2001},
  volume={31},
  number={4},
  pages={497-508},
  doi={10.1109/5326.983933}
}

@inproceedings{Chefrour2019ANI,
  title={A Novel Incremental Learning Algorithm Based on Incremental Vector Support Machina and Incremental Neural Network Learn++},
  author={Aida Chefrour and L. Souici-Meslati and Iness Difi and Nesrine Bakkouche},
  year={2019}
}
@article{agarwal2020ailearn,
  title={AILearn: An Adaptive Incremental Learning Model for Spoof Fingerprint Detection},
  author={Shivang Agarwal and Ajita Rattani and C. Ravindranath Chowdary},
  journal={ArXiv},
  year={2020},
  volume={abs/2012.14639}
}

@article{roy2019treecnn,
  title={Tree-CNN: A hierarchical Deep Convolutional Neural Network for incremental learning},
  author={Deboleena Roy and Priyadarshini Panda and Kaushik Roy},
  journal={Neural networks : the official journal of the International Neural Network Society},
  year={2020},
  volume={121},
  pages={148-160}
}

@article{yoon2018lifelong,
  title={Lifelong Learning with Dynamically Expandable Networks},    author={Jaehong Yoon and Eunho Yang and Jeongtae Lee and Sung Ju Hwang},
  journal={ArXiv},
  year={2018},
  volume={abs/1708.01547}
}

@article{gepperth:hal-01418123,
  title={A Bio-Inspired Incremental Learning Architecture for Applied Perceptual Problems},
  author={Alexander Rainer Tassilo Gepperth and Cem Karaoguz},
  journal={Cognitive Computation},
  year={2016},
  volume={8},
  pages={924-934}
}

@article{camp2019selfnet,
  title={Self-Net: Lifelong Learning via Continual Self-Modeling},
  author={Jaya Krishna Mandivarapu and Blake Camp and Rolando Estrada},
  journal={Frontiers in Artificial Intelligence},
  year={2020},
  volume={3}
}

@inproceedings{68e0106dccca4881ba588fb29a034b32,
  title={Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability},
  author={Yang Yang and Da-Wei Zhou and De-Chuan Zhan and Hui Xiong and Yuan Jiang},
  journal={Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining},
  year={2019}
}

@article{Hu2019ANF,
  title={A Novel Feature Incremental Learning Method for Sensor-Based Activity Recognition},
  author={Chunyu Hu and Y. Chen and Xiaohui Peng and Han Yu and Chenlong Gao and L. Hu},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  year={2019},
  volume={31},
  pages={1038-1050}
}

@article{Sarwar_2020,
  title={Incremental Learning in Deep Convolutional Neural Networks Using Partial Network Sharing},
  author={Syed Shakib Sarwar and Aayush Ankit and Kaushik Roy},
  journal={IEEE Access},
  year={2020},
  volume={8},
  pages={4615-4628}
}

@article{Aljundi2017ExpertGL,
  title={Expert Gate: Lifelong Learning with a Network of Experts},
  author={Rahaf Aljundi and Punarjay Chakravarty and Tinne Tuytelaars},
  journal={2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2017},
  pages={7120-7129}
}

@article{kirkpatrick2017overcoming,
  title={Overcoming catastrophic forgetting in neural networks},
  author={James Kirkpatrick and Razvan Pascanu and Neil C. Rabinowitz and Joel Veness and Guillaume Desjardins and Andrei A. Rusu and Kieran Milan and John Quan and Tiago Ramalho and Agnieszka Grabska-Barwinska and Demis Hassabis and Claudia Clopath and Dharshan Kumaran and Raia Hadsell},
  journal={Proceedings of the National Academy of Sciences},
  year={2017},
  volume={114},
  pages={3521 - 3526}
}

@article{rusu2016progressive,
  title={Progressive Neural Networks},
  author={Andrei A. Rusu and Neil C. Rabinowitz and Guillaume Desjardins and Hubert Soyer and James Kirkpatrick and Koray Kavukcuoglu and Razvan Pascanu and Raia Hadsell},
  journal={ArXiv},
  year={2016},
  volume={abs/1606.04671}
}

