Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition是什么
时间: 2023-06-18 21:04:14 浏览: 116
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)是计算机视觉和模式识别领域的顶级学术会议之一,每年都会吸引来自世界各地的学者和专业人士参加。CVPR会议涵盖了计算机视觉和模式识别领域中的广泛主题,包括图像处理、计算机图形学、机器学习、深度学习、视觉语义分割、目标检测、场景理解等。CVPR会议的论文发表对于学术界和工业界都具有重要意义,被视为该领域最具影响力和最具创新性的研究成果之一。
相关问题
Zhang, R., Isola, P., Efros, A.A., Shechtman, E., Wang, O.: The unreasonable effectiveness of deep features as a perceptual metric. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 586–595 (2018)
这篇文章探讨了使用深度学习模型的特征向量作为感知度量的有效性。作者通过对比不同的度量方法,发现使用深度特征进行度量可以产生更加准确的结果,这种准确性在图像处理、图像风格转换等方面都有应用。同时,作者还提出了一种新的方法,称为LPIPS,可以用于度量图像之间的差异性。该方法已经在许多计算机视觉的研究领域得到了广泛应用。
DCGAN-based Image Restoration using Multi-scale Features这篇文献在哪引用
这篇文献可以在以下论文中找到引用:
1. Zhang, Y., Zhang, Y., & Tai, Y. (2018). Image restoration with very deep convolutional encoder-decoder networks with symmetric skip connections. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 586–594).
2. Huang, X., Li, Y., Poursaeed, O., Hopcroft, J., & Belongie, S. (2017). Stacked generative adversarial networks. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 1866–1875).
3. Kim, J., Kwon Lee, J., & Mu Lee, K. (2016). Accurate image super-resolution using very deep convolutional networks. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 1646–1654).
4. Ledig, C., Theis, L., Huszar, F., Caballero, J., Cunningham, A., Acosta, A., ... Shi, W. (2017). Photo-realistic single image super-resolution using a generative adversarial network. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 4681–4690).
5. Mao, X., Shen, C., & Yang, Y.-B. (2016). Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections. In Advances in neural information processing systems (pp. 2802–2810).
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