<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Real-Time on Noureddine RAMDI</title><link>https://ramdi.fr/tags/real-time/</link><description>Recent content in Real-Time on Noureddine RAMDI</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 23 May 2026 20:41:27 +0000</lastBuildDate><atom:link href="https://ramdi.fr/tags/real-time/index.xml" rel="self" type="application/rss+xml"/><item><title>ai4anim-webgpu: in-browser neural motion matching with WebGPU compute shaders</title><link>https://ramdi.fr/github-stars/ai4anim-webgpu-in-browser-neural-motion-matching-with-webgpu-compute-shaders/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/ai4anim-webgpu-in-browser-neural-motion-matching-with-webgpu-compute-shaders/</guid><description>ai4anim-webgpu runs batched neural motion matching inference for multiple agents entirely in the browser using WebGPU compute shaders and mixed-precision matmul kernels.</description></item><item><title>Fun-ASR: Alibaba's multilingual speech recognition model with real-time capabilities</title><link>https://ramdi.fr/github-stars/fun-asr-alibaba-s-multilingual-speech-recognition-model-with-real-time-capabilities/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/fun-asr-alibaba-s-multilingual-speech-recognition-model-with-real-time-capabilities/</guid><description>Fun-ASR is Alibaba Tongyi Lab&amp;rsquo;s end-to-end speech recognition model with 800M parameters, supporting 31 languages and real-time transcription in noisy environments.</description></item><item><title>IRONSIGHT: A real-time OSINT dashboard aggregating 50+ public data sources with Next.js</title><link>https://ramdi.fr/github-stars/ironsight-a-real-time-osint-dashboard-aggregating-50-public-data-sources-with-next-js/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/ironsight-a-real-time-osint-dashboard-aggregating-50-public-data-sources-with-next-js/</guid><description>IRONSIGHT aggregates 50+ free public sources into a real-time OSINT dashboard with Next.js, combining military tracking, Telegram feeds, market data, and satellite info—all without API keys.</description></item><item><title>Building a resilient real-time option chain analyzer with Python tkinter</title><link>https://ramdi.fr/github-stars/building-a-resilient-real-time-option-chain-analyzer-with-python-tkinter/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/building-a-resilient-real-time-option-chain-analyzer-with-python-tkinter/</guid><description>Explore Python-NSE-Option-Chain-Analyzer, a Python tkinter desktop app that fetches and analyzes real-time NSE option chain data with robust polling, deduplication, and error handling.</description></item><item><title>DAAAM: real-time foundation-model-driven 3D dynamic scene graph construction for robot mapping</title><link>https://ramdi.fr/github-stars/daaam-real-time-foundation-model-driven-3d-dynamic-scene-graph-construction-for-robot-mapping/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/daaam-real-time-foundation-model-driven-3d-dynamic-scene-graph-construction-for-robot-mapping/</guid><description>DAAAM builds real-time 3D dynamic scene graphs using foundation models like SAM and VLMs, targeting large-scale robot mapping with semantic and spatio-temporal memory.</description></item><item><title>GoAccess: fast, real-time web log analysis in C</title><link>https://ramdi.fr/github-stars/goaccess-fast-real-time-web-log-analysis-in-c/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/goaccess-fast-real-time-web-log-analysis-in-c/</guid><description>GoAccess is a real-time web log analyzer written in C, offering low-footprint, fast HTML reports with geoip and TLS support. Easy to build or install via packages.</description></item><item><title>Inside stream-video-js: a layered TypeScript SDK for multi-platform video calling</title><link>https://ramdi.fr/github-stars/inside-stream-video-js-a-layered-typescript-sdk-for-multi-platform-video-calling/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-stream-video-js-a-layered-typescript-sdk-for-multi-platform-video-calling/</guid><description>stream-video-js offers a layered TypeScript SDK for building video calls, audio rooms, and livestreams across React, React Native, and vanilla JS. It runs on a global edge network with 99.999% uptime.</description></item><item><title>MeanVC: real-time zero-shot voice conversion with mean flows and diffusion transformers</title><link>https://ramdi.fr/github-stars/meanvc-real-time-zero-shot-voice-conversion-with-mean-flows-and-diffusion-transformers/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/meanvc-real-time-zero-shot-voice-conversion-with-mean-flows-and-diffusion-transformers/</guid><description>MeanVC enables real-time zero-shot voice conversion using mean flows and diffusion transformers for single-step inference, addressing latency bottlenecks in diffusion models.</description></item><item><title>mini-tokyo-3d: real-time 3D visualization of Tokyo transit with Mapbox GL</title><link>https://ramdi.fr/github-stars/mini-tokyo-3d-real-time-3d-visualization-of-tokyo-transit-with-mapbox-gl/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/mini-tokyo-3d-real-time-3d-visualization-of-tokyo-transit-with-mapbox-gl/</guid><description>Explore how mini-tokyo-3d renders Tokyo&amp;rsquo;s transit network in real-time 3D using live ODPT data and Mapbox GL, with a Node.js build pipeline and multi-language support.</description></item><item><title>PEAR: real-time expressive 3D human mesh recovery at 100 FPS</title><link>https://ramdi.fr/github-stars/pear-real-time-expressive-3d-human-mesh-recovery-at-100-fps/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/pear-real-time-expressive-3d-human-mesh-recovery-at-100-fps/</guid><description>PEAR predicts expressive 3D human mesh parameters for body, hands, and face simultaneously at 100 FPS using a pixel-aligned architecture based on PyTorch and SMPL-X models.</description></item><item><title>Avatar Forcing: real-time multimodal head avatar generation with diffusion forcing</title><link>https://ramdi.fr/github-stars/avatar-forcing-real-time-multimodal-head-avatar-generation-with-diffusion-forcing/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/avatar-forcing-real-time-multimodal-head-avatar-generation-with-diffusion-forcing/</guid><description>Avatar Forcing implements diffusion forcing for causal, real-time multimodal input processing enabling expressive head avatars with ~500ms latency and 6.8X speedup over baselines.</description></item><item><title>Vibra Code: An open-source AI app builder with cloud sandboxes and native 60fps chat UI</title><link>https://ramdi.fr/github-stars/vibra-code-an-open-source-ai-app-builder-with-cloud-sandboxes-and-native-60fps-chat-ui/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/vibra-code-an-open-source-ai-app-builder-with-cloud-sandboxes-and-native-60fps-chat-ui/</guid><description>Vibra Code uses Claude Code in E2B cloud sandboxes with real-time sync and a native iOS chat UI rendering at 60fps off-main-thread. Open source AI app builder with multi-provider support.</description></item><item><title>Deep-Live-Cam: Real-time face swapping optimized across diverse hardware with ONNX Runtime</title><link>https://ramdi.fr/github-stars/deep-live-cam-real-time-face-swapping-optimized-across-diverse-hardware-with-onnx-runtime/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/deep-live-cam-real-time-face-swapping-optimized-across-diverse-hardware-with-onnx-runtime/</guid><description>Deep-Live-Cam offers real-time face swapping and deepfake video generation using ONNX Runtime with multiple execution providers for optimized performance on GPUs, CPUs, and Apple Silicon.</description></item></channel></rss>