Image Enhancement For Improved Visibility of Digital Displays Under The Sunlight

Person image generation has attracted more and more attention because it has many applications. This paper focuses on pose transfer and virtual try-on. We propose a flow-based method called attribute-decomposited spatial transformation network. It warps different body parts separately using segmentation and then fuses different body parts and generates images. The flow-based technique enables the model to generate high-quality person images for pose transfer and the attribute-decomposited technique enables the model to support virtual try-on. The proposed method was evaluated on Deepfashion dataset. Quantitative and qualitative experimental results show the superiority of the method.