Estimating and rectifying the orientation angle of any image is a pretty challenging task. Initial work used the hand engineering features for this purpose, where after the invention of deep learning using convolution-based neural network showed significant improvement in this problem. However, this paper shows that the combination of CNN and a custom loss function specially designed for angles lead to a state-of-the-art results. This includes the estimation of the orientation angle of any image or document at any degree (0 to 360 degree),

中文翻译：

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深度图像方向角检测

估计和校正任何图像的方向角是一项非常具有挑战性的任务。最初的工作为此目的使用了手工工程​​特征，在使用基于卷积的神经网络的深度学习发明之后，这个问题有了显着的改善。然而，这篇论文表明，将 CNN 与专门为角度设计的自定义损失函数相结合，可以产生最先进的结果。这包括在任何角度（0 到 360 度）估计任何图像或文档的方向角，