Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/junha1125/awesome-test-time-adaptation

awesome-test-time-adaptation
https://github.com/junha1125/awesome-test-time-adaptation

List: awesome-test-time-adaptation

Last synced: 16 days ago
JSON representation

awesome-test-time-adaptation

Awesome Lists containing this project

README 

        
# Awesome Test-time Adaptation [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)



## Contributing

Please help contribute this list by contacting [me](https://github.com/junha1125) or add `pull request`



Markdown format:

```markdown

- Paper Name. 

  [[pdf]](link) 

  [[code]](link)

  - Author 1, Author 2, and Author 3. *Conference Year*

```



## Table of Contents

- [Requisite](#Requisite)

- [2021,2022](#2021,2022)



## Requisite



1. Tent: Fully Test-time Adaptation by Entropy Minimization ([pdf](https://arxiv.org/abs/2006.10726))

   - Dequan Wang, Evan Shelhamer, Shaoteng Liu, Bruno Olshausen, Trevor Darrell, ICLR Spotlight, 2021

2. Test-Time Training with Self-Supervision for Generalization under Distribution Shifts ([pdf](https://arxiv.org/abs/1909.13231))

   - Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei A. Efros, Moritz Hardt, ICML, 2020



## 2021,2022



1. AUGCO Augmentation Consistency-guided Self-training ([pdf](https://arxiv.org/abs/2107.10140))

   - Viraj Prabhu, Shivam Khare, Deeksha Kartik, Judy Hoffman, arXiv, 2021

2. Adaptive generalization for semantic segmentation ([pdf](https://openreview.net/forum?id=1O5UK-zoK8g))

   - Sherwin Bahmani, Oliver Hahn, Eduard Sebastian Zamfir, Nikita Araslanov, Stefan Roth, ICLR submitted, 2022

3. Continual Test-Time Domain Adaptation ([pdf](https://arxiv.org/abs/2203.13591))

   - Qin Wang, Olga Fink, Luc Van Gool, Dengxin Dai, CVPR, 2022

4. Contrastive Test-Time Adaptation ([pdf](https://arxiv.org/abs/2204.10377))

   - Dian Chen, Dequan Wang, Trevor Darrell, Sayna Ebrahimi, CVPR, 2022

5. Covariance-aware Feature Alignment with Pre-computed Source Statistics for Test-time Adaptation ([pdf](https://arxiv.org/abs/2204.13263))

   - Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai, arXiv, 2022

6. MEMO Test Time Robustness via Adaptation and Augmentation / Test Time Robustification of Deep Models via Adaptation and Augmentation ([pdf](https://openreview.net/forum?id=J1uOGgf-bP))

   - Marvin Mengxin Zhang, Sergey Levine, Chelsea Finn, ICLR submitted, 2022

7. MixNorm Test-time adaptation Through Online Normalization Estimation ([pdf](https://openreview.net/forum?id=EPIeOo3ql96))

   - Xuefeng Hu, Mustafa Uzunbas, Bor-Chun Chen, Rui Wang, Ashish Shah, Ram Nevatia, Ser-Nam Lim, ICLR submitted, 2022

8. Multi-Modal Test-time adaptation for 3D Semantic Segmentation ([pdf](https://arxiv.org/abs/2204.12667))

   - Inkyu Shin, Yi-Hsuan Tsai, Bingbing Zhuang, Samuel Schulter, Buyu Liu, Sparsh Garg, In So Kweon, Kuk-Jin Yoon, CVPR, 2022

9. Parameter-free Online Test-time Adaptation ([pdf](https://arxiv.org/abs/2201.05718))

   - Malik Boudiaf, Romain Mueller, Ismail Ben Ayed, Luca Bertinetto, CVPR oral, 2022

10. Single Image Test-time Adaptation ([pdf](https://arxiv.org/abs/2112.02355))

   - Ansh Khurana, Sujoy Paul, Piyush Rai, Soma Biswas, Gaurav Aggarwal, arXiv, 2021

11. Test-time adaptation for Event-Based Object Recognition ([pdf](https://arxiv.org/abs/2203.12247))

    - Junho Kim, Inwoo Hwang, Young Min Kim, CVPR, 2022

12. Sketch3T: Test-Time Training for Zero-Shot SBIR ([pdf](https://arxiv.org/pdf/2203.14691.pdf))

    - Aneeshan Sain, Ayan Kumar Bhunia, Vaishnav Potlapalli, Pinaki Nath Chowdhury, CVPR, 2022

