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ByteDance is cooking! a solid rival to LTX2. ALIVE: Unified audio-video generation; - T2VA, I2VA, lifelike vids with synced sound; - dynamic, photorealistic, trained on high-quality data. - MMDiT, 480p base gens to 1080p

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Wildminder

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12,663 görüntüleme • 5 ay önce •via X (Twitter)

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As part of Meta Movie Gen, we trained a 13B parameter audio generation model that can take a video + optional text prompts to generate high quality audio — including ambient sound, foley & instrumental background music — all synced to the video. Details ➡️
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As part of Meta Movie Gen, we trained a 13B parameter audio generation model that can take a video + optional text prompts to generate high quality audio — including ambient sound, foley & instrumental background music — all synced to the video. Details ➡️

AI at Meta

76,692 görüntüleme • 1 yıl önce

🚨 It is here! Kling 2.6 is launching exclusively on fal day 0! 🎬 Native audio generation for text-to-video and image-to-video 🎵 Cinematic storytelling with expressive audio performances ✨ High-intensity VFX with detailed sound design
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🚨 It is here! Kling 2.6 is launching exclusively on fal day 0! 🎬 Native audio generation for text-to-video and image-to-video 🎵 Cinematic storytelling with expressive audio performances ✨ High-intensity VFX with detailed sound design

fal

81,095 görüntüleme • 8 ay önce

Sound Effects 1.0 from Sonilo is now available on fal. Generate realistic sound effects from video or text. Upload a video to get a fully synced audio track, or describe the exact sound you need with a text prompt. Generated in seconds.
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Sound Effects 1.0 from Sonilo is now available on fal. Generate realistic sound effects from video or text. Upload a video to get a fully synced audio track, or describe the exact sound you need with a text prompt. Generated in seconds.

fal

20,420 görüntüleme • 16 gün önce

Meta announces Movie Gen A Cast of Media Foundation Models We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabilities such as precise instruction-based video editing and generation of personalized videos based on a user’s image. Our models set a new state-of-the-art on multiple tasks: text-to-video synthesis, video personalization, video editing, video-to-audio generation, and text-to-audio generation. Our largest video generation model is a 30B parameter transformer trained with a maximum context length of 73K video tokens, corresponding to a generated video of 16 seconds at 16 frames-per-second. We show multiple technical innovations and simplifications on the architecture, latent spaces, training objectives and recipes, data curation, evaluation protocols, parallelization techniques, and inference optimizations that allow us to reap the benefits of scaling pre-training data, model size, and training compute for training large scale media generation models. We hope this paper helps the research community to accelerate progress and innovation in media generation models
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Meta announces Movie Gen A Cast of Media Foundation Models We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabilities such as precise instruction-based video editing and generation of personalized videos based on a user’s image. Our models set a new state-of-the-art on multiple tasks: text-to-video synthesis, video personalization, video editing, video-to-audio generation, and text-to-audio generation. Our largest video generation model is a 30B parameter transformer trained with a maximum context length of 73K video tokens, corresponding to a generated video of 16 seconds at 16 frames-per-second. We show multiple technical innovations and simplifications on the architecture, latent spaces, training objectives and recipes, data curation, evaluation protocols, parallelization techniques, and inference optimizations that allow us to reap the benefits of scaling pre-training data, model size, and training compute for training large scale media generation models. We hope this paper helps the research community to accelerate progress and innovation in media generation models

AK

62,719 görüntüleme • 1 yıl önce

Make Pixels Dance: High-Dynamic Video Generation paper page: Creating high-dynamic videos such as motion-rich actions and sophisticated visual effects poses a significant challenge in the field of artificial intelligence. Unfortunately, current state-of-the-art video generation methods, primarily focusing on text-to-video generation, tend to produce video clips with minimal motions despite maintaining high fidelity. We argue that relying solely on text instructions is insufficient and suboptimal for video generation. In this paper, we introduce PixelDance, a novel approach based on diffusion models that incorporates image instructions for both the first and last frames in conjunction with text instructions for video generation. Comprehensive experimental results demonstrate that PixelDance trained with public data exhibits significantly better proficiency in synthesizing videos with complex scenes and intricate motions, setting a new standard for video generation.
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Make Pixels Dance: High-Dynamic Video Generation paper page: Creating high-dynamic videos such as motion-rich actions and sophisticated visual effects poses a significant challenge in the field of artificial intelligence. Unfortunately, current state-of-the-art video generation methods, primarily focusing on text-to-video generation, tend to produce video clips with minimal motions despite maintaining high fidelity. We argue that relying solely on text instructions is insufficient and suboptimal for video generation. In this paper, we introduce PixelDance, a novel approach based on diffusion models that incorporates image instructions for both the first and last frames in conjunction with text instructions for video generation. Comprehensive experimental results demonstrate that PixelDance trained with public data exhibits significantly better proficiency in synthesizing videos with complex scenes and intricate motions, setting a new standard for video generation.