@article{amer2019reducing,
  title={Reducing Catastrophic Forgetting in Modular Neural Networks by Dynamic Information Balancing},
  author={Mohammed Amer and T. Maul},
  journal={ArXiv},
  year={2019},
  volume={abs/1912.04508}
}

@article{zenke2017continual,
  title={Continual Learning Through Synaptic Intelligence},
  author={Friedemann Zenke and Ben Poole and Surya Ganguli},
  journal={Proceedings of machine learning research},
  year={2017},
  volume={70},
  pages={3987-3995}
}

@inproceedings{Chaudhry_2018,
  title={Riemannian walk for incremental learning: Understanding forgetting and intransigence},
  author={Chaudhry, Arslan and Dokania, Puneet K and Ajanthan, Thalaiyasingam and Torr, Philip HS},
  booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},
  pages={532--547},
  year={2018}
}

@inproceedings{aljundi2018memory,
  title={Memory Aware Synapses: Learning what (not) to forget},
  author={Rahaf Aljundi and Francesca Babiloni and Mohamed Elhoseiny and Marcus Rohrbach and Tinne Tuytelaars},
  booktitle={ECCV},
  year={2018}
}

@article{zeng2018continuous,
  title={Continuous Learning of Context-dependent Processing in Neural Networks},
  author={Guanxiong Zeng and Yang Chen and Bo Cui and Shan Yu},
  journal={ArXiv},
  year={2019},
  volume={abs/1810.01256}
}

@inproceedings{farajtabar2019orthogonal,
  title={Orthogonal Gradient Descent for Continual Learning},
  author={Mehrdad Farajtabar and Navid Azizan and Alexander Mott and Ang Li},
  booktitle={AISTATS},
  year={2020}
}

@article{lee2018overcoming,
  title={Overcoming Catastrophic Forgetting by Incremental Moment Matching},
  author={Sang-Woo Lee and Jin-Hwa Kim and Jaehyun Jun and Jung-Woo Ha and Byoung-Tak Zhang},
  journal={ArXiv},
  year={2017},
  volume={abs/1703.08475}
}

@article{Li2018LearningWF,
  title={Learning without Forgetting},
  author={Zhizhong Li and Derek Hoiem},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2018},
  volume={40},
  pages={2935-2947}
}

@article{Yao2019AdversarialFA,
  title={Adversarial Feature Alignment: Avoid Catastrophic Forgetting in Incremental Task Lifelong Learning},
  author={X. Yao and Tianchi Huang and Chenglei Wu and Ruixiao Zhang and L. Sun},
  journal={Neural Computation},
  year={2019},
  volume={31},
  pages={2266-2291}
}

@article{Kim2019IncrementalLW,
  title={Incremental Learning with Maximum Entropy Regularization: Rethinking Forgetting and Intransigence},
  author={Dahyun Kim and Jihwan Bae and Yeonsik Jo and Jonghyun Choi},
  journal={ArXiv},
  year={2019},
  volume={abs/1902.00829}
}

@inproceedings{Jung2018LessforgetfulLF,
  title={Less-forgetful Learning for Domain Expansion in Deep Neural Networks},
  author={Heechul Jung and Jeongwoo Ju and Minju Jung and Junmo Kim},
  booktitle={AAAI},
  year={2018}
}

@article{Lee2019OvercomingCF,
  title={Overcoming Catastrophic Forgetting With Unlabeled Data in the Wild},
  author={Kibok Lee and Kimin Lee and Jinwoo Shin and Honglak Lee},
  journal={2019 IEEE/CVF International Conference on Computer Vision (ICCV)},
  year={2019},
  pages={312-321}
}

@article{Rebuffi2017iCaRLIC,
  title={iCaRL: Incremental Classifier and Representation Learning},
  author={Sylvestre-Alvise Rebuffi and Alexander Kolesnikov and G. Sperl and Christoph H. Lampert},
  journal={2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2017},
  pages={5533-5542}
}

