Exploring Semantic Segmentation on the DCT Representation

@article{Lo2019ExploringSS,
  title={Exploring Semantic Segmentation on the DCT Representation},
  author={Shao-Yuan Lo and Hsueh-Ming Hang},
  journal={Proceedings of the ACM Multimedia Asia},
  year={2019}
}
Typical convolutional networks are trained and conducted on RGB images. However, images are often compressed for memory savings and efficient transmission in real-world applications. In this paper, we explore methods for performing semantic segmentation on the discrete cosine transform (DCT) representation defined by the JPEG standard. We first rearrange the DCT coefficients to form a preferred input type, then we tailor an existing network to the DCT inputs. The proposed method has an accuracy… Expand
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