Researchers propose ReactVAU, a Slow-Fast Decoupled Framework for real-time streaming video anomaly understanding, addressing the limitations of existing offline methods that rely on global temporal sampling and violate causality. The framework enables deployment in live surveillance streams by decoupling slow and fast processing paths.
In this paper, we propose ReactVAU, a Slow-Fast Decoupled Framework for real-time streaming Video Anomaly Understanding (VAU). Existing VAU methods rely on offline inference with global temporal sampling, which violates causality and prevents deployment in live surveillance streams. Conversely, gene
EU-based hosting, git-push deploys, automatic HTTPS, no cold starts. Free tier with a custom domain — perfect for shipping the agent you just read about.