@article{Castro2018EndtoEndIL,
  title={End-to-End Incremental Learning},
  author={F. M. Castro and Manuel J. Mar{\'i}n-Jim{\'e}nez and Nicol{\'a}s Guil Mata and C. Schmid and Alahari Karteek},
  journal={ArXiv},
  year={2018},
  volume={abs/1807.09536}
}

@article{Wu2019LargeSI,
  title={Large Scale Incremental Learning},
  author={Y. Wu and Yan-Jia Chen and Lijuan Wang and Yuancheng Ye and Zicheng Liu and Yandong Guo and Yun Fu},
  journal={2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2019},
  pages={374-382}
}

@article{Wu2018IncrementalCL,
  title={Incremental Classifier Learning with Generative Adversarial Networks},
  author={Y. Wu and Y. Chen and Lijuan Wang and Yuancheng Ye and Zicheng Liu and Yandong Guo and Z. Zhang and Yun Fu},
  journal={ArXiv},
  year={2018},
  volume={abs/1802.00853}
}

@inproceedings{Odena2017ConditionalIS,
  title={Conditional Image Synthesis with Auxiliary Classifier GANs},
  author={Augustus Odena and Christopher Olah and Jonathon Shlens},
  booktitle={ICML},
  year={2017}
}

@article{Mellado2019SelfImprovingGA,
  title={Self-Improving Generative Artificial Neural Network for Pseudorehearsal Incremental Class Learning},
  author={D. Mellado and C. Saavedra and S. Chabert and Romina Torres and Rodrigo F. Salas},
  journal={Algorithms},
  year={2019},
  volume={12},
  pages={206}
}

@article{Ostapenko2019LearningTR,
  title={Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning},
  author={O. Ostapenko and M. Puscas and T. Klein and P. J{\"a}hnichen and Moin Nabi},
  journal={2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2019},
  pages={11313-11321}
}

@inproceedings{Shin2017ContinualLW,
  title={Continual Learning with Deep Generative Replay},
  author={Hanul Shin and J. Lee and Jaehong Kim and Jiwon Kim},
  booktitle={NIPS},
  year={2017}
}

@inproceedings{Hou2018LifelongLV,
  title={Lifelong Learning via Progressive Distillation and Retrospection},
  author={Saihui Hou and Xinyu Pan and Chen Change Loy and Zilei Wang and D. Lin},
  booktitle={ECCV},
  year={2018}
}

@article{Klingner2020ClassIncrementalLF,
  title={Class-Incremental Learning for Semantic Segmentation Re-Using Neither Old Data Nor Old Labels},
  author={Marvin Klingner and Andreas B{\"a}r and Philipp Donn and Tim Fingscheidt},
  journal={2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)},
  year={2020},
  pages={1-8}
}

@article{Michieli2021KnowledgeDF,
  title={Knowledge Distillation for Incremental Learning in Semantic Segmentation},
  author={Umberto Michieli and Pietro Zanuttigh},
  journal={Comput. Vis. Image Underst.},
  year={2021},
  volume={205},
  pages={103167}
}

@article{michieli2019incremental,
  title={Incremental Learning Techniques for Semantic Segmentation},
  author={Umberto Michieli and Pietro Zanuttigh},
  journal={2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)},
  year={2019},
  pages={3205-3212}
}


@article{Tasar2019IncrementalLF,
  title={Incremental Learning for Semantic Segmentation of Large-Scale Remote Sensing Data},
  author={O. Tasar and Y. Tarabalka and P. Alliez},
  journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  year={2019},
  volume={12},
  pages={3524-3537}
}

@article{kemker2018fearnet,
  title={FearNet: Brain-Inspired Model for Incremental Learning},
  author={Ronald Kemker and Christopher Kanan},
  journal={ArXiv},
  year={2018},
  volume={abs/1711.10563}
}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% OPEN WORLD
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

@InProceedings{Joseph_2021_CVPR,
    author    = {Joseph, K J and Khan, Salman and Khan, Fahad Shahbaz and Balasubramanian, Vineeth N},
    title     = {Towards Open World Object Detection},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month     = {June},
    year      = {2021},
    pages     = {5830-5840}
}

@article{Bendale2015TowardsOW,
  title={Towards Open World Recognition},
  author={Abhijit Bendale and Terrance E. Boult},
  journal={2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2015},
  pages={1893-1902}
}

