A processor implemented method for generating color variants for fashion apparels, the method comprising: receiving, via one or more hardware processors, (a) an input image comprising a fashion apparel, and (b) a target color for generating a color variant of the fashion apparel, wherein the target color is represented in terms of Red Blue Green, RGB, components; generating, via a two-step encoder of a Fashion Apparel Regeneration - Generative Adversarial Network, FAR-GAN, executed by the one or more hardware processors, a target style embedding of the fashion apparel by processing the input image, the two-step encoder comprising (a) a first level encoder generating a concatenated feature embedding representing a plurality of primary low-level features and an edge map of the fashion apparel and (b) a second level encoder generating the target style embedding from the concatenated feature embedding; generating, via the one or more hardware processors, a target color embedding from the RGB components of the target color via multi-layer Fully Connected, FC, layers of the FAR-GAN; and generating, via a decoder of the FAR-GAN executed by the one or more hardware processors, the decoder comprising a plurality of decoder blocks, a synthetic target image comprising the color variant of the fashion apparel, wherein the decoder dictates the target style embedding by the target color embedding using an Adaptive Instance Normalization, AdaIN, and utilizes un-correlated Gaussian noise added to each of the plurality of decoder blocks to impose variability in a color and a style of the fashion apparel in the synthetic target image enabling the synthetic target image to appear realistic when displayed on a display screen. receiving, via one or more hardware processors, (a) an input image comprising a fashion apparel, and (b) a target color for generating a color variant of the fashion apparel, wherein the target color is represented in terms of Red Blue Green, RGB, components; generating, via a two-step encoder of a Fashion Apparel Regeneration - Generative Adversarial Network, FAR-GAN, executed by the one or more hardware processors, a target style embedding of the fashion apparel by processing the input image, the two-step encoder comprising (a) a first level encoder generating a concatenated feature embedding representing a plurality of primary low-level features and an edge map of the fashion apparel and (b) a second level encoder generating the target style embedding from the concatenated feature embedding; generating, via the one or more hardware processors, a target color embedding from the RGB components of the target color via multi-layer Fully Connected, FC, layers of the FAR-GAN; and generating, via a decoder of the FAR-GAN executed by the one or more hardware processors, the decoder comprising a plurality of decoder blocks, a synthetic target image comprising the color variant of the fashion apparel, wherein the decoder dictates the target style embedding by the target color embedding using an Adaptive Instance Normalization, AdaIN, and utilizes un-correlated Gaussian noise added to each of the plurality of decoder blocks to impose variability in a color and a style of the fashion apparel in the synthetic target image enabling the synthetic target image to appear realistic when displayed on a display screen.