Computer vision using learnt lossy image compression representations

    公开(公告)号:US10984560B1

    公开(公告)日:2021-04-20

    申请号:US16370598

    申请日:2019-03-29

    Abstract: Techniques for performing learnt image compression and object detection using compressed image data are described. A system may perform image compression using an image compression model that includes an encoder, an entropy model, and a decoder. The encoder, the entropy model, and the decoder may be jointly trained using machine learning based on training data. After training, the encoder and the decoder may be separated to encode image data to generate compressed image data or to decode compressed image data to generate reconstructed image data. In addition, the system may perform object detection using a compressed object detection model that processes compressed image data generated by the image compression model. For example, the compressed object detection model may perform partial decoding using a single layer of the decoder and perform compressed object detection on the partially decoded image data.

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