@InProceedings{Cen_2021_ICCV,
    author    = {Cen, Jun and Yun, Peng and Cai, Junhao and Wang, Michael Yu and Liu, Ming},
    title     = {Deep Metric Learning for Open World Semantic Segmentation},
    booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
    month     = {October},
    year      = {2021},
    pages     = {15333-15342}
}

@article{shu2018unseen,
  title={Unseen Class Discovery in Open-world Classification},
  author={Lei Shu and Hu Xu and Bing Liu},
  journal={ArXiv},
  year={2018},
  volume={abs/1801.05609}
}

@article{Nakajima2019IncrementalCD,
  title={Incremental Class Discovery for Semantic Segmentation With RGBD Sensing},
  author={Yoshikatsu Nakajima and Byeongkeun Kang and H. Saito and Kris Kitani},
  journal={2019 IEEE/CVF International Conference on Computer Vision (ICCV)},
  year={2019},
  pages={972-981}
}

@article{He2021UnsupervisedCL,
  title={Unsupervised Continual Learning Via Pseudo Labels},
  author={Jiangpeng He and Feng Zhu},
  journal={ArXiv},
  year={2021},
  volume={abs/2104.07164}
}


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% DATASETS
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

@article{8237796,
  title={The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes},
  author={Gerhard Neuhold and Tobias Ollmann and Samuel Rota Bul{\`o} and Peter Kontschieder},
  journal={2017 IEEE International Conference on Computer Vision (ICCV)},
  year={2017},
  pages={5000-5009}
}
  
@article{Cordts2016TheCD,
  title={The Cityscapes Dataset for Semantic Urban Scene Understanding},
  author={Marius Cordts and Mohamed Omran and Sebastian Ramos and Timo Rehfeld and Markus Enzweiler and Rodrigo Benenson and Uwe Franke and Stefan Roth and Bernt Schiele},
  journal={2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2016},
  pages={3213-3223}
}

@article{geyer2020a2d2,
  title={A2D2: Audi Autonomous Driving Dataset},
  author={Jakob Geyer and Yohannes Kassahun and Mentar Mahmudi and Xavier Ricou and Rupesh Durgesh and Andrew S. Chung and Lorenz Hauswald and Viet Hoang Pham and Maximilian M{\"u}hlegg and Sebastian Dorn and Tiffany Fernandez and Martin J{\"a}nicke and Sudesh Ganapati Mirashi and Chiragkumar Savani and M. Sturm and Oleksandr Vorobiov and Martin Oelker and Sebastian Garreis and Peter Schuberth},
  journal={ArXiv},
  year={2020},
  volume={abs/2004.06320}
}


@inproceedings{deng2009imagenet,
  title={ImageNet: A large-scale hierarchical image database},
  author={Jia Deng and Wei Dong and Richard Socher and Li-Jia Li and K. Li and Li Fei-Fei},
  booktitle={CVPR},
  year={2009}
}

@article{yu2020bdd100k,
  title={BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning},
  author={Fisher Yu and Haofeng Chen and Xin Wang and Wenqi Xian and Yingying Chen and Fangchen Liu and Vashisht Madhavan and Trevor Darrell},
  journal={2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2020},
  pages={2633-2642}
}

@inproceedings{Dosovitskiy17,
  title = { {CARLA}: {An} Open Urban Driving Simulator},
  author = {Alexey Dosovitskiy and German Ros and Felipe Codevilla and Antonio Lopez and Vladlen Koltun},
  booktitle = {Proceedings of the 1st Annual Conference on Robot Learning},
  pages = {1--16},
  year = {2017}
}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% METASEG
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

@article{rottmann2019prediction,  
  title={Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities},
  author={Matthias Rottmann and Pascal Colling and Thomas-Paul Hack and Fabian H{\"u}ger and Peter Schlicht and Hanno Gottschalk},
  journal={2020 International Joint Conference on Neural Networks (IJCNN)},
  year={2020},
  pages={1-9}
}

