DNN-based cross component prediction

A system comprising:

• at least one memory configured to store computer program code;
• and
• at least one processor configured to access the computer program code and operate as instructed by the computer program code, the computer program code comprising:
• inputting code configured to cause the at least one processor to input a reconstructed luma block of an image or video, reference components, and side information associated with the reconstructed luma block into a deep neural network (DNN) that is implemented by the at least one processor, the side information includes block partition depth information;
• and
• predicting code configured to cause the at least one processor to predict, by the DNN, a reconstructed chroma block of the image or video based on the reconstructed luma block, the reference components, and the side information that are input.

A non-transitory computer-readable medium storing computer code that is configured to, when executed by at least one processor, cause the at least one processor to:

• implement a deep neural network (DNN);
• input a reconstructed luma block of an image or video, reference components, and side information associated with the reconstructed luma block into the DNN, the side information includes block partition depth information;
• and
• predict, by the DNN, a reconstructed chroma block of the image or video based on the reconstructed luma block, the reference components, and the side information that are input.