US 12,450,690 B2
Method, device, and computer program product for image processing
Zhisong Liu, Shenzhen (CN); Zijia Wang, WeiFang (CN); and Zhen Jia, Shanghai (CN)
Assigned to Dell Products L.P., Round Rock, TX (US)
Filed by Dell Products L.P., Round Rock, TX (US)
Filed on Nov. 15, 2022, as Appl. No. 17/987,491.
Claims priority of application No. 202211298887.8 (CN), filed on Oct. 21, 2022.
Prior Publication US 2024/0135489 A1, Apr. 25, 2024
Prior Publication US 2024/0233073 A9, Jul. 11, 2024
Int. Cl. G06K 9/00 (2022.01); G06N 3/08 (2023.01); G06T 3/4046 (2024.01); G06T 3/4053 (2024.01)
CPC G06T 3/4046 (2013.01) [G06N 3/08 (2013.01); G06T 3/4053 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for image processing, comprising:
for an input image of a first resolution, generating a feature map of a second resolution, the first resolution being less than the second resolution;
processing the feature map of the second resolution through a processing pipeline comprising at least a first residual-based dense back projection (RDBP) network, a second RDBP network, and a cross-scale attention layer, the first RDBP network and the second RDBP network each comprising a downsampling back projection layer, an upsampling back projection layer, and a spatial attention layer, the first and second RDBP networks being configured to generate respective instances of the feature map of the second resolution and respective corresponding instances of a feature map of the first resolution, for processing by the cross-scale attention layer of the processing pipeline, the cross-scale attention layer comprising a multi-head attention block including a bottom-up attention block and a top-down attention block, the bottom-up attention block and the top-down attention block generating respective feature maps of respective different resolutions with attention adjusted across scales by processing outputs of different ones of the downsampling back projection layers and the upsampling back projection layers of the first and second RDBP networks; and
generating, utilizing the cross-scale attention layer of the processing pipeline, an output image of the second resolution based on the feature maps of the second resolution and the feature maps of the first resolution generated through the first RDBP network and the second RDBP network.