[40] Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollar. Focal loss for dense object detection. In ICCV, 2017. 9
[41] Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dólár, and C Lawrence Zitnick. Microsoft coco: Common objects in context. In European conference on computer vision, pages 740-755. Springer, 2014. 9
[42] Jihao Liu, Boxiao Liu, Hongsheng Li, and Yu Liu. Meta knowledge distillation. arXiv preprint arXiv:2202.07940, 2022. 3
[43] Xiaolong Liu, Lujun Li, Chao Li, and Anbang Yao. Norm: Knowledge distillation via n-to-one representation matching. In ICLR, 2023. 3
[44] Yifan Liu, Changyong Shu, Jingdong Wang, and Chunhua Shen. Structured knowledge distillation for dense prediction. IEEE transactions on pattern analysis and machine intelligence, 2020. 9
[45] Yu Liu, Xuhui Jia, Mingxing Tan, Raviteja Vemulapalli, Yukun Zhu, Bradley Green, and Xiaogang Wang. Search to distill: Pearls are everywhere but not the eyes. In CVPR, 2020. 2
[46] Seyed Iman Mirzadeh, Mehrdad Farajtabar, Ang Li, Nir Levine, Akihiro Matsukawa, and Hassan Ghasemzadeh. Improved knowledge distillation via teacher assistant. In AAAI, 2020. 2, 6
[47] Yulei Niu, Long Chen, Chang Zhou, and Hanwang Zhang. Respecting transfer gap in knowledge distillation. 2022. 7
[48] Wonpyo Park, Yan Lu, Minsu Cho, and Dongju Kim. Relational knowledge distillation. In CVPR, 2019. 3, 7
[49] Zimian Wei Xin Niu ZHILIANG TIAN Hengyue Pan Peijie Dong, Lujun Li. Emq: Evolving training-free proxies for automated mixed precision quantization. In ICCV, 2023. 1
[50] Chen Pengguang, Liu Shu, Zhao Hengshuang, and Jiaya Jia. Distilling knowledge via knowledge review. In CVPR, 2021. 2, 6, 8
[51] Jie Qin, Jie Wu, Xuefeng Xiao, Lujun Li, and Xingang Wang. Activation modulation and recalibration scheme for weakly supervised semantic segmentation. In AAAI, 2022. 9
[52] Zengyu Qiu, Xinzhu Ma, Kunlin Yang, Chunya Liu, Jun Hou, Shuai Yi, and Wanli Ouyang. Better teacher better student: Dynamic prior knowledge for knowledge distillation. arXiv preprint arXiv:2206.06067, 2022. 5
[53] Mohammad Rastegari, Vicente Ordonez, Joseph Redmon, and Ali Joseph. Xnor-net: Imagenet classification using binary convolutional neural networks. In ECCV, 2016. 1
[54] Esteban Real, Chen Liang, David So, and Quoc Le. Automl-zero: Evolving machine learning algorithms from scratch. In ICML, 2020. 3
[55] Esteban Real, Chen Liang, David R. So, and Quoc V. Le. Automl-zero: Evolving machine learning algorithms from scratch, 2020. 2
[56] Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun. Faster r-cnn: Towards real-time object detection with region proposal networks. arXiv preprint, arXiv:1506.01497, 2015. 9
[57] Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang, Carlo Gatta, and Yoshua Bengio. Fitnets: Hints for thin deep nets. In ICLR, 2015. 1, 7
[58] Xiaojie Li Jianlong Wu Fei Wang Chen Qian Shangchen Du, Shan You and Changshui Zhang. Agree to disagree: Adaptive ensemble knowledge distillation in gradient space. In NeurIPS, 2020. 6
[59] Changyong Shu, Yifan Liu, Jianfei Gao, Zheng Yan, and Chunhua Shen. Channel-wise knowledge distillation for dense prediction. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 5311-5320, 2021. 3, 9