13. Test-time adaptation to Distribution Shift by Confidence Maximization and Input Transformation ([pdf](https://openreview.net/forum?id=GOfGGASIUkg))

    - Chaithanya Kumar Mummadi, Robin Hutmacher, Kilian Rambach, Evgeny Levinkov, Thomas Brox, Jan Hendrik Metzen, NeurIPS submitted, 2021

14. Test-Time Classifier Adjustment Module for Domain Generalization ([pdf](https://proceedings.neurips.cc/paper/2021/hash/1415fe9fea0fa1e45dddcff5682239a0-Abstract.html))

    - Yusuke Iwasawa, Yutaka Matsuo, NeurIPS, 2021

15. Test-time Batch Statistics Calibration for Covariate Shift ([pdf](https://arxiv.org/abs/2110.04065))

    - Fuming You, Jingjing Li, Zhou Zhao, arXiv, 2021

16. When Does Self-Supervised Test-Time Training Fail or Thrive? ([pdf](https://proceedings.neurips.cc/paper/2021/file/b618c3210e934362ac261db280128c22-Paper.pdf))

    - Yuejiang Liu, Parth Kothari, Bastien van Delft, NeurIPS, 2021

17. Adaptive Denoising via GainTuning ([pdf](https://arxiv.org/abs/2107.12815))

    - Sreyas Mohan, Joshua L. Vincent, Ramon Manzorro, Peter A. Crozier, Eero P. Simoncelli, Carlos Fernandez-Granda, arXiv, 2021

18. Continual Active Adaptation to Evolving Distributional Shifts ([pdf](https://openaccess.thecvf.com/content/CVPR2022W/RoSe/papers/Machireddy_Continual_Active_Adaptation_to_Evolving_Distributional_Shifts_CVPRW_2022_paper.pdf))

    - Amrutha Machireddy, Ranganath Krishnan, Nilesh Ahuja, Omesh Tickoo, CVPR, 2022

19. Continual BatchNorm Adaptation (CBNA) for Semantic Segmentation ([pdf](https://arxiv.org/abs/2203.01074))

    - Marvin Klingner, Mouadh Ayache, Tim Fingscheidt, arXiv, 2022

20. DistillAdapt- Source-Free Active Visual Domain Adaptation ([pdf](https://arxiv.org/pdf/2205.12840.pdf))

    - Divya Kothandaraman, Sumit Shekhar, Abhilasha Sancheti, Manoj Ghuhan, Tripti Shukla, Dinesh Manocha, arXiv, 2022

21. Efficient Test Time Adapter Ensembling for Low-resource Language Varieties ([pdf](https://aclanthology.org/2021.findings-emnlp.63.pdf))

    - Xinyi Wang, Yulia Tsvetkov, Sebastian Ruder, Graham Neubig, EMNLP, 2021 

22. Exploring Domain-Invariant Parameters for Source Free Domain Adaptation ([pdf](https://openaccess.thecvf.com/content/CVPR2022/papers/Wang_Exploring_Domain-Invariant_Parameters_for_Source_Free_Domain_Adaptation_CVPR_2022_paper.pdf))

    - Fan Wang, Zhongyi Han, Yongshun Gong, CVPR, 2022

23. Fully Test-Time Adaptation for (medical) Image Segmentation ([pdf](https://miccai2021.org/openaccess/paperlinks/2021/09/01/204-Paper1319.html))

    - Minhao Hu, Tao Song, Yujun Gu, Xiangde Luo, Jieneng Chen, Yinan Chen, Ya Zhang, Shaoting Zhang, MICCAI, 2021

24. Generalizable Model-agnostic Semantic Segmentation via Target-specific Normalization ([pdf](https://arxiv.org/abs/2003.12296))

    - Jian Zhang, Lei Qi, Yinghuan Shi, Yang Gao, Pattern Recognition (PR), 2021

25. Improving Adversarial Defense with Self-supervised Test-time Fine-tuning ([pdf](https://openreview.net/forum?id=r8S93OsHWEf))

    - Zhichao Huang, Chen Liu, Mathieu Salzmann, Sabine Süsstrunk, Tong Zhang, ICLR submitted, 2022

26. Leveraging Test-Time Consensus Prediction for Robustness against Unseen Noise ([pdf](https://openaccess.thecvf.com/content/WACV2022/papers/Sarkar_Leveraging_Test-Time_Consensus_Prediction_for_Robustness_Against_Unseen_Noise_WACV_2022_paper.pdf))