@article{rottmann2019uncertainty,
  title={Uncertainty Measures and Prediction Quality Rating for the Semantic Segmentation of Nested Multi Resolution Street Scene Images},
  author={Matthias Rottmann and Marius Schubert},
  journal={2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year={2019},
  pages={1361-1369}
}

@article{Maag2020TimeDynamicEO,
  title={Time-Dynamic Estimates of the Reliability of Deep Semantic Segmentation Networks},
  author={Kira Maag and Matthias Rottmann and Hanno Gottschalk},
  journal={2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI)},
  year={2020},
  pages={502-509}
}

@article{oberdiek2020detection,
  title={Detection and Retrieval of Out-of-Distribution Objects in Semantic Segmentation},
  author={Philipp Oberdiek and Matthias Rottmann and Gernot A. Fink},
  journal={2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year={2020},
  pages={1331-1340}
}


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% CLUSTERING
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

@inproceedings{dbscan,
  title={A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise},
  author={Martin Ester and Hans-Peter Kriegel and J{\"o}rg Sander and Xiaowei Xu},
  booktitle={KDD},
  year={1996}
}

@inproceedings{kmeans,
  title={Some methods for classification and analysis of multivariate observations},
  author={J. MacQueen},
  booktitle={},
  year={1967}
}

@article{Maaten2008VisualizingDU,
  title={Visualizing Data using t-SNE},
  author={Laurens van der Maaten and Geoffrey E. Hinton},
  journal={Journal of Machine Learning Research},
  year={2008},
  volume={9},
  pages={2579-2605}
}

@article{FRSLIIIOL,
  title={LIII. On lines and planes of closest fit to systems of points in space},
  author={Karl {Pearson F.R.S.}},
  journal={Philosophical Magazine Series 1},
  year={},
  volume={2},
  pages={559-572}
}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Neural Networks
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

@article{chen2017deeplab,
  title={DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs},
  author={Liang-Chieh Chen and George Papandreou and Iasonas Kokkinos and Kevin P. Murphy and Alan Loddon Yuille},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2018},
  volume={40},
  pages={834-848}
}

@article{wang2020deep,
  title={Deep High-Resolution Representation Learning for Visual Recognition},
  author={Jingdong Wang and Ke Sun and Tianheng Cheng and Borui Jiang and Chaorui Deng and Yang Zhao and D. Liu and Yadong Mu and Mingkui Tan and Xinggang Wang and Wenyu Liu and Bin Xiao},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2021},
  volume={43},
  pages={3349-3364}
}

@article{huang2018densely,
  title={Densely Connected Convolutional Networks},
  author={Gao Huang and Zhuang Liu and Kilian Q. Weinberger},
  journal={2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2017},
  pages={2261-2269}
}

@article{chen2018encoderdecoder,
  title={Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation},
  author={Liang-Chieh Chen and Yukun Zhu and George Papandreou and Florian Schroff and Hartwig Adam},
  journal={ArXiv},
  year={2018},
  volume={abs/1802.02611}
}


@article{Zhao2017PyramidSP,
  title={Pyramid Scene Parsing Network},
  author={Hengshuang Zhao and Jianping Shi and Xiaojuan Qi and Xiaogang Wang and Jiaya Jia},
  journal={2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2017},
  pages={6230-6239}
}


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% ANOMALY DETECTION
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

@article{Akay2019SkipGANomalySC,
  title={Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detection},
  author={Samet Akçay and Amir Atapour-Abarghouei and T. Breckon},
  journal={2019 International Joint Conference on Neural Networks (IJCNN)},
  year={2019},
  pages={1-8}
}

@inproceedings{Baur2018DeepAM,
  title={Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images},
  author={Christoph Baur and Benedikt Wiestler and Shadi Albarqouni and Nassir Navab},
  booktitle={BrainLes@MICCAI},
  year={2018}
}
@article{Creusot2015RealtimeSO,
  title={Real-time small obstacle detection on highways using compressive RBM road reconstruction},
  author={Clement Creusot and Asim Munawar},
  journal={2015 IEEE Intelligent Vehicles Symposium (IV)},
  year={2015},
  pages={162-167}
}

