Controllable Person Image Synthesis With Attribute-Decomposed GAN
Controllable Person Image Synthesis With Attribute-Decomposed GAN
This paper introduces the Attribute-Decomposed GAN, a novel generative model for controllable person image synthesis, which can produce realistic person images with desired human attributes (e.g., pose, head, upper clothes and pants) provided in various source inputs. The core idea of the proposed model is to embed human attributes into …