Abstract:
There is provided a method, apparatus and system for adapting a machine learning model for optical flow prediction. A machine learning model can be trained or adapted based on compressed video data, using motion vector information extracted from the compressed video data as ground-truth information for use in adapting the model to a motion vector prediction task. The model so adapted can accordingly be adapted for the similar task of optical flow prediction. Thus, the model can be adapted at test time to image data which is taken from an appropriate distribution. A meta-learning process can be performed prior to such model adaptation to potentially improve the model's performance.
Abstract:
A data management method, a system, and a device are provided. An example method includes: A data storage entity receives a data access request and sends an access permission verification request to a distributed ledger node storing a data access policy of the client and/or a data access policy of the user. The distributed ledger node verifies, based on an identifier of a client and/or an identifier of a user in the access permission verification request and a distributed ledger, whether the client has data access permission, and sends a first access permission verification response to the data storage entity if the client has the data access permission, where the first access permission verification response indicates that the client has the data access permission. After receiving the first access permission verification response sent from the distributed ledger node, the data storage entity sends corresponding data to the client.
Abstract:
The present application discloses an image processing method and apparatus, and an electronic device, and pertains to the field of image processing. The method includes: obtaining an inter-frame residual between two adjacent image frames to obtain a residual block; determining, based on the residual block, a target pixel region on which super-resolution processing needs to be performed; and performing super-resolution processing on only the target pixel region to obtain a target pixel region after the super-resolution processing. For another pixel region, a super-resolution processing result of an image frame that is in the two image frames and on which super-resolution processing is performed is directly used. This application can resolve a problem of high computation costs of super-resolution processing.
Abstract:
The present disclosure provides a discovery method, a device and a system for an application layer traffic optimization server, which relate to communication field, so as to reduce the cross-domain traffic and meet the network optimization demand of a network ISP as an internet access point. The method for an application layer traffic optimization server, related to a terminal side, comprising: obtaining a domain name of a proxy server for a terminal data layer to access internet; obtaining, according to a query name constructed using the domain name of the proxy server, an address of an application layer traffic optimization ALTO server related to the proxy server from a domain name server DNS; and communicating with the ALTO server according to the address of the ALTO server. Embodiments of the present disclosure are mainly applied to the communication between the terminal and the ALTO server.