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Subject [ICIP 2019] Generative Guiding Block (by Minho Park) is accepted in IEEE ICIP2019
Date 2019-05-01
Title: Generative Guiding Block: Synthesizing Realistic Looking Variants Capable Of Even Large Change Demands

Authors: Minho Park, Hak Gu Kim, and Yong Man Ro

Abstract: Realistic image synthesis is to generate an image that is perceptually indistinguishable from an actual image. Generating realistic looking images with large variations (e.g., large spatial deformations and large pose change), however, is very challenging. Handing large variations as well as preserving appearance needs to be taken into account in the realistic looking image generation. In this paper, we propose a novel realistic looking image synthesis method, especially in large change demands. To do that, we devise generative guiding blocks. The proposed generative guiding block includes realistic appearance preserving discriminator and naturalistic variation transforming discriminator. By taking the proposed generative guiding blocks into generative model, the latent features at the layer of generative model are enhanced to synthesize both realistic looking- and target variation- image. With qualitative and quantitative evaluation in experiments, we demonstrated the effectiveness of the proposed generative guiding blocks, compared to the state-of-the-arts.