@article{Lis2019DetectingTU,
  title={Detecting the Unexpected via Image Resynthesis},
  author={Krzysztof Lis and Krishna Kanth Nakka and Pascal Fua and Mathieu Salzmann},
  journal={2019 IEEE/CVF International Conference on Computer Vision (ICCV)},
  year={2019},
  pages={2152-2161}
}

@inproceedings{chan2021segmentmeifyoucan,
author = {Chan, Robin and Lis, Krzysztof and Uhlemeyer, Svenja and Blum, Hermann and Honari, Sina and Siegwart, Roland and Fua, Pascal and Salzmann, Mathieu and Rottmann, Matthias},
booktitle = {Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track},
eprint = {2104.14812},
primaryClass = {cs.CV},
title = {{SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation}},
year = {2021}
}

@inproceedings{Schlegl2017UnsupervisedAD,
  title={Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery},
  author={Thomas Schlegl and Philipp Seeb{\"o}ck and Sebastian M. Waldstein and Ursula Margarethe Schmidt-Erfurth and Georg Langs},
  booktitle={IPMI},
  year={2017}
}
@article{Zenati2018AdversariallyLA,
  title={Adversarially Learned Anomaly Detection},
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  year={2018},
  pages={727-736}
}

@article{Ngo2019FenceGT,
  title={Fence GAN: Towards Better Anomaly Detection},
  author={Cuong Phuc Ngo and Amadeus Aristo Winarto and Connie Khor Li Kou and Sojeong Park and Farhan Akram and Hwee Kuan Lee},
  journal={2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI)},
  year={2019},
  pages={141-148}
}

@inproceedings{Akay2018GANomalySA,
  title={GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training},
  author={Samet Akçay and Amir Atapour-Abarghouei and T. Breckon},
  booktitle={ACCV},
  year={2018}
}

@inproceedings{Hendrycks2017msp,
    author    = {Dan Hendrycks and Kevin Gimpel},
    title     = {A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks},
    booktitle = {5th International Conference on Learning Representations, {ICLR} 2017, Toulon, France, April 24-26, 2017, Conference Track Proceedings},
    year      = {2017}
}

@inproceedings{liang18odin,
    title={Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks},
    author={Shiyu Liang and Yixuan Li and R. Srikant},
    booktitle={International Conference on Learning Representations},
    year={2018}
}

@inproceedings{Kendall2017WhatUD,
  title={What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?},
  author={Alex Kendall and Yarin Gal},
  booktitle={NIPS},
  year={2017}
}

@InProceedings{gal2016dropout,
    title = 	 {Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning},
    author = 	 {Yarin Gal and Zoubin Ghahramani},
    booktitle = 	 {Proceedings of The 33rd International Conference on Machine Learning},
    pages = 	 {1050--1059},
    year = 	 {2016},
    volume = 	 {48},
    series = 	 {Proceedings of Machine Learning Research},
    address = 	 {New York, New York, USA},
    month = 	 {6},
    publisher = 	 {PMLR}
}

@article{Mukhoti2018EvaluatingBD,
  title={Evaluating Bayesian Deep Learning Methods for Semantic Segmentation},
  author={Jishnu Mukhoti and Yarin Gal},
  journal={ArXiv},
  year={2018},
  volume={abs/1811.12709}
}

@inproceedings{Lakshminarayanan2017SimpleAS,
  title={Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles},
  author={Balaji Lakshminarayanan and Alexander Pritzel and Charles Blundell},
  booktitle={NIPS},
  year={2017}
}

@InProceedings{Chan_2021_ICCV,
    author    = {Chan, Robin and Rottmann, Matthias and Gottschalk, Hanno},
    title     = {Entropy Maximization and Meta Classification for Out-of-Distribution Detection in Semantic Segmentation},
    booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
    month     = {October},
    year      = {2021},
    pages     = {5128-5137}
}

@article{Devries2018LearningCF,
  title={Learning Confidence for Out-of-Distribution Detection in Neural Networks},
  author={Terrance Devries and Graham W. Taylor},
  journal={ArXiv},
  year={2018},
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}


