US 12,277,670 B2
Image processing method and apparatus
Junyong Noh, Daejeon (KR); Sanghun Park, Daejeon (KR); and Kwanggyoon Seo, Daejeon (KR)
Assigned to KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY, Daejeon (KR)
Filed by KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY, Daejeon (KR)
Filed on Aug. 29, 2023, as Appl. No. 18/457,499.
Application 18/457,499 is a division of application No. 17/444,919, filed on Aug. 12, 2021, granted, now 11,790,486.
Claims priority of application No. 10-2020-0159197 (KR), filed on Nov. 24, 2020.
Prior Publication US 2023/0410249 A1, Dec. 21, 2023
Int. Cl. G06K 9/00 (2022.01); G06N 3/045 (2023.01); G06N 3/088 (2023.01); G06T 3/4007 (2024.01); G06T 3/4046 (2024.01); G06T 5/50 (2006.01)
CPC G06T 3/4007 (2013.01) [G06N 3/045 (2023.01); G06N 3/088 (2013.01); G06T 3/4046 (2013.01); G06T 5/50 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)] 11 Claims
OG exemplary drawing
 
7. An image processing apparatus, comprising:
at least one processor;
wherein, the processor is configured to:
obtain training data comprising a first image, a second image, and a ground truth morphing image that is based on a morphing control parameter, wherein the ground truth morphing image is generated by linearly interpolating a first point corresponding to the first image sampled in a latent space by a pretrained model and a second point corresponding to the second image sampled in the latent space by the pretrained model, based on the morphing control parameter;
obtain an output morphing image by inputting the first image, the second image, and the morphing control parameter to a morphing generator; and
train the morphing generator based on a loss function that is based on at least one of the images comprised in the training data and the output morphing image,
wherein the loss function is determined based on at least one of:
an adversarial loss associated with a discrimination between the image comprised in the training data and the output morphing image obtained from the morphing generator; or
a pixel-wise reconstruction loss associated with a difference between pixels of the image comprised in the training data and pixels of the output morphing image.