Short video synthesis method and apparatus, and device and storage medium

A short video synthesis apparatus, comprising:

• a video frame set obtaining module, configured to obtain a video frame set corresponding to a to-be-processed video, wherein each video frame in the video frame set carries a timestamp;
• a to-be-synthesized video frame obtaining module, configured to respectively input all video frames in the video frame set into an interest frame identification model to obtain a plurality of to-be-synthesized video frames, wherein the interest frame identification model is used for identifying a video frame meeting an interest degree condition in the input video frames;
• and
• a short video forming module, configured to splice, according to the timestamp carried by the each to-be-synthesized video frame, the plurality of to-be-synthesized video frames to form a short video corresponding to the to-be-processed video;
• wherein the interest frame identification model is obtained through training a set deep learning model by using a plurality of video frame samples marked with an interest label.

A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein, when executing the computer program, the processor is configured to:

• obtain a video frame set corresponding to a to-be-processed video, wherein each video frame in the video frame set carries a timestamp;
• respectively input all video frames in the video frame set into an interest frame identification model to obtain a plurality of to-be-synthesized video frames, wherein the interest frame identification model is used for identifying a video frame meeting an interest degree condition in the input video frames;
• and
• splice, according to the timestamp carried by the each to-be-synthesized video frame, the plurality of to-be-synthesized video frames to form a short video corresponding to the to-be-processed video;
• wherein the interest frame identification model is obtained through training a set deep learning model by using a plurality of video frame samples marked with an interest label.