{"id":5313,"date":"2011-08-28T12:05:22","date_gmt":"2011-08-28T09:05:22","guid":{"rendered":"http:\/\/hgpu.org\/?p=5313"},"modified":"2011-08-28T12:05:22","modified_gmt":"2011-08-28T09:05:22","slug":"real-time-photo-style-transfer","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=5313","title":{"rendered":"Real-time photo style transfer"},"content":{"rendered":"<p>This paper presents a novel approach for real-time photo style transfer. The automatic image manipulation technique is performed in the oRGB color space, which is a new color model based on the psychologically opponent color theory. We transfer color from an appropriate source image to the target image using a simple statistical analysis. In addition, we match the global luminance histogram to achieve better photographic look. Note that the whole pipeline is highly parallel, enabling a GPU-based real-time implementation. Several experimental results are shown to demonstrate the effectiveness and efficiency of the proposed method.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This paper presents a novel approach for real-time photo style transfer. The automatic image manipulation technique is performed in the oRGB color space, which is a new color model based on the psychologically opponent color theory. We transfer color from an appropriate source image to the target image using a simple statistical analysis. In addition, [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[89,33,3],"tags":[14,480,1786,20,357,297],"class_list":["post-5313","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-image-processing","category-paper","tag-cuda","tag-directx","tag-image-processing","tag-nvidia","tag-nvidia-geforce-8800-gts","tag-real-time-graphics"],"views":2050,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5313","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=5313"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5313\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5313"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5313"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5313"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}