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📢MinT: Temporally-Controlled Multi-Event Video Generation📢 mint-video.github.io TL;DR: We identify a fundamental failure mode of existing video generators: they cannot produce videos with sequential events. MinT unlocks this capability with temporal grounding of events. 🧵

MinT beats Sora in multi-event generation! One week after the release of MinT, Sora also released a *storyboard* tool that targets the same task (sequential events + time control). Below are a few comparisons, where MinT shows better event transition and timing: (1/N)

Introducing ⚗️ Video Alchemist Our new video model supporting 👪 Multi-subject open-set personalization 🏞️ Foreground & background personalization 🚀 Without the need of inference-time tuning snap-research.github.io/open-set-video… [Results] 1. Sora girl rides a dinosaur on a savanna 🧵👇

Can pretrained diffusion models connect for cross-modal generation? 📢 Introducing AV-Link ♾ Bridging unimodal diffusion models in one framework to enable: 📽️ ➡️ 🔊 Video-to-Audio 🔊 ➡️ 📽️ Audio-to-Video 🌐: snap-research.github.io/AVLink/ 📄: hf.co/papers/2412.15… ⤵️ Results