Multi-granularity semantic alignment distillation learning for remote sensing image semantic segmentation
Di ZHANG, Yong ZHOU, Jiaqi ZHAO, Zhongyuan YANG, Hui DONG, Rui YAO, Huifang MA
Multi-granularity semantic alignment distillation learning for remote sensing image semantic segmentation
[1] |
Cheng G , Xie X , Han J , Guo L , Xia G S . Remote sensing image scene classification meets deep learning: challenges, methods, benchmarks, and opportunities. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13: 3735– 3756
|
[2] |
Li C , Mao Y , Zhang R , Huai J . A revisit to MacKay algorithm and its application to deep network compression. Frontiers of Computer Science, 2020, 14( 4): 144304
|
[3] |
Hinton G Vinyals O Dean J. Distilling the knowledge in a neural network. 2015, arXiv preprint arXiv: 1503.02531
|
[4] |
Liu Y Chen K Liu C Qin Z Luo Z Wang J. Structured knowledge distillation for semantic segmentation. In: Proceedings of 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2019, 2599– 2608
|
[5] |
Wang Y Zhou W Jiang T Bai X Xu Y. Intra-class feature variation distillation for semantic segmentation. In: Proceedings of the 16th European Conference on Computer Vision. 2020, 346– 362
|
[6] |
Hou Y Ma Z Liu C Loy C C. Learning lightweight lane detection CNNs by Self Attention distillation. In: Proceedings of 2019 IEEE/CVF International Conference on Computer Vision. 2019, 1013– 1021
|
/
〈 | 〉 |