AK

102,444 görüntüleme • 2 yıl önce

The first truly open-source audio-video model. LTX-2 is a DiT-based foundation model with all core video generation capabilities in one unified model. Designed to run locally on consumer GPUs. - text-to-video - image-to-video - and video-to-video modes 100% open-source.
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The first truly open-source audio-video model. LTX-2 is a DiT-based foundation model with all core video generation capabilities in one unified model. Designed to run locally on consumer GPUs. - text-to-video - image-to-video - and video-to-video modes 100% open-source.

Akshay 🚀

66,088 görüntüleme • 7 ay önce

🎬 Lovart x Veo 3 is live! Start creating high-quality AI videos with native sound—including dialogue, ambient FX, and dynamic camera movement. The demo below? 100% generated in Lovart using Veo 3 — cinematic visuals, synced speech, and immersive audio in one seamless output. How to use Veo 3 in Lovart: 1️⃣ Just type: "use veo3..." to generate a video 2️⃣ Or select Veo 3 from the Custom Mode dropdown #AIvideo #Veo3 #Lovart #LovartAI #LovartBeta
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🎬 Lovart x Veo 3 is live! Start creating high-quality AI videos with native sound—including dialogue, ambient FX, and dynamic camera movement. The demo below? 100% generated in Lovart using Veo 3 — cinematic visuals, synced speech, and immersive audio in one seamless output. How to use Veo 3 in Lovart: 1️⃣ Just type: "use veo3..." to generate a video 2️⃣ Or select Veo 3 from the Custom Mode dropdown #AIvideo #Veo3 #Lovart #LovartAI #LovartBeta

LovartAI

11,732 görüntüleme • 1 yıl önce

Sonilo has released Sound Effects 1.0, a video-native audio model that can read on-screen motion, scene context, and timing. > It can make sound effects synced to the footage. > Video-to-Sound-Effects runs automatically without requiring a prompt. > Text-to-Sound-Effects is able to generate standalone assets from a written description.
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Sonilo has released Sound Effects 1.0, a video-native audio model that can read on-screen motion, scene context, and timing. > It can make sound effects synced to the footage. > Video-to-Sound-Effects runs automatically without requiring a prompt. > Text-to-Sound-Effects is able to generate standalone assets from a written description.

🚨 AI News | TestingCatalog

15,523 görüntüleme • 13 gün önce

Seed-Music A Unified Framework for High Quality and Controlled Music Generation discuss: We introduce Seed-Music, a suite of music generation systems capable of producing high-quality music with fine-grained style control. Our unified framework leverages both auto-regressive language modeling and diffusion approaches to support two key music creation workflows: controlled music generation and post-production editing. For controlled music generation, our system enables vocal music generation with performance controls from multi-modal inputs, including style descriptions, audio references, musical scores, and voice prompts. For post-production editing, it offers interactive tools for editing lyrics and vocal melodies directly in the generated audio.
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Seed-Music A Unified Framework for High Quality and Controlled Music Generation discuss: We introduce Seed-Music, a suite of music generation systems capable of producing high-quality music with fine-grained style control. Our unified framework leverages both auto-regressive language modeling and diffusion approaches to support two key music creation workflows: controlled music generation and post-production editing. For controlled music generation, our system enables vocal music generation with performance controls from multi-modal inputs, including style descriptions, audio references, musical scores, and voice prompts. For post-production editing, it offers interactive tools for editing lyrics and vocal melodies directly in the generated audio.

AK

32,967 görüntüleme • 1 yıl önce

Wan2.5: Let Sound Take the Director's Chair! Native audio-driven video generation lets you shape visuals with voice, text, or images. Create up to 10s of high-quality, narrative-rich content. Your voice, your vision—brought to life. Try Wan 2.5-Preview today!
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Wan2.5: Let Sound Take the Director's Chair! Native audio-driven video generation lets you shape visuals with voice, text, or images. Create up to 10s of high-quality, narrative-rich content. Your voice, your vision—brought to life. Try Wan 2.5-Preview today!

