SEMINAR

Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, Timo Aila , "Analyzing and Improving the Image Quality of StyleGAN", CVPR 2020


  • 추헌국 발표, 2022.12

  • https://arxiv.org/abs/1912.04958

Bardes, A., Ponce, J., & LeCun, Y. Vicreg: Variance-invariance-covariance regularization for self-supervised learning. arXiv preprint arXiv:2105.04906, 2021.


  • 최대웅 발표, 2021.08.03

  • 발표자료 : link

  • References below

[References]

[1] Bardes, A., Ponce, J., & LeCun, Y. (2021). Vicreg: Variance-invariance-covariance regularization for self-supervised learning. arXiv preprint arXiv:2105.04906.

[2] Wu, Zhirong, et al. "Unsupervised feature learning via non-parametric instance discrimination." Proceedings of the IEEE conference on computer vision and pattern recognition. 2018.

[3] Chen, Ting, et al. "A simple framework for contrastive learning of visual representations." International conference on machine learning. PMLR, 2020.

[4] He, Kaiming, et al. "Momentum contrast for unsupervised visual representation learning." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2020.

[5] Grill, Jean-Bastien, et al. "Bootstrap your own latent: A new approach to self-supervised learning." arXiv preprint arXiv:2006.07733 (2020).

[6] Caron, Mathilde, et al. "Unsupervised learning of visual features by contrasting cluster assignments." arXiv preprint arXiv:2006.09882 (2020).

[7] Gidaris, S., Singh, P., & Komodakis, N. (2018). Unsupervised representation learning by predicting image rotations. arXiv preprint arXiv:1803.07728

[8] Noroozi, M., & Favaro, P. (2016, October). Unsupervised learning of visual representations by solving jigsaw puzzles. In European conference on computer vision (pp. 69-84). Springer, Cham.

[9] Other resources

- Antonin Raffin, SSL관련 twitter : https://twitter.com/araffin2/status/1...

- PR-326: VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning : https://www.youtube.com/watch?v=iQVvh...

-김재훈, “Dive into BYOL” : https://www.youtube.com/watch?v=Rb1Dy...

- PR-305: Exploring Simple Siamese Representation Learning : https://www.youtube.com/watch?v=Z1Os5...


Tomas Jakab, Ankush Gupta, Hakan Bilen, Andrea Vedaldi, "Unsupervised Learning of Object Landmarks through Conditional Image Generation", NeurIPS 2018.


  • 윤동련 발표, 2021.08.03

  • 발표자료 : link


Katrin Renz, Nicolaj C. Stache, Neil Fox, Gül Varol, Samuel Albanie. Sign Segmentation with Changepoint-Modulated Pseudo-Labelling. CVPRW21, 2021.


  • 심호현 발표, 2021.08.03

  • 발표자료 : link

  • References below

[References]

[1] Katrin Renz, Nicolaj C. Stache, Neil Fox, Gül Varol, Samuel Albanie. Sign Segmentation with Changepoint-Modulated Pseudo-Labelling. In CVPRW21, 2021.

[2] Katrin Renz, Nicolaj Stache, Samuel Albanie, and Gul Varol. Sign language segmentation with temporal convolutional networks. In ICASSP, 2021

[3] Charles Truong, Laurent Oudre, and Nicolas Vayatis. Selective review of offline change point detection methods. Signal Processing, 2019.

[4] Other resources

- Sign language segmentation with temporal convolutional networks presentation : https://www.youtube.com/watch?v=N7EyM...

- Sign Segmentation with Changepoint-Modulated Pseudo-Labelling presentation : https://www.youtube.com/watch?v=N7EyM...

- PELT method 관련 : https://medium.com/dataman-in-ai/find...

- Pseudo-labelling 관련 : https://lv99.tistory.com/79 , https://www.stand-firm-peter.me/2018/...

Dahiya, Aneesh. "Exploring self-supervised learning techniques for hand pose estimation." Master Thesis, AIT Lab, ETH Zurich, 2021.


  • 서경은 발표, 2021.08.03

  • 발표자료 : link

  • References below

[References]

[1] Dahiya, Aneesh. "Exploring self-supervised learning techniques for hand pose estimation." Master Thesis, AIT Lab, ETH Zurich, 2021.

[2] Zhang, J., Jiao, J., Chen, M., Qu, L., Xu, X., & Yang, Q. (2016). 3d hand pose tracking and estimation using stereo matching. arXiv preprint arXiv:1610.07214.

[3] Zimmermann, C., Ceylan, D., Yang, J., Russell, B., Argus, M., & Brox, T. (2019). Freihand: A dataset for markerless capture of hand pose and shape from single rgb images. In Proceedings of the IEEE/CVF International Conference on Computer Vision (pp. 813-822).

[4] Zimmermann, C., & Brox, T. (2017). Learning to estimate 3d hand pose from single rgb images. In Proceedings of the IEEE international conference on computer vision (pp. 4903-4911).

[5] Chen, T., Kornblith, S., Norouzi, M., & Hinton, G. (2020, November). A simple framework for contrastive learning of visual representations. In International conference on machine learning (pp. 1597-1607). PMLR.

[6] Chen, T., Kornblith, S., Norouzi, M., & Hinton, G. (2020, November). A simple framework for contrastive learning of visual representations. In International conference on machine learning (pp. 1597-1607). PMLR.

[7] Other resources

- http://dmqm.korea.ac.kr/activity/semi...

- https://lilianweng.github.io/lil-log/...

- https://velog.io/@tobigs-gm1/Self-Sup...

- Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg & Demis Hassabis "Human-level control through deep reinforcement learning", Nature, February 2015

- 발표자: 고려대 ICPS 연구실 조현덕


- Yasushi Sakurai, Christos Faloutsos, Masashi Yamamuro, " Stream Monitoring under the Time Warping Distance", IEEE International Conference on Data Engineering, 2007

- 발표자: 고려대 ICPS 연구실 조현덕

- Barret Zoph, Deniz Yuret, Jonathan May, Kevin Knight, "Transfer Learning for Low-Resource Neural Machine Translation", EMNLP, 2016

- 발표자: 고려대 ICPS 연구실 이승재

- Guillaume Lample, Alexis Conneau, "Cross-lingual Language Model Pretraining", NeurIPS 2019

- 발표: 고려대 ICPS 연구실, 문성원

- Zhiyang Fang, Junfeng Wang, Jiaxuan Geng, Xuan Kan, "Feature Selection for Malware Detection Based on Reinforcement Learning", IEEE Access, Dec. 2019

- 발표: 고려대 네트워크관리연구실 박지태

- Yandong Liu, Mianxiong Dong, Kaoru Ota, Jianhua Li, Jun Wu, "Deep reinforcement learning based smart mitigation of DDoS flooding in software-defined networks", CAMAD 2018

- 발표: 고려대 네트워크관리연구실 박지태


"A study of reinforcement learning for neural machine translation" reviewed by 이승재


"ELECTRA: PRE-TRAINING TEXT ENCODERS AS DISCRIMINATORS RATHER THAN GENERATORS" reviewed by 문성원