--- title: GHARP: Real-Time Gaussian Head Animation from... description: GHARP animates 3D human heads in real time from a few input images plus a driving expression signal. It splits the task into an offline identity stage that... canonical: https://daily.dev/posts/gharp-real-time-gaussian-head-animation-from-large-scale-reconstruction-prior-s8rbw2yaj twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: GHARP: Real-Time Gaussian Head Animation from Large-Scale Reconstruction Prior | daily.dev og:description: GHARP animates 3D human heads in real time from a few input images plus a driving expression signal. It splits the task into an offline identity stage that... og:url: https://daily.dev/posts/gharp-real-time-gaussian-head-animation-from-large-scale-reconstruction-prior-s8rbw2yaj og:image: https://api.daily.dev/og/posts/S8RBw2yaJ.png og:image:alt: GHARP: Real-Time Gaussian Head Animation from Large-Scale Reconstruction Prior og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # GHARP: Real-Time Gaussian Head Animation from Large-Scale Reconstruction Prior **[Apple Machine Learning Research](https://daily.dev/sources/mlapple)** · 2 min read · 0 upvotes · 0 comments ## Summary GHARP animates 3D human heads in real time from a few input images plus a driving expression signal. It splits the task into an offline identity stage that builds geometry and appearance, and a lightweight runtime animation stage suited for mobile devices. Animation happens in a structured latent space from a pretrained reconstruction model, fusing multiple views into a compact canonical Gaussian representation. A body alignment network addresses blur and flicker caused by underspecified body pose and clothing. GHARP reaches state-of-the-art quality on the Ava-256 benchmark while running up to 13x faster on an A100 GPU with 8x fewer Gaussians. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### What is GHARP and how does it animate 3D head avatars in real time? GHARP is a method that animates 3D human heads in real time from a few input images and a driving expression signal. It separates the task into an offline identity stage building subject geometry and appearance, and a lightweight runtime animation stage predicting expression-dependent residuals, optimized for mobile devices. _Developers building real-time avatar or graphics pipelines can track research like this on daily.dev._ ### How does GHARP fix blur and flicker in body regions not covered by facial expression codes? It uses a body alignment network that aligns the person's body in the target image with the input reference images, removing training ambiguity. Expression codes only describe the face, leaving body pose and clothing underspecified, which otherwise causes the animation network to average conflicting appearances and produce blur and temporal flicker. _Anyone solving avatar artifacts from underspecified inputs can follow this kind of fix on daily.dev._ ### How much faster is GHARP than previous methods on the Ava-256 benchmark? GHARP achieves state-of-the-art quality on the Ava-256 benchmark while running up to 13 times faster on an A100 GPU, using 8 times fewer Gaussians than comparable approaches. _Engineers comparing real-time rendering benchmarks can keep up with results like this on daily.dev._ ## Similar posts on daily.dev - [SHARP](https://daily.dev/posts/sharp-yujlg6jjr) · Hacker News · 0 upvotes · 0 comments - [D4RT: Unified, Fast 4D Scene Reconstruction & Tracking](https://daily.dev/posts/d4rt-unified-fast-4d-scene-reconstruction-tracking-q8nmhkzzd) · DeepMind · 0 upvotes · 0 comments - [Room360: Video-to-3D Spatial Reconstruction Platform](https://daily.dev/posts/room360-video-to-3d-spatial-reconstruction-platform-qofbpihck) · Hugging Face · 0 upvotes · 0 comments - [A 3D Body from Eight Questions — No Photo, No GPU](https://daily.dev/posts/a-3d-body-from-eight-questions-no-photo-no-gpu-0r6pfre5s) · Hacker News · 17 upvotes · 0 comments --- Tags: [#apple](https://daily.dev/tags/apple), [#3d](https://daily.dev/tags/3d), [#computer-vision](https://daily.dev/tags/computer-vision) [View this post on daily.dev](https://daily.dev/posts/gharp-real-time-gaussian-head-animation-from-large-scale-reconstruction-prior-s8rbw2yaj) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"GHARP: Real-Time Gaussian Head Animation from Large-Scale Reconstruction Prior","url":"https://daily.dev/posts/gharp-real-time-gaussian-head-animation-from-large-scale-reconstruction-prior-s8rbw2yaj","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/gharp-real-time-gaussian-head-animation-from-large-scale-reconstruction-prior-s8rbw2yaj"},"datePublished":"2026-10-26T20:00:07.364Z","dateModified":"2026-10-26T20:32:22.552Z","description":"GHARP animates 3D human heads in real time from a few input images plus a driving expression signal. It splits the task into an offline identity stage that...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/8dda20dea5f9a8a0e25a1b7bb36a1a20?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/8dda20dea5f9a8a0e25a1b7bb36a1a20?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Apple Machine Learning Research","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Apple Machine Learning Research","logo":"https://media.daily.dev/image/upload/s--mD-1uSe0--/f_auto,q_auto/v1785654191/logos/mlapple","url":"https://daily.dev/sources/mlapple"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/gharp-real-time-gaussian-head-animation-from-large-scale-reconstruction-prior-s8rbw2yaj","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"apple,3d,computer-vision","timeRequired":"PT2M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Apple Machine Learning Research","item":"https://daily.dev/sources/mlapple"},{"@type":"ListItem","position":3,"name":"GHARP: Real-Time Gaussian Head Animation from Large-Scale Reconstruction Prior"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/gharp-real-time-gaussian-head-animation-from-large-scale-reconstruction-prior-s8rbw2yaj#faq","mainEntity":[{"@type":"Question","name":"What is GHARP and how does it animate 3D head avatars in real time?","acceptedAnswer":{"@type":"Answer","text":"GHARP is a method that animates 3D human heads in real time from a few input images and a driving expression signal. It separates the task into an offline identity stage building subject geometry and appearance, and a lightweight runtime animation stage predicting expression-dependent residuals, optimized for mobile devices. Developers building real-time avatar or graphics pipelines can track research like this on daily.dev."}},{"@type":"Question","name":"How does GHARP fix blur and flicker in body regions not covered by facial expression codes?","acceptedAnswer":{"@type":"Answer","text":"It uses a body alignment network that aligns the person's body in the target image with the input reference images, removing training ambiguity. Expression codes only describe the face, leaving body pose and clothing underspecified, which otherwise causes the animation network to average conflicting appearances and produce blur and temporal flicker. Anyone solving avatar artifacts from underspecified inputs can follow this kind of fix on daily.dev."}},{"@type":"Question","name":"How much faster is GHARP than previous methods on the Ava-256 benchmark?","acceptedAnswer":{"@type":"Answer","text":"GHARP achieves state-of-the-art quality on the Ava-256 benchmark while running up to 13 times faster on an A100 GPU, using 8 times fewer Gaussians than comparable approaches. Engineers comparing real-time rendering benchmarks can keep up with results like this on daily.dev."}}]} ```