Alibaba Cloud

3,243,746 görüntüleme • 7 ay önce

Today we're announcing the open-source release of HunyuanVideo-Foley, our new end-to-end Text-Video-to-Audio (TV2A) framework for generating high-fidelity audio.🚀 This tool empowers creators in video production, filmmaking, and game development to generate professional-grade audio that precisely aligns with visual dynamics and semantic context, addressing key challenges in V2A generation.🔊 Key Innovations: 🔹Exceptional Generalization: Trained on a massive 100k-hour multimodal dataset, the model generates contextually-aware soundscapes for a wide range of scenes, from natural landscapes to animated shorts. 🔹Balanced Multimodal Response: Our innovative multimodal diffusion transformer (MMDiT) architecture ensures the model balances video and text cues, generating rich, layered sound effects that capture every detail—from the main subject to subtle background elements. 🔹High-Fidelity Audio: Using a Representation Alignment (REPA) loss function and a powerful Audio VAE, we've improved generation stability and producing professional-grade audio, free of noise and inconsistencies. HunyuanVideo-Foley achieves SOTA on multiple benchmarks, surpassing all open-source models in audio quality, visual-semantic alignment, and temporal alignment. 👉Try it now: 🌐Project Page: 🔗Code: 📄Technical Report: 🤗Hugging Face:
1:16

Today we're announcing the open-source release of HunyuanVideo-Foley, our new end-to-end Text-Video-to-Audio (TV2A) framework for generating high-fidelity audio.🚀 This tool empowers creators in video production, filmmaking, and game development to generate professional-grade audio that precisely aligns with visual dynamics and semantic context, addressing key challenges in V2A generation.🔊 Key Innovations: 🔹Exceptional Generalization: Trained on a massive 100k-hour multimodal dataset, the model generates contextually-aware soundscapes for a wide range of scenes, from natural landscapes to animated shorts. 🔹Balanced Multimodal Response: Our innovative multimodal diffusion transformer (MMDiT) architecture ensures the model balances video and text cues, generating rich, layered sound effects that capture every detail—from the main subject to subtle background elements. 🔹High-Fidelity Audio: Using a Representation Alignment (REPA) loss function and a powerful Audio VAE, we've improved generation stability and producing professional-grade audio, free of noise and inconsistencies. HunyuanVideo-Foley achieves SOTA on multiple benchmarks, surpassing all open-source models in audio quality, visual-semantic alignment, and temporal alignment. 👉Try it now: 🌐Project Page: 🔗Code: 📄Technical Report: 🤗Hugging Face:

Tencent Hy

122,706 görüntüleme • 11 ay önce

Google Vids is an easy-to-use video editing suite, and we just added new AI capabilities, starting with: High-quality video generation with Veo 3.1, available to everyone at no cost 🎬 ✨ Find out what else is new 👇 then get started creating at
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Google Vids is an easy-to-use video editing suite, and we just added new AI capabilities, starting with: High-quality video generation with Veo 3.1, available to everyone at no cost 🎬 ✨ Find out what else is new 👇 then get started creating at

Google Workspace

252,280 görüntüleme • 4 ay önce

Wan2.5: Let Sound Take the Director’s Chair! 🎬 Today, we’re excited to unveil another major feature in our powerful Wan 2.5 Preview: Native Audio-Driven Video Generation. ✨ Now you can use audio input directly for both text-to-video and image-to-video generation. Combine audio with text prompts or a reference image to shape your video's narrative. ✨ With support for videos up to 10 seconds and enhanced video quality, unlock a richer visual space where more engaging stories come to life.
0:33

Wan2.5: Let Sound Take the Director’s Chair! 🎬 Today, we’re excited to unveil another major feature in our powerful Wan 2.5 Preview: Native Audio-Driven Video Generation. ✨ Now you can use audio input directly for both text-to-video and image-to-video generation. Combine audio with text prompts or a reference image to shape your video's narrative. ✨ With support for videos up to 10 seconds and enhanced video quality, unlock a richer visual space where more engaging stories come to life.

