{"id":3352,"date":"2025-09-13T04:08:06","date_gmt":"2025-09-13T04:08:06","guid":{"rendered":"https:\/\/172-234-197-23.ip.linodeusercontent.com\/?page_id=3352"},"modified":"2025-09-13T04:08:06","modified_gmt":"2025-09-13T04:08:06","slug":"cuda-accelerated-rf-nerf-fast-volumetric-rendering-with-rf-conditioned-fields","status":"publish","type":"page","link":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/?page_id=3352","title":{"rendered":"CUDA-Accelerated RF-NeRF: Fast Volumetric Rendering with RF-Conditioned Fields"},"content":{"rendered":"\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/wp-content\/uploads\/2025\/09\/CUDA-Accelerated-RF-NeRF-Benjamin-J-Gilbert-College-of-the-Mainland-Robotic-Process-Automation.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of CUDA-Accelerated RF-NeRF Benjamin J Gilbert College of the Mainland Robotic Process Automation.\"><\/object><a id=\"wp-block-file--media-c642f6fa-7d0c-4018-9b48-1220546d694d\" href=\"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/wp-content\/uploads\/2025\/09\/CUDA-Accelerated-RF-NeRF-Benjamin-J-Gilbert-College-of-the-Mainland-Robotic-Process-Automation.pdf\">CUDA-Accelerated RF-NeRF Benjamin J Gilbert College of the Mainland Robotic Process Automation<\/a><a href=\"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/wp-content\/uploads\/2025\/09\/CUDA-Accelerated-RF-NeRF-Benjamin-J-Gilbert-College-of-the-Mainland-Robotic-Process-Automation.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-c642f6fa-7d0c-4018-9b48-1220546d694d\">Download<\/a><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">We present a CUDA-accelerated renderer for RF conditioned NeRF with GPU kernels for ray generation, stratified sampling, and volumetric integration. A small benchmark<br>sweeps samples and chunk sizes, logging PSNR\/SSIM vs. latency;<br>JSON\u2192LATEX keeps tables and plots reproducible.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"882\" height=\"795\" src=\"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/wp-content\/uploads\/2025\/09\/image-52.png\" alt=\"\" class=\"wp-image-3354\" style=\"width:631px;height:auto\" srcset=\"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/wp-content\/uploads\/2025\/09\/image-52.png 882w, https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/wp-content\/uploads\/2025\/09\/image-52-300x270.png 300w, https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/wp-content\/uploads\/2025\/09\/image-52-768x692.png 768w\" sizes=\"auto, (max-width: 882px) 100vw, 882px\" \/><\/figure>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>We present a CUDA-accelerated renderer for RF conditioned NeRF with GPU kernels for ray generation, stratified sampling, and volumetric integration. A small benchmarksweeps samples and chunk sizes, logging PSNR\/SSIM vs. latency;JSON\u2192LATEX keeps tables and plots reproducible.<\/p>\n","protected":false},"author":2,"featured_media":3354,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"neve_meta_sidebar":"","neve_meta_container":"","neve_meta_enable_content_width":"","neve_meta_content_width":0,"neve_meta_title_alignment":"","neve_meta_author_avatar":"","neve_post_elements_order":"","neve_meta_disable_header":"","neve_meta_disable_footer":"","neve_meta_disable_title":"","footnotes":""},"class_list":["post-3352","page","type-page","status-publish","has-post-thumbnail","hentry"],"_links":{"self":[{"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/pages\/3352","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3352"}],"version-history":[{"count":0,"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/pages\/3352\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/media\/3354"}],"wp:attachment":[{"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3352"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}