@article{Vasilev2018qSpaceND,
  title={q-Space Novelty Detection with Variational Autoencoders},
  author={Aleksei Vasilev and Vladimir Golkov and Ilona Lipp and Eleonora Sgarlata and Valentina Tomassini and Derek K. Jones and Daniel Cremers},
  journal={ArXiv},
  year={2018},
  volume={abs/1806.02997}
}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% CLASS DISCOVERY
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%



@article{Niu2021SPICESP,
  title={SPICE: Semantic Pseudo-labeling for Image Clustering},
  author={Chuang Niu and Ge Wang},
  journal={ArXiv},
  year={2021},
  volume={abs/2103.09382}
}

@inproceedings{Mahon2021SelectivePC,
  title={Selective Pseudo-label Clustering},
  author={Louis Mahon and Thomas Lukasiewicz},
  booktitle={KI},
  year={2021}
}

@article{Xie2016UnsupervisedDE,
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  author={Junyuan Xie and Ross B. Girshick and Ali Farhadi},
  journal={ArXiv},
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  volume={abs/1511.06335}
}

@article{Li2018DiscriminativelyBI,
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  journal={ArXiv},
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  volume={abs/1703.07980}
}

@inproceedings{Yang2017TowardsKS,
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  booktitle={ICML},
  year={2017}
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@inproceedings{Tian2017DeepClusterAG,
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  author={Kai Tian and Shuigeng Zhou and Jihong Guan},
  booktitle={ECML/PKDD},
  year={2017}
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@article{Zhang2019SelfSupervisedCS,
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  journal={2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2019},
  pages={5468-5477}
}

@article{Dizaji2017DeepCV,
  title={Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization},
  author={Kamran Ghasedi Dizaji and Amirhossein Herandi and Cheng Deng and Weidong (Tom) Cai and Heng Huang},
  journal={2017 IEEE International Conference on Computer Vision (ICCV)},
  year={2017},
  pages={5747-5756}
}

@inproceedings{Jiang2017VariationalDE,
  title={Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering},
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  booktitle={IJCAI},
  year={2017}
}

@article{Dilokthanakul2016DeepUC,
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  journal={ArXiv},
  year={2016},
  volume={abs/1611.02648}
}

@article{Zhou2018DeepAS,
  title={Deep Adversarial Subspace Clustering},
  author={Pan Zhou and Yunqing Hou and Jiashi Feng},
  journal={2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2018},
  pages={1596-1604}
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@INPROCEEDINGS{9517087,  
    author={Liu, Jiaxin and Wang, Dongwei and Yu, Siquan and Li, Xueliang and Han, Zhi and Tang, Yandong},  
    booktitle={2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)},   
    title={A Survey of Image Clustering: Taxonomy and Recent Methods},   
    year={2021},  volume={},  number={},  pages={375-380}
}


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% ETC
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

@article{Janai2020ComputerVF,
  title={Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art},
  author={Joel Janai and Fatma G{\"u}ney and Aseem Behl and Andreas Geiger},
  journal={Found. Trends Comput. Graph. Vis.},
  year={2020},
  volume={12},
  pages={1-308}
}

@INPROCEEDINGS{1434171,  
    author={Ma Yi-de and Liu Qing and Qian Zhi-bai},  
    booktitle={Proceedings of 2004 International Symposium on Intelligent Multimedia, Video and Speech Processing, 2004.},   
    title={Automated image segmentation using improved PCNN model based on cross-entropy}, year={2004}, 
    pages={743-746},  
    doi={10.1109/ISIMP.2004.1434171}
}


@article{Zhu2019ImprovingSS,
  title={Improving Semantic Segmentation via Video Propagation and Label Relaxation},
  author={Yi Zhu and Karan Sapra and Fitsum A. Reda and Kevin J. Shih and S. Newsam and Andrew Tao and Bryan Catanzaro},
  journal={2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2019},
  pages={8848-8857}
}

@misc{kowol2022aeye,
      title={A-Eye: Driving with the Eyes of AI for Corner Case Generation}, 
      author={Kamil Kowol and Stefan Bracke and Hanno Gottschalk},
      year={2022},
      eprint={2202.10803},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}