Wan

52,119 görüntüleme • 10 ay önce

BOOM! Been testing this for quite a while and absolutely blown away. Meet Open Source and FREE NotaGen a symbolic music generation model aims to producing high-quality classical sheet music. It is pre-trained on 1.6M pieces of music, and then fine-tuned on approximately 9K high-quality classical compositions conditioned on ``period-composer-instrumentation'' prompts. Link:
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BOOM! Been testing this for quite a while and absolutely blown away. Meet Open Source and FREE NotaGen a symbolic music generation model aims to producing high-quality classical sheet music. It is pre-trained on 1.6M pieces of music, and then fine-tuned on approximately 9K high-quality classical compositions conditioned on ``period-composer-instrumentation'' prompts. Link:

Brian Roemmele

30,357 görüntüleme • 1 yıl önce

Researchers at Meta recently shared MAGNeT, a single non-autoregressive transformer model for text-to-music & text-to-sound generation capable of generating audio on-par with the quality of SOTA models — at 7x the speed. MAGNeT is open source as part of AudioCraft. Hear audio samples and get more details on this work ➡️
0:51

Researchers at Meta recently shared MAGNeT, a single non-autoregressive transformer model for text-to-music & text-to-sound generation capable of generating audio on-par with the quality of SOTA models — at 7x the speed. MAGNeT is open source as part of AudioCraft. Hear audio samples and get more details on this work ➡️

AI at Meta

122,001 görüntüleme • 2 yıl önce

"Born to Be Alive" by Patrick Hernandez is a 1978 disco anthem that became a worldwide hit, known for its infectious groove and upbeat energy. In this special video mix, the legendary track is paired with a dynamic dance perfectly synced to the rhythm, creating an energetic and nostalgic throwback to the golden age of disco.
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"Born to Be Alive" by Patrick Hernandez is a 1978 disco anthem that became a worldwide hit, known for its infectious groove and upbeat energy. In this special video mix, the legendary track is paired with a dynamic dance perfectly synced to the rhythm, creating an energetic and nostalgic throwback to the golden age of disco.

𝐌𝐮𝐬𝐢𝐜 - 𝐌𝐨𝐯𝐢𝐞 - 𝐀𝐧𝐝 𝐌𝐨𝐫𝐞⭐️❤️

18,638 görüntüleme • 5 ay önce

I stopped writing giant video prompts. Now I build the audio first with Seed Audio 1.0. Dialogue, pauses, emotion, sound cues, all in one generation. Then I feed that audio into Seedance and the video follows the rhythm on its own. Timing, pacing, even camera feeling, all coming from the sound. Audio first. Video second. This is a different way to make AI films.
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I stopped writing giant video prompts. Now I build the audio first with Seed Audio 1.0. Dialogue, pauses, emotion, sound cues, all in one generation. Then I feed that audio into Seedance and the video follows the rhythm on its own. Timing, pacing, even camera feeling, all coming from the sound. Audio first. Video second. This is a different way to make AI films.

Anabiya

56,404 görüntüleme • 29 gün önce

BREAKING 🔥: ByteDance launched SeedRealtime, a native audio-visual full-duplex LLM! > SeedRealtime uses a unified architecture to natively fuse audio, video, and text, enabling real-time interaction over continuous multimodal streams and delivering a brand-new "watch, listen, and speak" experience. It is now live on the Doubao App for free, enabling voice and video conversations. Full-duplex Omni 🤯
1:29

BREAKING 🔥: ByteDance launched SeedRealtime, a native audio-visual full-duplex LLM! > SeedRealtime uses a unified architecture to natively fuse audio, video, and text, enabling real-time interaction over continuous multimodal streams and delivering a brand-new "watch, listen, and speak" experience. It is now live on the Doubao App for free, enabling voice and video conversations. Full-duplex Omni 🤯

🚨 AI News | TestingCatalog

85,077 görüntüleme • 1 gün önce

We're releasing Paris 2.0, which, to our knowledge, is the world's first decentralized trained video generation model. We benchmarked it against a monolithic model trained on the same data and compute budget, and Paris 2.0 outperformed the monolithic by ~2x on FVD benchmark.
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We're releasing Paris 2.0, which, to our knowledge, is the world's first decentralized trained video generation model. We benchmarked it against a monolithic model trained on the same data and compute budget, and Paris 2.0 outperformed the monolithic by ~2x on FVD benchmark.

Bidhan Roy

456,287 görüntüleme • 2 ay önce

New AI capabilities are coming to Google Vids, including high-quality video generation powered by Veo 3.1, available at no cost. Now, anyone with a Google account can bring stories to life from just a simple prompt or photo. Explore more of the new features 🧵
0:26

New AI capabilities are coming to Google Vids, including high-quality video generation powered by Veo 3.1, available at no cost. Now, anyone with a Google account can bring stories to life from just a simple prompt or photo. Explore more of the new features 🧵

Google

271,331 görüntüleme • 4 ay önce