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Deep neural models in recent years have been successful in almost every field, including extremely complex problem statements.
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Q. Dou, Q. Liu, P. A. Heng, and B. Glocker, “Unpaired multi-modal segmentation via knowledge distillation,”
2020
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A. Perez, V. Sanguineti, P. Morerio, and V. Murino, “Audio-visual model distillation using acoustic images,” in
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L. Zhao, X. Peng, Y. Chen, M. Kapadia, and D. N. Metaxas, “Knowledge as priors: Cross-modal knowledge generalization for datasets without superior knowledge,”
2020
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L. Wang, T.-K. Kim, and K.-J. Yoon, “Eventsr: From asynchronous events to image reconstruction, restoration, and super-resolution via end-to-end adversarial learning,”
2020
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2020
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H. Lee, S. J. Hwang, and J. Shin, “Rethinking data augmentation: Self-supervision and self-distillation,”
2020
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X. Cheng, Z. Rao, Y. Chen, and Q. Zhang, “Explaining knowledge distillation by quantifying the knowledge,” in
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2020
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P. Liu, W. Liu, H. Ma, T. Mei, and M. Seok, “Ktan: knowledge transfer adversarial network,”
2020
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M. Goldblum, L. Fowl, S. Feizi, and T. Goldstein, “Adversarially robust distillation,”
2020
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M. Li, J. Lin, Y. Ding, Z. Liu, J.-Y. Zhu, and S. Han, “Gan compression: Efficient architectures for interactive conditional gans,”
2020
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H. Chen, Y. Wang, H. Shu, C. Wen, C. Xu, B. Shi, C. Xu, and C. Xu, “Distilling portable generative adversarial networks for image translation,”
2020
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C. Lassance, M. Bontonou, G. B. Hacene, V. Gripon, J. Tang, and A. Ortega, “Deep geometric knowledge distillation with graphs,”
2020
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2020
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G. Xu, Z. Liu, X. Li, and C. C. Loy, “Knowledge distillation meets self-supervision,”
2020
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2020
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2020
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2020
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H. Felix, W. M. Rodrigues, D. Macêdo, F. Simões, A. L. Oliveira, V. Teichrieb, and C. Zanchettin, “Squeezed deep 6dof object detection using knowledge distillation,”
2020
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2020
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X. Xu, Q. Zou, X. Lin, Y. Huang, and Y. Tian, “Integral knowledge distillation for multi-person pose estimation,”
2020
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F. Tosi, F. Aleotti, P. Z. Ramirez, M. Poggi, S. Salti, L. Di Stefano, and S. Mattoccia, “Distilled semantics for comprehensive scene understanding from videos,”
2020
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H. Wang, Y. Li, Y. Wang, H. Hu, and M.-H. Yang, “Collaborative distillation for ultra-resolution universal style transfer,”
2020
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M. Farhadi and Y. Yang, “Tkd: Temporal knowledge distillation for active perception,”
2020
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Z. Zhang, Y. Shi, C. Yuan, B. Li, P. Wang, W. Hu, and Z. Zha, “Object relational graph with teacher-recommended learning for video captioning,”
2020
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B. Pan, H. Cai, D.-A. Huang, K.-H. Lee, A. Gaidon, E. Adeli, and J. C. Niebles, “Spatio-temporal graph for video captioning with knowledge distillation,”
2020
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