Realization RGBD Image Stylization

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PubDate: May 2023

Teams: University of Alberta

Writers: Bhavya Sehgal, Vaishnavi Mendu, Aparna Mendu

PDF: Realization RGBD Image Stylization


This research paper explores the application of style transfer in computer vision using RGB images and their corresponding depth maps. We propose a novel method that incorporates the depth map and a heatmap of the RGB image to generate more realistic style transfer results. We compare our method to the traditional neural style transfer approach and find that our method outperforms it in terms of producing more realistic color and style. The proposed method can be applied to various computer vision applications, such as image editing and virtual reality, to improve the realism of generated images. Overall, our findings demonstrate the potential of incorporating depth information and heatmap of RGB images in style transfer for more realistic results.

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