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Topaz Labs - "We're launching Project Starlight: the first-ever diffusion model for video restoration. Enhance old, low-quality videos to stunning high-resolution. This is our biggest leap since Video AI was first launched."

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Chubby♨️

126,564 subscribers

67,019 Aufrufe • vor 1 Jahr •via X (Twitter)

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11 Kommentare

Profilbild von Carl Peterson
Carl Petersonvor 1 Jahr

Something tells me most of these users won’t be enhancing moon landing footage

Profilbild von Akool Inc
Akool Incvor 1 Jahr

AI has made it easy for anyone to create realistic avatar videos without expensive gear. AKOOL and Synthesia are top choices for AI-generated "talking photo" videos. Which one is best for your team?

Profilbild von VascularHand
VascularHandvor 1 Jahr

I have a subscription to their video product...I wonder if this will be included or a stand alone thing.

Profilbild von Chubby♨️
Chubby♨️vor 1 Jahr

Nice. Is it good so far?

Profilbild von Ian Lucas
Ian Lucasvor 1 Jahr

So cool

Profilbild von Tim Eckard
Tim Eckardvor 1 Jahr

I use Topaz Labs software and it's amazing both for video and photography.

Profilbild von Chubby♨️
Chubby♨️vor 1 Jahr

Good to hear

Profilbild von Drew 👷‍♂️ 🛠️ 🚀
Drew 👷‍♂️ 🛠️ 🚀vor 1 Jahr

They need to enhance the JFK video

Profilbild von erosYume
erosYumevor 1 Jahr

surprised they're still in the game, used to use some of their stuff in photoshop way back.

Profilbild von TMS
TMSvor 1 Jahr

What's video restoration good for? "ENHANCE?"

Profilbild von L8NTLABS
L8NTLABSvor 1 Jahr

Project Starlight sounds like a game-changer for video restoration. I can already think of a few old family videos that could benefit from this technology. The potential for preserving memories and historical footage is huge.

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A new frontier. Project Starlight—the first and only diffusion-based AI model for enhancing video. Launching soon.
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Wow 🤩 the response to Project Starlight, the first-ever diffusion model for AI video restoration, has been incredible🚀 Many of you couldn't wait and sent us your videos to restore with Starlight So let’s make it a thing: Send us your videos, and we’ll restore them for free using Starlight 🌟 Read instructions in 🧵👇 Like & comment Starlight to get early access, if you haven’t done so already #ProjectStarlight
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Wow 🤩 the response to Project Starlight, the first-ever diffusion model for AI video restoration, has been incredible🚀 Many of you couldn't wait and sent us your videos to restore with Starlight So let’s make it a thing: Send us your videos, and we’ll restore them for free using Starlight 🌟 Read instructions in 🧵👇 Like & comment Starlight to get early access, if you haven’t done so already #ProjectStarlight

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Upscale-A-Video: Temporal-Consistent Diffusion Model for Real-World Video Super-Resolution paper page: Text-based diffusion models have exhibited remarkable success in generation and editing, showing great promise for enhancing visual content with their generative prior. However, applying these models to video super-resolution remains challenging due to the high demands for output fidelity and temporal consistency, which is complicated by the inherent randomness in diffusion models. Our study introduces Upscale-A-Video, a text-guided latent diffusion framework for video upscaling. This framework ensures temporal coherence through two key mechanisms: locally, it integrates temporal layers into U-Net and VAE-Decoder, maintaining consistency within short sequences; globally, without training, a flow-guided recurrent latent propagation module is introduced to enhance overall video stability by propagating and fusing latent across the entire sequences. Thanks to the diffusion paradigm, our model also offers greater flexibility by allowing text prompts to guide texture creation and adjustable noise levels to balance restoration and generation, enabling a trade-off between fidelity and quality. Extensive experiments show that Upscale-A-Video surpasses existing methods in both synthetic and real-world benchmarks, as well as in AI-generated videos, showcasing impressive visual realism and temporal consistency.
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