    - Anindya Sarkar, Anirban Sarkar, Vineeth N Balasubramanian, WACV, 2022

27. Meta Test-Time Training for Self-Supervised Test-Time Adaption ([pdf](https://proceedings.mlr.press/v151/bartler22a.html))

    - Alexander Bartler, Andre Bühler, Felix Wiewel, Mario Döbler, Bin Yang, PMLR, 2022

28. On the Road to Online Adaptation for Semantic Image Segmentation ([pdf](https://arxiv.org/abs/2203.16195))

    - Riccardo Volpi, Pau de Jorge, Diane Larlus, Gabriela Csurka, CVPR, 2022

29. Revisiting Realistic Test-Time Training- Sequential Inference and Adaptation by Anchored Clustering ([pdf](https://arxiv.org/abs/2206.02721))

    - Yongyi Su, Xun Xu, Kui Jia, arXiv, 2022

30. SHIFT- A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptation ([pdf](https://www.vis.xyz/pub/shift/))

    - Tao Sun, Mattia Segu, Janis Postels, Yuxuan Wang, Luc Van Gool, Bernt Schiele, Federico Tombari, Fisher Yu, CVPR, 2022

31. Self-supervised Test-time Adaptation on Video Data ([pdf](https://sslneurips21.github.io/files/CameraReady/SSL_TTA.pdf))

    - Fatemeh Azimi, Sebastian Palacio, Federico Raue, Jörn Hees, Luca Bertinetto, Andreas Dengel, WACV, 2022

32. Test time Adaptation through Perturbation Robustness ([pdf](https://arxiv.org/abs/2110.10232))

    - Prabhu Teja Sivaprasad, François Fleuret, NeurIPS Workshop, 2021

33. Test-Time Adaptation with Shape Moments for (medical) Image Segmentation ([pdf](https://arxiv.org/abs/2205.07983))

    - Mathilde Bateson, Hervé Lombaert, Ismail Ben Ayed, MICCAI, 2022

34. Test-Time Adaption by Aligning Prototypes using Self-Supervision ([pdf](https://arxiv.org/abs/2205.08731?context=cs))

    - Alexander Bartler, Florian Bender, Felix Wiewel, Bin Yang, IJCNN, 2022

35. Test-time Batch Normalization ([pdf](https://aps.arxiv.org/abs/2205.10210))

    - Tao Yang, Shenglong Zhou, Yuwang Wang, Yan Lu, Nanning Zheng, arXiv, 2022 

36. Towards Multi domain Single Image Dehazing via Test-time adaptation ([pdf](https://openaccess.thecvf.com/content/CVPR2022/papers/Liu_Towards_Multi-Domain_Single_Image_Dehazing_via_Test-Time_Training_CVPR_2022_paper.pdf))

    - Huan Liu, Zijun Wu, Liangyan Li, Sadaf Salehkalaibar, Jun Chen1, Keyan Wang, CVPR, 2022

37. Towards Online Domain Adaptive Object Detection ([pdf](https://arxiv.org/pdf/2204.05289.pdf))

    - Vibashan VS, Poojan Oza and Vishal M. Patel, arXiv, 2022

38. Uncertainty Reduction for Model Adaptation in Semantic Segmentation ([pdf](https://openaccess.thecvf.com/content/CVPR2021/papers/S_Uncertainty_Reduction_for_Model_Adaptation_in_Semantic_Segmentation_CVPR_2021_paper.pdf))

    - Prabhu Teja S, Franc¸ois Fleuret, CVPR, 2022

39. Uncertainty-Guided Mixup for Semi-Supervised Domain Adaptation without Source Data ([pdf](https://arxiv.org/abs/2107.06707))

    - Ning Ma, Jiajun Bu, Zhen Zhang, Sheng Zhou, arXiv, 2021

40. Unsupervised Adaptation of Semantic Segmentation Models without Source Data ([pdf](https://arxiv.org/abs/2112.02359))

    - Sujoy Paul, Ansh Khurana, Gaurav Aggarwal, arXiv, 2021

41. Test-Time Training Can Close the Natural Distribution Shift Performance Gap in Deep Learning Based Compressed Sensing ([pdf](https://arxiv.org/abs/2204.07204))

    - Mohammad Zalbagi Darestani, Jiayu Liu, Reinhard Heckel, arXiv, 2022