The invention discloses a video content semantic understanding and text description generation method based on
deep learning, and relates to the technical field of
multimedia information processing.The method comprises the steps that the
semantic similarity of a text and a video frame is calculated through a CLIP model, related key frames are selected, and features are aggregated; respectively extracting audio, visual and semantic features; aligning different
modal features by using self-attention, unifying dimensions of the LSTM, and then splicing and fusing; attention weights are calculated at a video level, a frame level and a channel level, and key information expression is enhanced; swin Transform encodes fusion features, and LSTM (
Long Short Term Memory)
decodes step by step to generate
natural language description; and a text-video index
database is constructed, and rapid retrieval is realized based on
semantic similarity. According to the method, the mapping relation between the video features and the
natural language is learned end to end through the
deep learning model, dependence on a fixed template can be eliminated, and semantic description with various
sentence patterns and coherent logic is generated.