Method for decoding, method for encoding, and method for training model

A method for decoding, comprising:

• receiving, by a processor, a first image and a second image of a scene, wherein the first image is downsampled and is different from the second image, the first image is a depth image, and the second image is a color image;
• obtaining, by the processor, a residual map associated with edges of the scene according to the second image and the downsampled first image, comprising:
• deriving an intensity edge map from the color image;
• estimating a depth edge feature map based on the depth image using a first machine learning model;
• estimating an intensity edge feature map based on the intensity edge map using a second machine learning model;
• estimating a color edge feature map based on the color image, the depth image, and the intensity edge map using a third machine learning model;
• fusing the estimated depth edge feature map and the estimated intensity edge feature map to the estimated color edge feature map;
• and
• estimating the residual map based on the fused color edge feature map using a fourth machine learning model;
• upsampling, by the processor, the downsampled first image;
• and
• reconstructing, by the processor, the first image based on the upsampled first image and the residual map.