Mixed-Precision Collaborative Quantization for Fast Object Tracking

Author:

Xie Yefan,Guo Yanwei,Hou Xuan,Zheng Jiangbin

Publisher

Springer Nature Singapore

Reference17 articles.

1. Banner, R., Nahshan, Y., Soudry, D.: Post training 4-bit quantization of convolutional networks for rapid-deployment. In: Advances in Neural Information Processing Systems 32 (2019)

2. Lecture Notes in Computer Science;L Bertinetto,2016

3. Bhalgat, Y., Lee, J., Nagel, M., Blankevoort, T., Kwak, N.: LSQ+: improving low-bit quantization through learnable offsets and better initialization. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 696–697 (2020)

4. Choi, J., Wang, Z., Venkataramani, S., Chuang, P.I.J., Srinivasan, V., Gopalakrishnan, K.: PACT: parameterized clipping activation for quantized neural networks. arXiv preprint arXiv:1805.06085 (2018)

5. Dekel, T., Oron, S., Rubinstein, M., Avidan, S., Freeman, W.T.: Best-buddies similarity for robust template matching. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2021–2029 (2015)

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