An electronic device for colorizing a black and white image using a Generative Adversarial Network (GAN)- based model comprising a transformer block, the electronic device comprising a processor, wherein the processor is set to: obtain a black and white image including only first information about a luminance channel; and generate a pseudo color image including only second information about a chrominance channel by applying the black and white image to the GAN-based model, the GAN-based model includes a generator network including a plurality of transformer blocks for color conversion, a plurality of convolution layers, and a plurality of transpose convolution layers, the plurality of transformer blocks each include a Depth Wise Convolution (DWC) layer, a first Layer Normal-ization (LN) layer, a Window-based Multi-head Self Attention (W-MSA) layer, a second LN layer, and a Colorization Feed Forward (CFF) block, B₂ the W-MSA layer includes a first-group MSA and a second-group MSA, and the first-group MSA is provided with a feature map divided into first-type windows and the second-group MSA is provided with a feature map divided into second-type windows obtained by shifting the first-type windows.

An electronic device for colorizing a black and white image using a Generative Adversarial Network (GAN)- based model comprising a transformer block, the electronic device comprising a processor, wherein the processor is set to: obtain a black and white image including only first information about a luminance channel; and generate a pseudo color image including only second information about a chrominance channel by applying the black and white image to the GAN-based model, the GAN-based model includes a generator network including a plurality of transformer blocks for color conversion, a plurality of convolution layers, and a plurality of transpose convolution layers, the plurality of transformer blocks each include a Depth Wise Convolution (DWC) layer, a first Layer Normal-ization (LN) layer, a Window-based Multi-head Self Attention (W-MSA) layer, a second LN layer, and a Colorization Feed Forward (CFF) block, B₂ the W-MSA layer includes a first-group MSA and a second-group MSA, and the first-group MSA is provided with a feature map divided into first-type windows and the second-group MSA is provided with a feature map divided into second-type windows obtained by shifting the first-type windows.

An electronic device for colorizing a black and white image using a Generative Adversarial Network (GAN)- based model comprising a transformer block, the electronic device comprising a processor, wherein the processor is set to: obtain a black and white image including only first information about a luminance channel; and generate a pseudo color image including only second information about a chrominance channel by applying the black and white image to the GAN-based model, the GAN-based model includes a generator network including a plurality of transformer blocks for color conversion, a plurality of convolution layers, and a plurality of transpose convolution layers, the plurality of transformer blocks each include a Depth Wise Convolution (DWC) layer, a first Layer Normal-ization (LN) layer, a Window-based Multi-head Self Attention (W-MSA) layer, a second LN layer, and a Colorization Feed Forward (CFF) block, B₂ the W-MSA layer includes a first-group MSA and a second-group MSA, and the first-group MSA is provided with a feature map divided into first-type windows and the second-group MSA is provided with a feature map divided into second-type windows obtained by shifting the first-type windows.

An electronic device for colorizing a black and white image using a Generative Adversarial Network (GAN)- based model comprising a transformer block, the electronic device comprising a processor, wherein the processor is set to: obtain a black and white image including only first information about a luminance channel; and generate a pseudo color image including only second information about a chrominance channel by applying the black and white image to the GAN-based model, the GAN-based model includes a generator network including a plurality of transformer blocks for color conversion, a plurality of convolution layers, and a plurality of transpose convolution layers, the plurality of transformer blocks each include a Depth Wise Convolution (DWC) layer, a first Layer Normal-ization (LN) layer, a Window-based Multi-head Self Attention (W-MSA) layer, a second LN layer, and a Colorization Feed Forward (CFF) block, B₂ the W-MSA layer includes a first-group MSA and a second-group MSA, and the first-group MSA is provided with a feature map divided into first-type windows and the second-group MSA is provided with a feature map divided into second-type windows obtained by shifting the first-type windows.