Deprecated: The each() function is deprecated. This message will be suppressed on further calls in /home/zhenxiangba/zhenxiangba.com/public_html/phproxy-improved-master/index.php on line 456 Paper page - MOVA: Towards Scalable and Synchronized Video-Audio Generation
https://mosi.cn/models/mova Model:https://huggingface.co/collections/OpenMOSS-Team/mova Code:https://github.com/OpenMOSS/MOVA\n","updatedAt":"2026-02-10T05:48:59.268Z","author":{"_id":"62c14609ac1b639c2d87192c","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1656833489364-noauth.png","fullname":"SII-liangtianyi","name":"tianyilt","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":5,"isUserFollowing":false}},"numEdits":0,"identifiedLanguage":{"language":"zh","probability":0.4221690893173218},"editors":["tianyilt"],"editorAvatarUrls":["https://cdn-avatars.huggingface.co/v1/production/uploads/1656833489364-noauth.png"],"reactions":[{"reaction":"🔥","users":["Cqy2019","ngc7293","natalie5","gaoyang07","tianyilt"],"count":5}],"isReport":false}},{"id":"698bdf1fb9b8fbd45e1ec8e1","author":{"_id":"63d3e0e8ff1384ce6c5dd17d","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1674830754237-63d3e0e8ff1384ce6c5dd17d.jpeg","fullname":"Librarian Bot (Bot)","name":"librarian-bot","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":318,"isUserFollowing":false},"createdAt":"2026-02-11T01:45:03.000Z","type":"comment","data":{"edited":false,"hidden":false,"latest":{"raw":"This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [Apollo: Unified Multi-Task Audio-Video Joint Generation](https://huggingface.co/papers/2601.04151) (2026)\n* [JoVA: Unified Multimodal Learning for Joint Video-Audio Generation](https://huggingface.co/papers/2512.13677) (2025)\n* [LTX-2: Efficient Joint Audio-Visual Foundation Model](https://huggingface.co/papers/2601.03233) (2026)\n* [TalkVerse: Democratizing Minute-Long Audio-Driven Video Generation](https://huggingface.co/papers/2512.14938) (2025)\n* [Omni2Sound: Towards Unified Video-Text-to-Audio Generation](https://huggingface.co/papers/2601.02731) (2026)\n* [MM-Sonate: Multimodal Controllable Audio-Video Generation with Zero-Shot Voice Cloning](https://huggingface.co/papers/2601.01568) (2026)\n* [JUST-DUB-IT: Video Dubbing via Joint Audio-Visual Diffusion](https://huggingface.co/papers/2601.22143) (2026)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`","html":"
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تفاصيل المشهد (السيناريو):
\n\n
البداية (0:00 - 0:03): الصورة: الكاميرا مثبتة (أو محمولة باليد بأسلوب الـ Vlog)، تبدأ بلقطة مقربة على \"القمريات\" (النوافذ الزجاجية الملونة) وهي تعكس ضوء الشمس على الجدار الحجري، ثم تنزل الكاميرا لتظهر الفتاة جالسة على الأرض وتعدل جلستها. النص على الشاشة: \"أجواء رمضان في اليمن ما تشبه أي مكان ❤️\" الصوت: صوت خلفي خافت لأناشيد ترحيبية برمضان (مثل \"يا مرحبًا يا رمضان\") أو صوت أذان بعيد.
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تفاصيل المشهد (السينا ريو):
\n\n
البداية (0:00 - 0:03): الصورة: الكاميرا مثبتة (أو محمولة باليد بأسلوب الـ Vlog)، تبدأ بلقطة مقربة على \"القمريات\" (النوافذ الزجاجية الملونة) وهي تعكس ضوء الشمس على الجدار الحجري، ثم تنزل الكاميرا لتظهر الفتاة جالسة على الأرض وتعدل جلستها. النص على الشاشة: \"أجواء رمضان في اليمن ما تشبه أي مكان ❤️\" الصوت: صوت خلفي خافت لأناشيد ترحيبية برمضان (مثل \"يا مرحبًا يا رمضان\") أو صوت أذان بعيد.
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MOVA is an open-source model that generates synchronized audio-visual content using a Mixture-of-Experts architecture with 32 billion parameters, supporting image-text to video-audio generation tasks.
AI-generated summary
Audio is indispensable for real-world video, yet generation models have largely overlooked audio components. Current approaches to producing audio-visual content often rely on cascaded pipelines, which increase cost, accumulate errors, and degrade overall quality. While systems such as Veo 3 and Sora 2 emphasize the value of simultaneous generation, joint multimodal modeling introduces unique challenges in architecture, data, and training. Moreover, the closed-source nature of existing systems limits progress in the field. In this work, we introduce MOVA (MOSS Video and Audio), an open-source model capable of generating high-quality, synchronized audio-visual content, including realistic lip-synced speech, environment-aware sound effects, and content-aligned music. MOVA employs a Mixture-of-Experts (MoE) architecture, with a total of 32B parameters, of which 18B are active during inference. It supports IT2VA (Image-Text to Video-Audio) generation task. By releasing the model weights and code, we aim to advance research and foster a vibrant community of creators. The released codebase features comprehensive support for efficient inference, LoRA fine-tuning, and prompt enhancement.
البداية (0:00 - 0:03): الصورة: الكاميرا مثبتة (أو محمولة باليد بأسلوب الـ Vlog)، تبدأ بلقطة مقربة على "القمريات" (النوافذ الزجاجية الملونة) وهي تعكس ضوء الشمس على الجدار الحجري، ثم تنزل الكاميرا لتظهر الفتاة جالسة على الأرض وتعدل جلستها. النص على الشاشة: "أجواء رمضان في اليمن ما تشبه أي مكان ❤️" الصوت: صوت خلفي خافت لأناشيد ترحيبية برمضان (مثل "يا مرحبًا يا رمضان") أو صوت أذان بعيد.
البداية (0:00 - 0:03): الصورة: الكاميرا مثبتة (أو محمولة باليد بأسلوب الـ Vlog)، تبدأ بلقطة مقربة على "القمريات" (النوافذ الزجاجية الملونة) وهي تعكس ضوء الشمس على الجدار الحجري، ثم تنزل الكاميرا لتظهر الفتاة جالسة على الأرض وتعدل جلستها. النص على الشاشة: "أجواء رمضان في اليمن ما تشبه أي مكان ❤️" الصوت: صوت خلفي خافت لأناشيد ترحيبية برمضان (مثل "يا مرحبًا يا رمضان") أو صوت أذان بعيد.